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Hi then, it's Nicholas Kontopoulos.
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I'm the VP of Marketing for Twilio Asia Pacific Japan.
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And welcome back to Decoding Trust.
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In this series, we're going to explore what is it, what it takes to build and maintain trust in today's business world, from company culture to customer experience, security, and beyond.
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In our last episode, we talked about why trust is essential for businesses and for the people inside and outside of the organizations.
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Today, we're diving into one of the most complex and pressing challenges businesses face.
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That is balancing privacy, transparency, and personalization.
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We as all, we're all consumers and we all want personalized experiences.
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I don't know about you, but I love when I get personalized experiences.
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And we know this.
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Businesses know this.
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But it's a real challenge for a lot of businesses.
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Like last year, 76% of businesses said that personalizing customer engagement was a high or critical priority for their businesses.
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This is taken from our Twilio State of Customer Engagement report for last year.
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So I think you should be able to access that in the resource section.
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So we're on the right track, but it isn't easy.
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While the majority of customers want personalization, guess what?
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They're also demanding privacy and transparency.
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This is the balance that businesses are struggling to get right.
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Again, if I refer to our state of customer engagement report, 40% of businesses called finding the balance between security and customer experience is one of their most pressing challenges.
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So today we're going to explore this delicate balance.
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We'll explore how brands can personalize experiences without crossing privacy boundaries.
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And we'll talk about the role technology plays in ensuring transparency while keeping data secure.
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So I'm really excited today.
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We've got Stefan Sheela here with me today.
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Stefan is uh Stephen, sorry, is an influential voice in technology and AI.
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He was the former CEO of Facebook, ANZ, and is now the CEO of OmniNescent, a groundbreaking AI startup that has won numerous awards.
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He advises global brands like Google and Qantas and is a regular media commentator on the Wall Street Journal, Forbes, and ABC.
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So, Steven, thanks for being here, mate.
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I'd love uh to have you just also introduce yourself to the audience and maybe uh share a little bit more about your fascinating company that you've launched um and the work you're doing, because it really is true, truly groundbreaking.
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Yeah, great to be here, Nick.
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Thanks for to Twilio for asking me to be here.
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Thanks to you for hosting it.
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I I'm really lucky in my journey, Nick, as you mentioned before, I was at Facebook for a long time.
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Back when it was Facebook, now it's uh called something else.
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Uh but since I left Facebook, one of the things I was um fascinated by was how do how do we use AI, not just to you know serve you with more ads or optimize your feed, but how do we use it to really shift humanity forward?
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Uh use AI for the benefit of humankind.
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And I started to get fascinated by the human brain, which is the most complex thing in the universe.
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So everything open AI is building today is dwarfed by what your the complexity of what's between your two ears.
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And luckily, with the rise of AI and computing power and the algorithm we have today, we can now start to make sense of the brain in a way it was never possible before.
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So the company I built over the past few years with some other amazing people is the world leader in using AI to decode the brain.
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We build tools for mapping the human brain.
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Almost think of it a Google maps for the human brain.
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And the so what of all that is it's it's a real breakthrough for things like mental illness and neurodegenerative diagnosis, treatment, treatment, targeting.
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And you know, you think about when you you take a, you, you get a say you get depressed today, which many of us uh tragically do, you know, you go and you get a you get a pill.
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Well, it's the same pill that everybody else gets.
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Um, but that pill, of course, 40% of the time it doesn't work.
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Why?
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Because it's not targeted at your specific problem because doctors say don't understand the complexity of the brain.
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So we're building tools into that space today using AI, and it's you know, it's truly revolutionary technology.
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So um I'm very lucky to build that with the the people I do today.
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I mean, it's a bold vision and and ultimately really groundbreaking and exciting.
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And again, you know, that what you just described there, the the uh ability to tailor and target at an individual level, I think is uh amazing.
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Um, that's the same theme.
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Yeah, I would think it ties nicely into the theme of that, uh of what we're exploring, but obviously it a in a in a really uh beneficial way in from a ultimately what will benefit a lot of humans um in terms of their ability to battle some of the struggles they've got.
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Yeah, so that's amazing, Mighty.
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So thanks for that intro.
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And we're gonna kick start off with a poll.
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I like making my audiences work.
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So um I really would love to bring the audience into the poll, which will get pushed in front of you right now.
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And and what I want to hear is everyone's um ultimately, you know, is experiencing challenges on this topic in one way, shape, or form.
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So what do you feel is the biggest challenge?
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Um, this is a question to the audience.
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What do you feel is the biggest challenge in balancing privacy, transparency, and personalization?
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And you've got several choices here.
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We've got earning customer trust while collecting and using data, you know, providing personalized experiences without overstepping uh privacy boundaries, which is always tough because everyone has different boundaries, communicating data practices in a clear and transparent way, keeping up with changing privacy regulations, which also is a real challenge for uh marketing leaders that operate in a region like uh Amir or uh in particular an APJ, where we've got lots of different regulations.
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And there's another option, so feel free to put some free text in there.
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So if you can start uh, you know, marking up uh what option you feel is the biggest challenge, and uh we can then get a sense or pulse check of where everyone's at in that respect.
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So, Marco, hopefully you've got the uh poll up and running.
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Not sure if that's been pushed.
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Uh while it's going while it's going on, Nick.
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I uh I noticed there wasn't an all of the all of the above option, which I think that would be my choice if I had one.
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It will be all of the above.
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Everything you mentioned there um it it all comes together as a huge challenge to figure out where's where's the balance.
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Um, and I think that's what we're gonna explore more today.
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And I think part of that balance is just born out of the fact that what you privacy used to be uh assumed, you know, you knew that nobody, nobody, the butcher didn't know anything about you until you told the butcher about yourself.
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You know, Toyo didn't know who you were until you walked in the dealership and asked that asked to buy a car.
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We know that world is different now.
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So you want personalization, but you also want privacy.
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And I even think consumers don't know where they they're drawing the line themselves.
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100%.
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And I agree with you.
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Uh it is this definitely should have been all of the above because that is uh, if I think about it just from my world, it I'm considering all those.
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I can't actually see the actual results.
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I'm not sure that there's a glitch going on here.
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So, Marco in the chat, I don't know if you can give me an indication of which one was a top choice.
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Otherwise, what we'll we'll do is we'll move on.
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Um, you know, maybe setting the scene.
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All right.
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Well, let's set the scene.
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Amazon was fined$25 million back in 23 for retaining children's voice data captured through Alexa devices.
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Um, I remember my kids talking to these devices quite excitedly.
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So, why do you think it's a challenge it's so challenging uh for businesses to strike this right balance between privacy and personalization, Steven?
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Well, let me let me go back a little bit because I think it's I think for all of us in business, it's it's good to know where we are sitting and the kind of the evolution of trust and privacy.
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And I've I've read a lot about this.
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I build companies in this space, I've talked to leaders, uh, but so this is based on my own experience.
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I'm not quoting for a from a poll or a survey, but in and I I what I think has happened over the past 20, 30 years is we went from a world where privacy was essentially assumed, in the sense as the example I gave before, Toyota didn't know anything about you, and I'm just using them as an example, until you walked into the dealership and you said you want to buy a car.
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And that's when the relationship started.
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Now, you would have triggered the relationship, most likely.
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You would have you've given them the information.
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Here's my name, phone number, kind of car I want, how many kids I have, whatever it is that was informing your purchase, you would have shared at that point.
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Um, fast forward to today, and I asked this question what do others know about you and what are they doing with it?
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And the truth is, not even Mark Zuckerberg or Elon Musk or Jeff Bezos know the answer to that question.
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We none of us do.
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So I think there's this, there's been this move, and it has happened because of largely because of the rise of the internet and the rise of data as the the key asset that all of us as consumers didn't know was so valuable, but companies like Google and Facebook and others did realize it was valuable and started to hoover it up.
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And so we have these data profiles that have been assembled by all the companies trying to reach us, and that can be good because it can create more personalization, but I think it can also be um invasive, it can be creepy, it can be um, it can go wrong in a way that we don't have full control of or transparency of what's going on.
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And um, there's been obviously there's been changes in regulation, GDPR, other privacy rules the past uh you know 10, 15 years.
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But still, I actually before um we got on this call, I was uh I start to ponder things and I I actually thought to myself, you know, how how many words are in like Meta's privacy statement, right?
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How many words are in Google's?
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How many words in Telstras or CBA's or you know, you know, or or Grab or you know, you and aim your company.
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Well, it's thousands.
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I mean, just to give you a sense, Meta has 9,000 words, you know, uh, Google has 8,000 words, you know, even the banks in Australia six, 7,000 words in the privacy statements.
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Now, how long would it take you to read that and absorb it?
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And it probably would take you, uh and I've tried, takes you hours, right?
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There's all kinds of deles and nomenclature understand, and click here to read another document.
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And you know, here's what does GDPR do and not do?
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Does it apply to you?
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And all these definitions.
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So the reality is, now which is the irony, is none of us understand that.
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Yet in the age of regenerative AI, you know, I can type anything I want into one of these, uh, you know, one of these Gen AI chatbots, and I get, you know, here's a PhD on any topic in the world.
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Yet I'm still like left to read your 9,000 word privacy statement.
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So I think brands are not putting themselves in a in a position to win.
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It's simply they're they've got a very clunky old way of understanding what are the rules and and then how do I move as a consumer?
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Where do I move the the the cursor along, you know, from super private to more open in in a sort of an exchange with you?
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So that's uh just some thoughts about where the moment we're in.
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And I think you know, I think brands are still still kind of living in the old world that we all, many of us grew up in, but the new world is very, very different.
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Yeah, I couldn't agree more.
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And it's moving at pace, right?
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Like the the speed.
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I mean, I'm um Gary Hamilton, I'm a big fan of, and I remember him saying a long time ago, and it it couldn't be more true today, is change is changing in itself in terms of the pace and rate of change.
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And that's putting a huge pressure, like you said, on an architecture that powers a lot of the businesses that is quite data, built really for the 19th and 20th century, if you really think about where a lot of the models that are still being used by businesses is really inhibiting their ability to keep pace with um uh their consumer base that and and employees that are serving them, right?
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I think that's another thing we often talk about customers, but it's also where is the the role of the employee in this picture also is how do we ensure that when they're having those conversations with customers, they're also being uh given the capabilities to explain what the privacy statement is, for example.
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Like you said, I would hate to try to imagine the difficulty I'd have doing that.
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Maybe um that's a good way to sort of if I because I like thinking in terms of people, process, and technology, uh Stephen.
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Um, and we as a technologist, people expect me to always go to technology straight away.
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But I really feel, and I'd love to get your thoughts on this, the importance of really exploring the impact of, you know, if we think about business transformation, we need to always start with the people side of the equation.
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And that's ultimately the customers we're serving, the employees that are going to serve them, and even the partners that are involved in that process.
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So with that in mind, I mean, how do you see businesses ultimately successfully uh successfully empowering their employees to champion the importance of balancing privacy and transparency and personalization?
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I mean, you know, the privacy policy.
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Again, someone wrote that, right?
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So, you know, how do we how do we set our employees up for success in navigating this new world?
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Yeah, I it's interesting because I I've been building a company in AI in and very sensitive data the past few years.
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The business I built in brain AI called it's called omniscient.
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And we're looking into the heart of what it is to be human.
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I mean, we're decoding people's brains, we're seeing things that or could see things that are no more personal than any data you have anywhere else.
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It's it's essentially your your soul.
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We can start to almost decode.
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And um we have our very we think we're very thoughtful and ethical about how we build in that world.
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And we tried to build the company from uh the first principles have been around ethics and and giving people agency over their data.
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Now, um partly this is true for us because my um one of my co-founders is a is a medical doctor.
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We build into the medical system today, the healthcare system, and there are a lot of controls there.
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You know, you're in most countries in the world, there's there's no data that's more protected than medical and healthcare data in every country in the world.
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So we don't see, for example, we never, even though I'm building a map of your brain, I don't know, I don't see personal personal data view.
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Everything we have is anonymized.
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We're not allowed to see P what's called PHI personal health, uh personal health information that we actually doesn't sit on our service, doesn't come into our cloud.
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But still, one thing I worry about is giving people agency over their data and their healthcare data.
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And there's a and data not just about what you did on the internet or you know, your social security number or your, you know, your any other identifying data, but data that's related to your biology, your genomics, your other omics, your connectomics, which is your connections, your brain.
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And then having agency over that data in a way that um you can make sensible decisions in your life.
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Now, the great thing about generative AI is it it's what is it?
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It's a copilot, it's an agent, an assistant.
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So I see a future, I'm not building this company, but I'd like I want to build it where there's agents that can help me monetize or control or control access to my data in a way that doesn't force me to read every 9,000 page or 9,000 words.
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So it seems like 9,000 page privacy statement, right?
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Of all the apps and tools that I use.
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Now, coming back to empowering employees, as you said, what we've tried to do is build a culture of transparency, disclosure, um, building with privacy by design in how we build everything that we do.
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And I think there's again, there's legacy companies.
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We we started five years ago, so we've been born in the age of AI.
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But companies that have been born, you know, decades ago or 100 years ago, you have legacy systems, legacy processes, legacy cultural norms.
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I really think you need to revisit and really work hard on privacy by design, which may run completely counter to how you do things today.
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And there's a lot of hard choices, I think, that need to be made inside organizations about, you know, what is truly right for the customer or for the ethical decisions you want to make as a business versus what's right for the bottom line.
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Those are not easy decisions, but I think having an honest discussion and debate with your organization and making sure people understand, you know, this is where we've landed as an organization.
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And these are the trade-offs that we understand we're making by landing there.
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So I find many um many businesses don't have that discussion with their employees.
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We we haven't really had that in many, many um, particularly legacy businesses.
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And I think that's really important, not just discussion to have, but we, you know, what's the new landing place that we need to get to?
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So that's sort of my my macro view.
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And I've got a lot of uh passion about it because of the company I've just been building the past few years.
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Well, I mean, yeah, it couldn't come from uh a better person.
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Obviously, you're living and breathing this now as an owner and builder of a business.
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I I yeah, I often say to folks, you is your company even AI ready before you even embark on unlocking this next generation of AI?
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And that's also an important distinction to make because I think AI has been around for a while, right?
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Like predictive AI.
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I mean, actually, AI as a term was coined back in 1953, machine learning three years later.
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So these aren't new concepts, they've been around for a while.
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But I think what we've seen is the convergence of sort of, you know, um, you know, the different technologies or capabilities coming together in recent times, which has obviously thrust this topic back into the spotlight in a in a way that is driving transformation.
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So therefore, we do need to think about, to your point, how do we prepare the organization and and and ensure that we're ultimately moving in the right direction and understanding what the roles and responsibilities are.
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Is that a fair statement?
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Yeah, yeah, I think that's a great what's happened the last few years, you're right, AI has been around a long time, but what has changed in the past couple years is the rise of generative AI on LLMs, which really we didn't have until three years ago.
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And now with the rise of that, what's it meant it's AI is much more accessible, much more usable, the user interface and the the natural language and human interface, the multimodal way human humans work, which is by vision, by by by sound, by by language.
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AI is now conversing in the same way.
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You don't to be a coder, you don't need to learn coding no learner coding language anymore.
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You can just you can just speak whatever language you speak.
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That's a huge change, right?
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That didn't exist before.
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And yet organizations are kind of as they need to be, they need to leap and get on to the AI revolution quickly.
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But the point you make, you need to be, you need to be, your culture needs to be AI ready.
00:18:27.759 --> 00:18:33.839
And I think I think there's a lot of organizations that are making mistakes in playing ahead of their culture.
00:18:34.160 --> 00:18:55.440
And you may not see the damage today, but the damage may start to come out in the next couple of years as we see wrong decisions being made, AI being applied in ways it shouldn't be, um disruption or destruction of customer trust and value when um you're trying to you're trying to the opposite, you're trying to make better experiences and you wind up making it worse.
00:18:55.759 --> 00:19:12.000
So um, and the re the reason I think we get there is and this is why I with this assumption I see a lot in a lot of business leaders that you know we know what's right for even even though you talk about customer centricity, there's still this assumption that, well, we know what's right for customers.
00:19:12.079 --> 00:19:17.759
They want more technology, they want more AI, they want more um options, they want more.
00:19:18.000 --> 00:19:19.680
And I don't think that's always true.
00:19:19.839 --> 00:19:24.880
I don't think that customers always want more to more technology, more AI, or even more options.
00:19:25.119 --> 00:19:31.359
I think they would just want to get to what matters quickly and they want to have some control over the nature of the relationship.
00:19:31.440 --> 00:19:38.480
Just like back in the old days, you know, when you when you walked into the Toyota dealership, it's what you told that dealer is what you disclosed.
00:19:38.640 --> 00:19:39.920
You were in control of it.
00:19:40.079 --> 00:19:43.920
Rather than, you know, you you shook his hand and he said, Oh, good to meet you.
00:19:44.079 --> 00:19:48.240
I'll tell you all about your needs as a as a car buyer because I know you're better than yourself.
00:19:48.400 --> 00:19:55.839
That might say sound exciting um as a personalization experience, but I think in terms of a privacy experience, it's it's not very exciting at all.
00:19:55.920 --> 00:19:57.839
It's a little, it's it's it's intrusive.
00:19:58.000 --> 00:20:06.160
So that balance, I think we're not with AI, we we are don't have cultures that are built to really make the right choices on that balance today.
00:20:06.480 --> 00:20:08.240
No, I I I couldn't agree more.
00:20:08.319 --> 00:20:26.319
And actually, I think it's um a nice little quick segue into where I want to double-click next um is uh really exploring this uh notion of the role of AI and and how we'll ultimately be collecting data and consent that enables that personalization.
00:20:26.400 --> 00:20:32.400
I I thought the Toyota example is a good example there, like in terms of where we've come from and where we're where where we are now.
00:20:32.720 --> 00:20:34.240
Um, how do you yeah?
00:20:34.319 --> 00:20:43.759
So, what do you see the role of AI being when it comes to collecting data and and you know playing a role in the consent uh that process that enables that personalization?
00:20:44.240 --> 00:20:47.680
I think there's an opportunity, a huge opportunity for brands.
00:20:47.839 --> 00:20:50.240
Um, and I've I've spoken about this before.
00:20:50.400 --> 00:20:56.240
I I think we've entered an age of permission-based marketing or consent-based marketing.
00:20:56.480 --> 00:21:05.359
And by that I mean getting permission and consent from consumers to go deeper into data collection, personalization, use of AI.
00:21:05.519 --> 00:21:10.319
I think that's what winning brands are going to do, rather than assuming there's a default setting for everybody.
00:21:10.400 --> 00:21:13.680
I think we've got an opportunity to say, no, where do you want your setting to be?
00:21:13.920 --> 00:21:20.000
And I just as an aside, I think one of those settings should be I want no AI in my product or service with you.
00:21:20.079 --> 00:21:24.000
I'm I'm I'm happy to go back to the the the analog way.
00:21:24.079 --> 00:21:27.519
You know, maybe I want to live an AI-free uh world.
00:21:27.759 --> 00:21:39.759
And and I almost think, I mean, I don't I'm not a big family regulation, but I almost think in some ways you know the government should encourage um you know many services and brands that they have to provide an AI-free alternative.
00:21:39.920 --> 00:21:45.279
Now I'm I'm big on AI, but I also believe that I think an AI free alternative should be available.
00:21:45.359 --> 00:21:52.319
So if you want to deal with your bank in a way that involves no AI, you should have the right to do that, or your telco or your or your social media provider, whoever.
00:21:52.480 --> 00:21:58.799
So I and it's just uh uh an aside, if I if you want to live an AI free life, I think you should have the right to do that.
00:21:59.039 --> 00:22:07.359
Um But coming back to data collection and AI, so uh I mean I said that I said before, what do people know about me and what are they doing with it?
00:22:07.519 --> 00:22:10.480
Well, that was hard enough before Generative AI came along.
00:22:10.640 --> 00:22:13.839
Now I would argue it's it's it's impossible.
00:22:14.720 --> 00:22:19.200
It truly is impossible to know what does uh generative AI know.
00:22:19.279 --> 00:22:28.079
What even even the you know the architects, the you know, even open AI doesn't know how open how ChatGPT is making its decisions or how it's uh processing things.
00:22:28.319 --> 00:22:31.359
And so we're living with black boxes all around us.
00:22:31.519 --> 00:22:43.279
I think the thing that's going to change though is one thing the opportunity, one is I said allowing consumers to s to to choose their setting in terms of how how AI fied they want their experience with you to be.
00:22:43.359 --> 00:22:51.200
I think that's uh that's an important way to, and that's and includes the data collection that takes place and or the data processing as well that takes place.
00:22:51.519 --> 00:22:59.839
But I think the second thing is to uh to allow consumers to uh I'm sorry, let me step back, not allow consumers.
00:22:59.920 --> 00:23:09.119
What's going to change is this, and it's changing already, is it's not going to be a my AI, you know, company X's AI talking to the consumer or approaching the consumer.
00:23:09.200 --> 00:23:12.400
It's going to be company X's AI talking to my AI.
00:23:12.559 --> 00:23:12.880
All right.
00:23:13.039 --> 00:23:16.640
So, and being another step removed from that consumer.
00:23:16.880 --> 00:23:19.039
Now, think about that challenge, right?
00:23:19.200 --> 00:23:29.759
So if I want to, if if if I'm a company and and I'm going to get to you, Nick, by to give you service or sell your product or show you an ad, but you've got your AI and you're talking to my AI.
00:23:29.920 --> 00:23:33.599
Well, now I got to get through your AI to get to your wallet somehow.
00:23:33.839 --> 00:23:39.599
And so optimizing this world is is happening, it's it's it's arrived.
00:23:39.759 --> 00:23:50.000
So optimizing for how what's the data exchange, what's the value exchange, what's the consent exchange in that interface, I think is going to be where again we're winning brands win.
00:23:50.640 --> 00:23:53.119
Ah, I couldn't agree more so much there.
00:23:53.279 --> 00:23:59.680
Um, yeah, definitely um the battle is going to be won or lost in that space.
00:23:59.759 --> 00:24:13.680
And I think it's also like we've obviously for the longest time marketers lived with the you know, relied on third-party data as a fuel to power their ability to personalize at scale.
00:24:13.839 --> 00:24:27.359
And, you know, I think where we've quickly moving to, and we'll even this is going to present some of the challenges you spoke about with you know the AIs working with one another, is the importance of first party and even zero-party data.
00:24:27.440 --> 00:24:39.039
And we define the latter as being the data that you know you willingly share with a brand, knowingly, you know, rich data that tells that brand who I am, what what I like, what I'm looking for, etc.
00:24:39.359 --> 00:24:52.880
And you know, obviously first party data being the data that you know I share, maybe not consciously or subconsciously and not aware of what what it's how it's being used, but those two data sets coming together and being used in a way that can really individualize that engagement.
00:24:53.200 --> 00:24:58.240
But there has to be a catalyst in order for me to want to share that data.
00:24:58.319 --> 00:25:00.480
And I think trust is a big part of that, right?
00:25:00.720 --> 00:25:04.480
So, you know, that trust anchors ultimately everything.
00:25:04.640 --> 00:25:10.400
And, you know, we need to create a, I guess as a business, you need to be creating a value proposition.
00:25:10.640 --> 00:25:18.640
If we go back to your your own endeavor in this space, obviously that is highly personal data that folks are sharing, right?
00:25:18.720 --> 00:25:27.119
So you've got to look after that data, cherish that data, and create a use the data in a way that actually creates a value back to the the giver of that data, right?
00:25:27.200 --> 00:25:28.400
Is that a fair statement?
00:25:28.640 --> 00:25:29.200
Yeah.
00:25:30.960 --> 00:25:31.440
Absolutely.
00:25:32.319 --> 00:25:40.960
I mean, there's a um we have a sort of truism on our business around, you know, we we hold nothing that's not necessary, right?
00:25:41.039 --> 00:25:44.720
That so anything that's not necessary, we we do not hold.
00:25:44.960 --> 00:25:52.160
And and secondly, giving as much sovereign control to the owner of that data as we possibly can.
00:25:52.319 --> 00:26:03.359
In fact, trying to look for ways to give more control to them and more agency to them, I think is the long term is going to benefit not just uh our business, but I think will benefit the the world.
00:26:03.440 --> 00:26:06.319
And we're trying to build tools that benefit humanity.
00:26:06.480 --> 00:26:16.160
And I think without giving humans agency over all their data and true transparency and control, the world is not going to be a better place.
00:26:16.319 --> 00:26:18.880
So that's like a meta thing that I believe in.
00:26:19.039 --> 00:26:21.599
Meta meta meaning big, not necessarily Facebook.
00:26:21.839 --> 00:26:24.400
Um and I know not all companies necessarily agree with that.
00:26:24.559 --> 00:26:34.559
And so, and perhaps all regulators don't agree with that, but that's the that's the philosophy that we have with our business because we're dealing with the most important data set in the world, which is which is your brain.
00:26:34.640 --> 00:26:37.359
There's nothing more critical and personal than that.
00:26:38.319 --> 00:27:00.240
And when it comes to looking after that data, um, you know, either in your sort of past roles or even in the current um capacities, what what processes do you recommend companies implement to prevent accident accidental exposure of personal um identifiable information during that collection aggregation process?
00:27:00.400 --> 00:27:05.359
Is there any sort of um pitfalls that can be avoided?
00:27:05.519 --> 00:27:05.759
Yeah.
00:27:06.480 --> 00:27:14.880
I mean, we we we have three buckets or three ways of thinking about safeguarding personal data in terms of processes, policies, et cetera.
00:27:14.960 --> 00:27:18.400
One is like the what are the organizational safeguards we put in place, right?
00:27:18.480 --> 00:27:25.279
So that's the what's the I mean there's a term there's like binding corporate rules and you know what are the what are the rules that we establish?
00:27:25.359 --> 00:27:26.559
How do we train our people in it?
00:27:26.640 --> 00:27:32.799
How do we how do we audit that um either internally or have external auditors audit that?
00:27:32.960 --> 00:27:42.160
The second is around sort of the technical safeguards, which is the deep space around, you know, you know, what are all the technical safety ones for if you're ICL compliance or SOC2 compliance?
00:27:42.240 --> 00:27:46.559
And a lot of that is you know laid out by other bodies, so it's not that you're dreaming up.
00:27:46.640 --> 00:27:48.160
There's there's ways to become compliant.
00:27:48.400 --> 00:27:50.960
And sometimes in our space, you have to be compliant.
00:27:51.119 --> 00:27:58.400
You know, a hospital won't deal with us unless we are so certified, SOC2 compliant, HIPAA compliant, all these, all these things, hip in the US.
00:27:58.559 --> 00:28:01.359
It's about healthcare, uh, how we control healthcare data.
00:28:01.599 --> 00:28:25.039
And then there's the contractual safeguards, not just that you have with customers, but it's how you choose your partners and your um, you know, the the trusted network of third parties that you have, because it's never just you and the customer, there's always others that have a potential access and potential positive and negative effects around security and the use of data.
00:28:25.200 --> 00:28:29.680
That's, you know, this is where vulnerabilities come in and cybersecurity becomes so important.
00:28:29.920 --> 00:28:39.279
You know, all these uh, you know, the data breaches we all hear about aren't, you know, rogue employees, they're they're third-party vulnerabilities generally that come through the door.
00:28:39.599 --> 00:28:45.920
So those three, those are the three chunks we think through, sort of organizational, technical, and then contractual.
00:28:46.160 --> 00:29:00.880
And we have kind of checkpoints for figuring out each one of those and whether we and you know, whether we're robust enough in each, and then continue to evolve it as our technology evolves, as rules and regulations evolve, as consumer uh expectations evolve.
00:29:00.960 --> 00:29:03.039
You know, do we evolve those as well?
00:29:03.279 --> 00:29:07.839
Because right now, as you know, particularly the AI, regulations changing fast.
00:29:08.160 --> 00:29:13.200
Consumer expectations are really almost unknown and certainly going to change fast.
00:29:13.440 --> 00:29:21.839
And then the data, the importance of data and this and the nature of data, the cleanliness of data is more important than ever.
00:29:22.000 --> 00:29:34.480
So there's a there's such a it's moving so quickly, it's almost like a, you know, these are living, living documents, living processes that need to be almost updated in real time as the world moves forward so quickly.
00:29:35.359 --> 00:29:36.400
Couldn't agree more.
00:29:36.559 --> 00:29:38.720
And actually, I love what you were saying there.
00:29:38.880 --> 00:29:43.839
Um uh it's a constantly evolution uh evolutionary process, right?
00:29:44.559 --> 00:29:49.440
It's not a once and done, let's put it on the shelf, come back, dust it off in a year's time and update.
00:29:50.079 --> 00:29:58.640
Um, interestingly, uh again, uh, I think what is faster than government regulation is actually human expectation.
00:29:58.880 --> 00:30:04.319
And uh that that's the real uh tip of the spear, right, in terms of trying to keep up with that.
00:30:04.480 --> 00:30:16.319
And that's where I think there is pressure on businesses, the smart businesses, to stay ahead of that as best as they can, because regulation, like you said, is moving to address issues that are surfacing up.
00:30:16.400 --> 00:30:20.160
But that still takes a little bit of time to work its way through the process.
00:30:20.640 --> 00:30:27.759
But our expectation as consumers isn't isn't uh is is is always going to be preceding that process, right?
00:30:27.839 --> 00:30:37.440
And therefore, brands, if they want to build that trust, need to be trying to anticipate where the changes need to occur before they actually occur, right?
00:30:37.599 --> 00:30:38.880
Is that a fair statement?
00:30:39.839 --> 00:30:40.319
Absolutely.
00:30:40.480 --> 00:30:48.799
Consumers change on a turn on a dime, regulators take years to catch up, um, and companies are caught in the middle, right?
00:30:48.960 --> 00:30:54.799
Trying to deal with the regulatory changes that are always lagging, but the consumers are always out ahead.
00:30:55.039 --> 00:30:56.720
And uh you said something earlier.
00:30:56.799 --> 00:31:07.359
I just wanted to give a it sort of sparked something in my mind, and and maybe the the the audience will definitely have this experience uh as consumers or as as business people.
00:31:07.759 --> 00:31:11.440
The um and this is my personal experience.
00:31:11.680 --> 00:31:17.200
I want to be able to choose where I get hyper-personalization, right?
00:31:17.279 --> 00:31:18.640
I I don't want it chosen for me.
00:31:18.720 --> 00:31:21.759
Now maybe that's just me, but I do think a lot of people are like this.
00:31:21.920 --> 00:31:25.039
And and I find I'll give you an example the other day.
00:31:25.200 --> 00:31:29.440
I um I was uh I had I was booking an airline, a flight on an airline.
00:31:29.920 --> 00:31:31.359
We'll go unnamed.
00:31:31.519 --> 00:31:33.279
Um, and uh great airline.
00:31:33.359 --> 00:31:41.279
I fly them a lot, and uh it was a frequent flyer flight, a lot of points, and it was going to be for somebody else in my family who's a miner.
00:31:41.440 --> 00:31:45.440
She's she's under 14, and so and she was gonna fly alone, unaccompanied.
00:31:45.680 --> 00:31:49.680
Okay, so online you can't do that for certain legal reasons.
00:31:49.759 --> 00:31:51.119
You have to then call in.
00:31:51.279 --> 00:31:52.160
And then I called in.
00:31:52.240 --> 00:31:59.680
They said, Well, you need to book it online as if it was an adult, then you need to call this number, and then they'll be able to change it to a to a uh unaccompanied minor.
00:31:59.759 --> 00:32:02.559
Okay, and they charge you a fee for that as well, which is good.
00:32:02.720 --> 00:32:07.119
So um they really they hit you every time they can, which is great.
00:32:07.279 --> 00:32:09.440
Um, but anyway, okay, got it.
00:32:09.519 --> 00:32:14.640
So when I called back, the person I spoke to, I'd explained everything, you know, and I my time is precious.
00:32:14.799 --> 00:32:19.680
My wife couldn't do it for me because she's not the cangle holder, it's my point, so I had to do it, you know.
00:32:19.759 --> 00:32:25.599
And then I wind up talking to a human being, and the truth is that human being had an accent that didn't really understand, it wasn't a good line.
00:32:25.680 --> 00:32:27.440
I'm like, why isn't AI doing this?
00:32:27.519 --> 00:32:36.400
You know, and then she said she couldn't handle it, and so she transferred me to somebody else, and then I had to wait on hold and eventually that other person comes on, and then they said, How can I help you?
00:32:36.640 --> 00:32:41.039
And all I said was, Didn't your colleague explain to you what my what my query is?
00:32:41.119 --> 00:32:41.759
No, they didn't.
00:32:41.920 --> 00:32:43.279
I had to re-explain it all again.
00:32:43.359 --> 00:32:53.839
And again, I'm sitting there going, like, I would have pressed the have a gen AI solve my problem button now on the phone, like choose one because I don't want to do this, right?
00:32:54.000 --> 00:32:58.160
This is not a big thing, and and it's a process.
00:32:58.319 --> 00:33:07.440
It took me, it took me 55 minutes to sort that out, and it's the simplest thing, uh, that at least in you know my experience.
00:33:07.599 --> 00:33:12.160
So in that case, I wanted hyper-personalization and I want it solved immediately.
00:33:12.240 --> 00:33:17.119
Yeah, but then other cases, I don't want to be hyper-personalized things, I want to be more anonymous.
00:33:17.200 --> 00:33:19.519
So, but I don't have the right to choose.
00:33:19.759 --> 00:33:22.640
And so I think that's a that's a big opportunity again.
00:33:22.720 --> 00:33:26.400
It's a challenge, but it's an opportunity, I think, for brands to to give that level of choice.
00:33:26.720 --> 00:33:34.799
No, I I love I love that example because I think uh most people will connect with that in one way, shape, or form, uh, having gone through that.
00:33:34.960 --> 00:33:38.079
And I think you you also referenced earlier the toggling idea, right?
00:33:38.160 --> 00:33:45.440
Like being able to toggle um sort of where you want that deeper personalization, but other areas where you won't want that.
00:33:45.519 --> 00:33:56.240
And I think this is again where the new frontier is of opportunity for a lot of brands, is to start thinking about how they can give that, you know, hyper individualization, dare I say it, right?
00:33:56.480 --> 00:33:59.920
In terms of what I'm comfortable with and what I'm not comfortable with.
00:34:00.079 --> 00:34:16.480
But also I think it's really important in the spirit of transparency, because we at Twitter we talk about accountability, transparency, and responsibility as being the three core pillars and how we think about AI, both not in terms of just how we build that into our products, but how we use the tools internally ourselves, right?
00:34:16.800 --> 00:34:24.239
Um, and I think being um transparent with uh customers about when they're using an AI is really important.
00:34:24.480 --> 00:34:26.400
And also creating off-ramps, right?
00:34:26.480 --> 00:34:31.679
I think like a good example you gave there, you may maybe I I am comfortable with AI chatbots.
00:34:31.760 --> 00:34:43.840
I want to start with that, but also if it gets complicated, or if this is a you know uh really important topic or you know, there's risk involved, i.e., fraud in my account, whatever it might be, I want to then talk to a human.
00:34:44.079 --> 00:34:50.719
So I think that's Stephen is where we're what we also see is a new opportunity for folks in how they work with AIs.
00:34:50.880 --> 00:34:52.239
Do you would you agree?
00:34:52.639 --> 00:35:02.719
I love the idea of off-ramps because I think there's this idea that once you're on the AI highway, you're on the AI highway, whether the consumer wants it or not.
00:35:02.800 --> 00:35:12.719
And I think this idea that I'm happy that or I prefer to step off or step into another uh lane, I think should be uh should be offered.
00:35:12.880 --> 00:35:15.760
Um again, I think winning brands will will figure that out.
00:35:15.920 --> 00:35:18.400
I think the other thing, you just mentioned transparency, right?
00:35:18.480 --> 00:35:28.559
And I and we're talking about processes, and um I find a lot of brands still don't really think deeply about transparency and maybe think about the present.
00:35:28.639 --> 00:35:30.480
So I'll give you I'll give you an example.
00:35:30.719 --> 00:35:32.320
Pricing is a great example.
00:35:32.559 --> 00:35:35.360
So why does something cost what it does?
00:35:35.519 --> 00:35:39.599
Now there's all kinds of detail behind that, right?
00:35:39.679 --> 00:35:47.360
Like everybody, Twilio, my company, anybody listening, you price your product a certain way for certain consumers for a reason.
00:35:47.679 --> 00:35:52.880
But 99% of the time, you the you do all you tell all you tell the consumer is the price.
00:35:53.039 --> 00:35:54.880
You don't tell them what's behind it.
00:35:55.280 --> 00:36:00.400
And I think that's an opportunity to start to uh build trust, coming to building trusts.
00:36:00.480 --> 00:36:08.880
And again, with AI, this become much more dynamic, but to build trust with consumers about exactly why is that why is that price there versus somewhere else?
00:36:09.199 --> 00:36:14.000
And giving people agency about uh maybe what they want to pay.
00:36:14.079 --> 00:36:16.320
I mean, I'll give you an example from years ago.
00:36:16.480 --> 00:36:25.199
I was working in the auto industry, this is like 25 years ago, and we had this big debate around um the around in car dealerships.
00:36:25.440 --> 00:36:27.280
And if you've ever bought a car, this happened yourself.
00:36:27.360 --> 00:36:33.440
If you walk in a dealership, you know, you negotiate, the car costs 50,000 or 70,000, and then you start to haggle.
00:36:33.519 --> 00:36:44.400
And the old um joke that, you know, I'll go talk to the sales guy says, I'll go talk to my boss and see if I can, and he doesn't talk to anybody, he just goes off and has a cigarette and comes back.
00:36:44.719 --> 00:36:48.400
But the problem is you don't know how much that guy is making.
00:36:48.559 --> 00:36:58.559
Like if we we did a survey, and the survey showed of consumers that they always assumed it was saying it's a$50,000 car, they assumed the sales guy was making like$10,000 on that sale.
00:36:58.719 --> 00:37:03.280
And the reality is the sales guy's making like$1,500, right, for solving that car.
00:37:03.360 --> 00:37:11.599
It's not making that much money, but because of this disparity in uh in assumptions, you they the consumer would like try to negotiate hard.
00:37:11.679 --> 00:37:17.760
And the reason the sales guy stops stops is I'm not gonna make any money on the sale if the price goes too low.
00:37:18.000 --> 00:37:26.159
And so I would argue that in that case, it's maybe it's better to tell the consumer, hey, I'm only making a little bit of money on this, you know.
00:37:26.480 --> 00:37:30.559
I'm I'm doing it, I'm we're on the same side here, but you know, I still need to pay my bills.
00:37:30.639 --> 00:37:31.840
I got and I got a family.
00:37:31.920 --> 00:37:34.639
And and they're trying to establish that human relationship.
00:37:34.719 --> 00:37:36.719
That's what good salespeople do, right?
00:37:36.800 --> 00:37:38.000
I it's human human.
00:37:38.239 --> 00:37:45.280
And so I don't I think with AI, you could you could supercharge those sorts of opportunities around true transparency.
00:37:45.360 --> 00:37:48.400
And maybe pricing is one place every brand could start.
00:37:48.719 --> 00:37:50.000
I I couldn't agree more.
00:37:50.079 --> 00:38:14.000
And again, um, you know, I you the word transparency is used a lot, and I think it does require double clicking into that and really exploring how we can apply that from pricing to how we manage your data through to um uh even how we would respond to it being uh breached in some way, shape, or form and being open with community.
00:38:14.239 --> 00:38:21.440
So I think that is increasingly gonna become more and more important in how brands ultimately that connection and ultimately trust.
00:38:21.599 --> 00:38:26.400
Um, and we sort of we've been moving towards a bit more focus on technology.
00:38:26.480 --> 00:38:33.119
I'm gonna use that as a segue because I knew we're gonna uh be able to fill an hour easily in terms of conversation here.
00:38:33.280 --> 00:38:49.599
I want to go to the next poll um because uh I'd like to get the audience back in here and really get their view on what is your biggest trust or challenge, sorry, biggest challenge when it comes to using technology to balance privacy and personalization.
00:38:49.920 --> 00:39:05.119
Um, we've got a few choices here, ensuring data security while providing personalized experiences, gaining customer trust through transparent data practices, managing compliance with evolving privacy regulations or something else entirely, let us know in the chat.
00:39:05.199 --> 00:39:12.559
Um, I've now figured out what my problem was with the poll, I think, before I was it was user error, it wasn't technology glitch.
00:39:12.719 --> 00:39:15.360
So um I can now see the poll.
00:39:15.599 --> 00:39:19.840
Um, so I'll give it give folks a little bit of a moment to fill that in.
00:39:19.920 --> 00:39:32.960
But if you think about this, both in terms of whether it's for you, Stephen, or or brands you've worked with in the past, what do you see as being the biggest challenge when it comes to technology's use in balancing privacy and personalization?
00:39:33.280 --> 00:39:35.119
I think it's what I referred to before.
00:39:35.199 --> 00:39:43.119
It's the idea that because a technology exists doesn't necessarily mean you should you should interpose it between you and the consumer.
00:39:43.440 --> 00:39:59.199
And you know, being truly focused on what's the what's the how do I build trust and and and confidence in that consumer that I'm going to treat them in the way that they want to be treated at that point in their journey.
00:39:59.519 --> 00:40:18.880
And I think there's so many technologies now, there's not just AI, there's you know different channels, different ways of uh, you know, different ways of using data, different ways you can build you can build data and technology into your product in a way that wasn't possible before, that you almost get dazzled by it as a as a as a brand.
00:40:19.119 --> 00:40:23.360
But I think you're gonna pull back from that dazzle to say, what am I trying to achieve here?
00:40:23.519 --> 00:40:25.119
What's what matters?
00:40:25.440 --> 00:40:42.000
And I think with with with that framing about what really matters and what comes from that human connection, that human need of the consumer, that's then where you will figure out how to and where to apply that technology, either in the back end or in the front end when you're interfacing with them.
00:40:42.239 --> 00:40:49.199
And I think again, too many times we just the technology almost takes over, it's like uh Frankenstein's monster.
00:40:49.280 --> 00:40:55.440
It just kind of takes over what you're doing without really thinking about the person at the other end of it.
00:40:55.599 --> 00:41:03.039
And I and I no, I see options you have in the poll reflects the yeah, it does actually, yeah.
00:41:03.119 --> 00:41:07.599
Uh, and uh, I think it looks like the top ones actually, there's two of them are pretty close.
00:41:07.679 --> 00:41:15.760
So ensuring data security while providing personalized experiences and gaining uh customer trust through transparent data practices are the two top ones there.
00:41:15.840 --> 00:41:17.440
But I I love what you were saying again.
00:41:17.599 --> 00:41:25.360
Um, sometimes can or two leave people surprised by this, but you know, I I love the quote from Steve Jobs.
00:41:25.440 --> 00:41:30.159
Um, but when he said he talked start with a customer experience and work back to the technology.
00:41:30.320 --> 00:41:40.960
Um, don't start with the technology, is always my advice um when working with customers, because um, you really need to really be clear and understanding what is the problem I'm trying to solve.
00:41:41.119 --> 00:41:48.639
Because nine times out of ten, I don't know about you, Stephen, but what I see is folks addressing symptoms and not prop the core pro root cause of the problem.
00:41:48.719 --> 00:41:58.239
Um, and that can lead you down a completely wrong path, especially when it comes to then selecting the right technology solutions that you are ultimately really need to get where you want to get to.
00:41:58.400 --> 00:42:02.400
And look, you know, one thing's for sure, you we need technology, right?
00:42:02.480 --> 00:42:03.360
There's no doubt about that.
00:42:03.440 --> 00:42:08.480
That's ultimately going to be the enabler of any sort of business transformation.
00:42:08.719 --> 00:42:13.119
But again, that's not the starting point, is what I'm hearing from you, because there's just so many choices.
00:42:13.199 --> 00:42:16.159
And I think folks get overwhelmed as a as a result of that.
00:42:16.400 --> 00:42:19.280
Well, Apple's Apple's a really great example.
00:42:19.440 --> 00:42:30.559
I mean, let's you know, tip our hat to the greatest, one of the greatest companies in the world, um, in terms of the technology they've built and the impact they've had and the tech and the industries they've disrupted.
00:42:30.639 --> 00:42:41.440
But if you go back to the to a technology choice here, which was grounded in consumer behavior and consumer need, and someone in the audience will remember this moment.
00:42:41.920 --> 00:42:50.880
And there was a moment when the we'll remember the Blackberry was the personal, you know, the personal device of dominance, right?
00:42:51.039 --> 00:42:57.039
And the Blackberry's big differentiator was just the clicky keyboard that we all remember.
00:42:57.280 --> 00:43:00.079
Um, and there was even a film about this, right?
00:43:00.159 --> 00:43:06.639
There's a there's a film about Blackberry, it's a funny film, but it's got a very profound kind of message in there.
00:43:06.719 --> 00:43:17.119
And one of the messages, several messages, but one of them is the idea that they were obsessed by the idea that no, it the keyboard, the keyboard with your thumbs matters.
00:43:17.199 --> 00:43:21.039
People want to feel the clicking, they want the tech, the tactile nature of it.
00:43:21.599 --> 00:43:32.480
The choice around technology that Jobs made was that no, you you need to not have any buttons that are permanent, you need to have a touch screen where you can put any button you want on that screen.
00:43:32.639 --> 00:43:40.320
Now, that was not an easy technology to build or to deploy, but it turns out Steve Jobs and Apple were absolutely right.
00:43:40.480 --> 00:43:44.800
The touch screen was where people wanted to go, not the not the keyboard.
00:43:45.039 --> 00:43:54.480
And yet all the evidence in the early in those days showed that you know people were obsessed and loved the tactile uh keyboard that that Blackberry had.
00:43:54.559 --> 00:43:59.519
But but Jobs had another insight that went a completely different way, and there was a big risk.
00:44:00.320 --> 00:44:13.599
So I think that, you know, getting deep in what customers really want and really starting to and see the, almost see like, I don't want to say the long distance future, but see the next evolution about where you can take consumers.
00:44:13.840 --> 00:44:20.480
Again, I think brands really need to think about not just what they want today, but where are they going to go tomorrow and then how can you take them there?
00:44:20.559 --> 00:44:22.639
And that's where the winning brands are going to be.
00:44:22.880 --> 00:44:23.920
Oh, I couldn't agree more.
00:44:24.000 --> 00:44:30.239
I mean, uh, I was working for a company at the time that was working with BlackBerry from a global partnership perspective.
00:44:30.320 --> 00:44:40.800
And I remember working with some pretty senior people at Blackberry, and this is around 2008, and um, the company I work for was a global enterprise software company.
00:44:40.960 --> 00:44:45.280
Um, and I said, guys, I'm seeing my execs starting to use the iPhone.
00:44:45.679 --> 00:44:47.760
I think there's a change afoot here.
00:44:47.920 --> 00:44:51.679
And they were so sure, certain that that wasn't happening.
00:44:51.760 --> 00:45:00.480
But once you see execs in a company switching devices or to a new technology, there's a good potential uh signifier that there's a change afoot.
00:45:00.559 --> 00:45:03.679
But there was a hubris, I think, that gets that existed.
00:45:03.760 --> 00:45:17.119
And I think that's the risk for all companies is that you've got to not get so focused on what you do, and to your point, have an over-the-horizon sort of uh uh focus in trying to anticipate what's coming next.
00:45:17.360 --> 00:45:28.079
Yeah, it's looking at your it's looking at your product, your service, and your experience for your consumer and saying, what's the clicking keyboard in our world that like it seems to be the right thing today?
00:45:28.239 --> 00:45:33.280
But the truth is we could use technology to make it a lot better or to transform it.
00:45:33.519 --> 00:45:35.280
And where are we at risk, too?
00:45:35.360 --> 00:45:45.039
That's some something about our product or service, our our experience for our consumers, it risks going down the route of black of a Blackberry clicking keyboard.
00:45:45.199 --> 00:46:04.559
Um, and I think a again, a lot of brands I think aren't aren't grappling with that because uh generative I is this great, I mean, the best, uh the great that we haven't had a technology in 30 years or longer that's been so potential for such transformation of custom consumer experience as generative AI.
00:46:04.719 --> 00:46:13.920
And yet I see brand after brand of brand, I think, doing kind of simple, dumb, you know, not the smartest things, um, and or doing nothing or not getting it.
00:46:14.000 --> 00:46:17.119
I mean, when I talked to the airline the other day, I'm like, why haven't they solved this problem?
00:46:17.599 --> 00:46:23.840
Literally, I mean it's that is you would you don't need generative AI to tell the next caller that what I called about.
00:46:24.000 --> 00:46:30.719
Um, and so it's so in some of that's just that stuff needs to just still be ironed out even before we get to generative AI.
00:46:30.960 --> 00:46:41.840
Well, maybe maybe jumping in there, what role do you see AI and machine learning playing when it comes to optimizing personalization and privacy and compliance?
00:46:42.000 --> 00:46:44.400
I mean, yeah, maybe we can explore that.
00:46:46.320 --> 00:46:47.039
Compliance.
00:46:47.840 --> 00:46:58.639
Yeah, this should be the compliance used to be the topic I hated the most, like the idea that you know, uh, you know, we need to uh you know, you have guardrails, safeguards, all this sort of stuff.
00:46:58.719 --> 00:47:07.599
And I when I worked at Facebook back in the day, look, I was in the I was in the commercial side of the organization, not in the technical side of the business.
00:47:07.920 --> 00:47:16.960
But the idea of putting guardrails on things and can you know and worrying about compliance was almost foreign to the the culture and the and the business.
00:47:17.199 --> 00:47:25.519
I think it's part of the reason that Facebook made uh did great things, but also made some mistakes along the way because we didn't have enough of those guardrails.
00:47:25.679 --> 00:47:34.960
Now, since I've come over to building AI uh for the human brain, the first products and applications we're building are into the healthcare system and into medical land.
00:47:35.119 --> 00:47:40.320
Well, there you don't understand compliance and safety and security.
00:47:40.480 --> 00:47:41.679
You will not survive.
00:47:42.239 --> 00:47:45.039
You need to deal with the TA or the FDA.
00:47:45.119 --> 00:47:46.880
Your product needs to be safe and effective.
00:47:46.960 --> 00:47:48.800
You you get audited all the time.
00:47:48.880 --> 00:47:52.079
If there's anything that goes wrong, it has to be reported.
00:47:52.159 --> 00:47:55.519
You know, you have to uh document everything, nothing gets swept under the rug.
00:47:55.760 --> 00:48:03.760
And so we've now built a much more uh I've we had a project in the early days of the company which was called up, which was called Project Comply.
00:48:03.920 --> 00:48:05.119
That was literally the name of it.
00:48:05.280 --> 00:48:18.400
And I fell in love with Project Comply because I realized the better we were at compliance, the better we would be able to make our products and services for our customers and the more successful our business would be.
00:48:18.719 --> 00:48:28.719
So I went for it's almost a joke inside the company about how I fell in love with Project Comply after I was, you know, that word would have repelled me before.
00:48:28.960 --> 00:48:43.039
And so in the age of AI around compliance and how do we think about it, you know, we've got uh we've got so many opportunities and challenges, fraud, risk, you know, there's a huge space now.
00:48:43.199 --> 00:48:54.880
Um how do we how do we get a unified view of our customer and how do we make sure that all that data is accurate and we're using it in an appropriate way with the right safeguards and transparency?
00:48:55.280 --> 00:49:05.360
Um, how do we incorporate AI into our existing platforms, customer experience platforms, CRM, you know, um customer SaaS platforms.
00:49:05.679 --> 00:49:25.280
So um, and what's the what's the right level of and the balance between constraining yourself and in our in our business we have to be quite constrained because we build for the world of healthcare, but also thinking about how can we where where's the white space?
00:49:25.440 --> 00:49:36.880
Where can we actually be less how can compliance not slow us down in terms of innovating, pushing the boundaries, building new things for customers, um, and moving fast.
00:49:37.119 --> 00:49:41.039
So that balance, I think AI's only made it more challenging.
00:49:41.199 --> 00:49:45.840
And I think it's going to be not just true for my company, but for every company in the world.
00:49:46.239 --> 00:49:48.800
I think I was just thinking, I love again, I love that.
00:49:48.960 --> 00:49:52.000
I think that constraint, though.
00:49:52.559 --> 00:49:56.079
So the comply piece, I love that journey of you you had there.
00:49:56.320 --> 00:50:05.360
Um again, the the the the objective of complying is ultimately end of the day to still deliver a great experience and product to the end customer, right?
00:50:05.440 --> 00:50:06.320
That's the intent there.
00:50:06.400 --> 00:50:18.960
So if that is at the center of what you're trying to do, but also the constraints that that created for you guys obviously then forces you to be more creative in thinking around how do you solve for that, I would imagine.
00:50:19.199 --> 00:50:20.480
Is that a fair statement?
00:50:20.559 --> 00:50:24.559
And that that those constraints can help you actually innovate.
00:50:24.800 --> 00:50:25.440
Yeah.
00:50:25.920 --> 00:50:34.239
So if if you look at great artists, I would when I started my career as a long, long time, I was a musician, I was a classical pianist and violinist.
00:50:34.320 --> 00:50:38.320
I didn't have the talent to go to where I wanted to go, so I left it behind.
00:50:38.559 --> 00:50:45.599
But the thing you learn about when you're uh particularly let's take music, for example, is um music is full of compliance, right?
00:50:45.679 --> 00:50:49.199
Which is, you know, you have to tune your instrument a certain way.
00:50:49.360 --> 00:50:55.280
There's certain notes that are part of the you know, the part of how you play, right?
00:50:55.599 --> 00:51:00.000
How different instruments play with each other all has to comply to the same rules.
00:51:00.159 --> 00:51:05.199
There's you know, there's tonal and there's melodic rules about how at least Western music is produced.
00:51:05.280 --> 00:51:07.039
Why do things like Indian music sound different?
00:51:07.199 --> 00:51:08.320
Because the rules are different.
00:51:08.559 --> 00:51:16.000
The tonal structures and the and the the melod, the melodic structures or the the the frameworks that they use are different.
00:51:16.079 --> 00:51:16.960
That sounds different.
00:51:17.039 --> 00:51:25.360
But Western music, you know, if you hear something that sounds dissonant or it's uh it's uh or it's out of tune, it's like, oh, this might hits my ear wrong.
00:51:25.679 --> 00:51:26.480
Your ears fine.
00:51:26.639 --> 00:51:31.440
It's just that you're used to a complied, a compliance framework around how music is produced.
00:51:31.599 --> 00:51:45.599
So being a former musician, what happens is with when you put constraints on people, constraints don't um they don't inhibit creativity, they they encourage creativity within those constraints.
00:51:45.760 --> 00:51:52.960
So, you know, why was there's been there's been hundreds and hundreds of classical music composers over the centuries, thousands.
00:51:53.280 --> 00:51:55.679
But why does Mozart stand above?
00:51:56.079 --> 00:52:02.719
Is it was it because he broke all the rules and used the different uh different instruments or used different uh tonal scales?
00:52:02.880 --> 00:52:07.599
No, no, he used the same, he was in the same rules inside the same box of compliance to everybody else.
00:52:07.760 --> 00:52:15.679
But what he did is he he would he was more creative within that those that box of compliance, and so it's not a constraint uh at all.
00:52:15.840 --> 00:52:21.280
Um, it's you you have to draw a box somewhere, and then within that box, you can be a genius.
00:52:21.519 --> 00:52:35.199
And so I tell our company that doesn't matter, we can be geniuses within this box, uh, and we have to be a genius within that box because without some compliant compliance and constraint, you don't have a business.
00:52:35.280 --> 00:52:43.519
You have a you're you have you're an anarchy, and you don't have something that's safe and effective in the in the world of what we build, brain-related technology.
00:52:44.000 --> 00:52:49.199
But I I also think that that's fully transferable, irrespective of your and uh your industry.
00:52:49.360 --> 00:53:01.599
That's why I wanted to double-click on that, because I feel what you just shared there for those that are listening, irrespective of the industry in, you know, don't see compliance and privacy and um you know as a restriction.
00:53:01.760 --> 00:53:03.840
See it as well, it is a restriction.
00:53:03.920 --> 00:53:12.880
There, there's there's it's it's it's gonna be a forcing mechanism for you to be more creative in in thinking through how you could solve for those specific needs.
00:53:13.039 --> 00:53:20.800
Because at the end of the day, it is about delivering your customer that ability to trust that you have their best interests at heart, right?
00:53:20.960 --> 00:53:23.440
I think that's that's sort of what I take away from that.
00:53:23.519 --> 00:53:25.920
So I I really love the fact that you you shared that.
00:53:26.000 --> 00:53:26.480
That was brilliant.
00:53:26.639 --> 00:53:28.639
I knew look, we're we're coming up on time.
00:53:28.800 --> 00:53:36.880
I've got a uh one final question for you, then I'm gonna throw to the to the audience for um, I think one final survey.
00:53:36.960 --> 00:53:38.000
Oh no, no, we don't.
00:53:38.079 --> 00:53:43.119
Um actually, I'll just wrap up with you on one final question and then we'll wrap up the session.
00:53:43.360 --> 00:53:57.599
What do you think um is the single most important thing that companies need to do differently um right now in striking the right balance between privacy and personalization?
00:53:57.760 --> 00:53:58.400
Yeah.
00:53:59.760 --> 00:54:16.559
So I think coming back to something I said earlier about giving choice across the spectrum, I think the ability for consumers to choose their level of personalization with your product or service is going to become the new expectation.
00:54:16.719 --> 00:54:18.719
I I it's up to me to choose.
00:54:18.960 --> 00:54:24.079
So many brands, many companies, there it's more of a one, it's a one size fits all.
00:54:24.159 --> 00:54:27.920
We will, you know, everybody gets the same type of personalization.
00:54:28.000 --> 00:54:35.119
So we're not we're not all getting the same message or the same experience anymore, but we're all getting the same le assumption about the level that we want.
00:54:35.280 --> 00:54:36.400
I think that's wrong.
00:54:36.559 --> 00:54:39.199
I think the age of AI, what's AI?
00:54:39.360 --> 00:54:41.679
AI is hyper-personalized everything.
00:54:41.840 --> 00:54:44.400
I mean, no more searching Google and getting blue links.
00:54:44.559 --> 00:54:50.480
No, no, the the the answer is hyper-personalized to your uh you know, to your your prompt engineering.
00:54:50.719 --> 00:54:52.880
By the way, is that that's a term that needs a rebrand.
00:54:52.960 --> 00:54:56.320
I think it's worse sounds painful, prompt engineering.
00:54:56.480 --> 00:55:01.519
But prompt engineering is just asking the right questions and asking a question that's specific to your needs.
00:55:01.760 --> 00:55:12.960
So that idea that you can give different levels of choice around privacy and personalization to every single customer and giving off ramps, that I think is the number one thing that brand should be thinking about today.
00:55:13.280 --> 00:55:13.760
Awesome.
00:55:13.840 --> 00:55:15.199
I I I couldn't agree more.
00:55:15.280 --> 00:55:17.920
I think it's a great insight to share with the audience.
00:55:18.159 --> 00:55:22.000
Um I I really want to thank you.
00:55:22.079 --> 00:55:40.559
Um, I'm gonna actually ask you, I didn't sort of set this up, so uh I would like to ask you what is a resource that you go to to stay abreast of the latest and greatest, or a thinker that really influences or is having an influence on you in how you navigate um, you know, today's business world.
00:55:40.960 --> 00:55:42.239
So that's good.
00:55:42.639 --> 00:55:46.320
You know, I'm sure each one of us has I spent a lot of time in AI.
00:55:46.960 --> 00:55:57.360
I try to figure out not just what are the big things going on, but also like what's happening at the core face of of consumer experience of how companies are running themselves.
00:55:57.519 --> 00:56:03.920
And so there is a um uh uh through LinkedIn and through social media, there's a there's something called the rundown.
00:56:04.079 --> 00:56:05.760
I think it's called the rundown of AI.
00:56:06.159 --> 00:56:10.239
And so the rundown is I'm sure there's other newsletters, but it's a really simple.
00:56:10.480 --> 00:56:12.159
I get it in my inbox every day.
00:56:12.320 --> 00:56:33.760
You can go to you can go online to find out socials, but the rundown is a really good summary of just like the what are the big things happening in AI and some folks on AI today, but also more importantly, like what are the two it's like spotlight on different tools, different apps, different edge and AI tools that are coming out, and you know, a little and discussions about you know pros and cons of them, what are different alternatives, etc.
00:56:34.159 --> 00:56:35.119
I cannot keep up.
00:56:35.280 --> 00:56:38.079
I was just went to uh Google's website the other day.
00:56:38.159 --> 00:56:42.000
I mean, they had like 321 different use cases for generative AI.
00:56:42.159 --> 00:56:44.480
Like that was literally the the title.
00:56:44.719 --> 00:56:49.199
And there's thousands of use cases for generative AI, but you can't even keep up with it all.
00:56:49.360 --> 00:56:51.760
So the rundown AI I find pretty useful.
00:56:51.840 --> 00:56:53.840
I think it has several million subscribers.
00:56:54.000 --> 00:56:55.119
That's a good one for me.
00:56:55.360 --> 00:56:58.719
You're uh the audience will probably have other ones they find uh useful as well.
00:56:58.800 --> 00:57:01.360
There's only so many hours in the day I can spend digging in.
00:57:01.440 --> 00:57:05.199
I've got to still run my business, but that's been a really useful one for me.
00:57:05.519 --> 00:57:06.000
Perfect.
00:57:06.079 --> 00:57:08.480
Look, I I've just shared the link with the team.
00:57:08.639 --> 00:57:10.480
Hopefully they can push it out to the audience.
00:57:10.719 --> 00:57:11.840
I'm gonna subscribe.
00:57:12.000 --> 00:57:14.800
That wasn't one uh that I was subscribed to.
00:57:14.880 --> 00:57:15.599
So definitely doing it.
00:57:15.760 --> 00:57:18.159
Look, I really want to thank you, Mighty, for taking the time out.
00:57:18.239 --> 00:57:36.480
Um, again, the goal with this series is to share insights that can hopefully help the audience uh go back into their offices tomorrow or today and start noodling on ways that they can drive the business forward in you know, meeting the challenges that sit before ahead of us all, right?
00:57:36.559 --> 00:57:37.840
We're all grappling with this.
00:57:37.920 --> 00:57:39.920
So really appreciate that.
00:00:04.719 --> 00:00:06.959
Hi then, it's Nicholas Kontopoulos.
00:00:07.040 --> 00:00:11.279
I'm the VP of Marketing for Twilio Asia Pacific Japan.
00:00:11.439 --> 00:00:13.519
And welcome back to Decoding Trust.
00:00:13.679 --> 00:00:25.600
In this series, we're going to explore what is it, what it takes to build and maintain trust in today's business world, from company culture to customer experience, security, and beyond.
00:00:25.839 --> 00:00:34.079
In our last episode, we talked about why trust is essential for businesses and for the people inside and outside of the organizations.
00:00:34.560 --> 00:00:40.079
Today, we're diving into one of the most complex and pressing challenges businesses face.
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That is balancing privacy, transparency, and personalization.
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We as all, we're all consumers and we all want personalized experiences.
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I don't know about you, but I love when I get personalized experiences.
00:00:53.759 --> 00:00:54.719
And we know this.
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Businesses know this.
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But it's a real challenge for a lot of businesses.
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Like last year, 76% of businesses said that personalizing customer engagement was a high or critical priority for their businesses.
00:01:07.280 --> 00:01:12.159
This is taken from our Twilio State of Customer Engagement report for last year.
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So I think you should be able to access that in the resource section.
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So we're on the right track, but it isn't easy.
00:01:18.400 --> 00:01:22.640
While the majority of customers want personalization, guess what?
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They're also demanding privacy and transparency.
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This is the balance that businesses are struggling to get right.
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Again, if I refer to our state of customer engagement report, 40% of businesses called finding the balance between security and customer experience is one of their most pressing challenges.
00:01:42.239 --> 00:01:45.359
So today we're going to explore this delicate balance.
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We'll explore how brands can personalize experiences without crossing privacy boundaries.
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And we'll talk about the role technology plays in ensuring transparency while keeping data secure.
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So I'm really excited today.
00:01:59.359 --> 00:02:01.599
We've got Stefan Sheela here with me today.
00:02:01.840 --> 00:02:06.319
Stefan is uh Stephen, sorry, is an influential voice in technology and AI.
00:02:06.480 --> 00:02:15.520
He was the former CEO of Facebook, ANZ, and is now the CEO of OmniNescent, a groundbreaking AI startup that has won numerous awards.
00:02:15.680 --> 00:02:23.520
He advises global brands like Google and Qantas and is a regular media commentator on the Wall Street Journal, Forbes, and ABC.
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So, Steven, thanks for being here, mate.
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I'd love uh to have you just also introduce yourself to the audience and maybe uh share a little bit more about your fascinating company that you've launched um and the work you're doing, because it really is true, truly groundbreaking.
00:02:37.280 --> 00:02:38.560
Yeah, great to be here, Nick.
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Thanks for to Twilio for asking me to be here.
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Thanks to you for hosting it.
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I I'm really lucky in my journey, Nick, as you mentioned before, I was at Facebook for a long time.
00:02:48.080 --> 00:02:51.439
Back when it was Facebook, now it's uh called something else.
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Uh but since I left Facebook, one of the things I was um fascinated by was how do how do we use AI, not just to you know serve you with more ads or optimize your feed, but how do we use it to really shift humanity forward?
00:03:03.840 --> 00:03:06.159
Uh use AI for the benefit of humankind.
00:03:06.319 --> 00:03:10.560
And I started to get fascinated by the human brain, which is the most complex thing in the universe.
00:03:10.719 --> 00:03:17.680
So everything open AI is building today is dwarfed by what your the complexity of what's between your two ears.
00:03:17.919 --> 00:03:25.360
And luckily, with the rise of AI and computing power and the algorithm we have today, we can now start to make sense of the brain in a way it was never possible before.
00:03:25.439 --> 00:03:32.000
So the company I built over the past few years with some other amazing people is the world leader in using AI to decode the brain.
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We build tools for mapping the human brain.
00:03:34.960 --> 00:03:37.680
Almost think of it a Google maps for the human brain.
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And the so what of all that is it's it's a real breakthrough for things like mental illness and neurodegenerative diagnosis, treatment, treatment, targeting.
00:03:46.159 --> 00:03:54.080
And you know, you think about when you you take a, you, you get a say you get depressed today, which many of us uh tragically do, you know, you go and you get a you get a pill.
00:03:54.159 --> 00:03:56.319
Well, it's the same pill that everybody else gets.
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Um, but that pill, of course, 40% of the time it doesn't work.
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Why?
00:03:59.919 --> 00:04:04.560
Because it's not targeted at your specific problem because doctors say don't understand the complexity of the brain.
00:04:04.719 --> 00:04:09.680
So we're building tools into that space today using AI, and it's you know, it's truly revolutionary technology.
00:04:09.759 --> 00:04:12.719
So um I'm very lucky to build that with the the people I do today.
00:04:13.120 --> 00:04:16.879
I mean, it's a bold vision and and ultimately really groundbreaking and exciting.
00:04:16.959 --> 00:04:25.120
And again, you know, that what you just described there, the the uh ability to tailor and target at an individual level, I think is uh amazing.
00:04:25.199 --> 00:04:27.920
Um, that's the same theme.
00:04:28.240 --> 00:04:42.879
Yeah, I would think it ties nicely into the theme of that, uh of what we're exploring, but obviously it a in a in a really uh beneficial way in from a ultimately what will benefit a lot of humans um in terms of their ability to battle some of the struggles they've got.
00:04:43.040 --> 00:04:44.560
Yeah, so that's amazing, Mighty.
00:04:44.639 --> 00:04:45.759
So thanks for that intro.
00:04:45.839 --> 00:04:48.399
And we're gonna kick start off with a poll.
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I like making my audiences work.
00:04:50.639 --> 00:04:57.040
So um I really would love to bring the audience into the poll, which will get pushed in front of you right now.
00:04:57.120 --> 00:05:04.079
And and what I want to hear is everyone's um ultimately, you know, is experiencing challenges on this topic in one way, shape, or form.
00:05:04.240 --> 00:05:06.800
So what do you feel is the biggest challenge?
00:05:06.879 --> 00:05:08.399
Um, this is a question to the audience.
00:05:08.560 --> 00:05:13.439
What do you feel is the biggest challenge in balancing privacy, transparency, and personalization?
00:05:13.600 --> 00:05:15.199
And you've got several choices here.
00:05:15.279 --> 00:05:41.199
We've got earning customer trust while collecting and using data, you know, providing personalized experiences without overstepping uh privacy boundaries, which is always tough because everyone has different boundaries, communicating data practices in a clear and transparent way, keeping up with changing privacy regulations, which also is a real challenge for uh marketing leaders that operate in a region like uh Amir or uh in particular an APJ, where we've got lots of different regulations.
00:05:41.279 --> 00:05:44.399
And there's another option, so feel free to put some free text in there.
00:05:44.480 --> 00:05:55.279
So if you can start uh, you know, marking up uh what option you feel is the biggest challenge, and uh we can then get a sense or pulse check of where everyone's at in that respect.
00:05:55.439 --> 00:05:59.759
So, Marco, hopefully you've got the uh poll up and running.
00:06:01.040 --> 00:06:03.040
Not sure if that's been pushed.
00:06:05.199 --> 00:06:07.680
Uh while it's going while it's going on, Nick.
00:06:07.759 --> 00:06:15.360
I uh I noticed there wasn't an all of the all of the above option, which I think that would be my choice if I had one.
00:06:15.439 --> 00:06:16.399
It will be all of the above.
00:06:16.560 --> 00:06:22.720
Everything you mentioned there um it it all comes together as a huge challenge to figure out where's where's the balance.
00:06:22.800 --> 00:06:25.360
Um, and I think that's what we're gonna explore more today.
00:06:25.519 --> 00:06:35.439
And I think part of that balance is just born out of the fact that what you privacy used to be uh assumed, you know, you knew that nobody, nobody, the butcher didn't know anything about you until you told the butcher about yourself.
00:06:35.519 --> 00:06:39.680
You know, Toyo didn't know who you were until you walked in the dealership and asked that asked to buy a car.
00:06:39.920 --> 00:06:41.279
We know that world is different now.
00:06:41.360 --> 00:06:44.079
So you want personalization, but you also want privacy.
00:06:44.240 --> 00:06:47.600
And I even think consumers don't know where they they're drawing the line themselves.
00:06:47.920 --> 00:06:48.319
100%.
00:06:48.720 --> 00:06:49.680
And I agree with you.
00:06:49.759 --> 00:06:56.800
Uh it is this definitely should have been all of the above because that is uh, if I think about it just from my world, it I'm considering all those.
00:06:57.040 --> 00:06:59.120
I can't actually see the actual results.
00:06:59.360 --> 00:07:01.519
I'm not sure that there's a glitch going on here.
00:07:01.600 --> 00:07:06.000
So, Marco in the chat, I don't know if you can give me an indication of which one was a top choice.
00:07:06.240 --> 00:07:08.480
Otherwise, what we'll we'll do is we'll move on.
00:07:08.720 --> 00:07:10.800
Um, you know, maybe setting the scene.
00:07:10.959 --> 00:07:11.199
All right.
00:07:11.279 --> 00:07:12.319
Well, let's set the scene.
00:07:12.480 --> 00:07:19.360
Amazon was fined$25 million back in 23 for retaining children's voice data captured through Alexa devices.
00:07:19.519 --> 00:07:23.360
Um, I remember my kids talking to these devices quite excitedly.
00:07:23.519 --> 00:07:31.759
So, why do you think it's a challenge it's so challenging uh for businesses to strike this right balance between privacy and personalization, Steven?
00:07:32.879 --> 00:07:41.839
Well, let me let me go back a little bit because I think it's I think for all of us in business, it's it's good to know where we are sitting and the kind of the evolution of trust and privacy.
00:07:42.000 --> 00:07:44.240
And I've I've read a lot about this.
00:07:44.399 --> 00:07:49.040
I build companies in this space, I've talked to leaders, uh, but so this is based on my own experience.
00:07:49.120 --> 00:08:09.199
I'm not quoting for a from a poll or a survey, but in and I I what I think has happened over the past 20, 30 years is we went from a world where privacy was essentially assumed, in the sense as the example I gave before, Toyota didn't know anything about you, and I'm just using them as an example, until you walked into the dealership and you said you want to buy a car.
00:08:09.279 --> 00:08:10.959
And that's when the relationship started.
00:08:11.199 --> 00:08:13.920
Now, you would have triggered the relationship, most likely.
00:08:14.079 --> 00:08:16.079
You would have you've given them the information.
00:08:16.240 --> 00:08:23.680
Here's my name, phone number, kind of car I want, how many kids I have, whatever it is that was informing your purchase, you would have shared at that point.
00:08:23.920 --> 00:08:30.639
Um, fast forward to today, and I asked this question what do others know about you and what are they doing with it?
00:08:30.800 --> 00:08:35.919
And the truth is, not even Mark Zuckerberg or Elon Musk or Jeff Bezos know the answer to that question.
00:08:36.080 --> 00:08:37.200
We none of us do.
00:08:37.440 --> 00:08:54.480
So I think there's this, there's been this move, and it has happened because of largely because of the rise of the internet and the rise of data as the the key asset that all of us as consumers didn't know was so valuable, but companies like Google and Facebook and others did realize it was valuable and started to hoover it up.
00:08:54.639 --> 00:09:14.240
And so we have these data profiles that have been assembled by all the companies trying to reach us, and that can be good because it can create more personalization, but I think it can also be um invasive, it can be creepy, it can be um, it can go wrong in a way that we don't have full control of or transparency of what's going on.
00:09:14.399 --> 00:09:21.039
And um, there's been obviously there's been changes in regulation, GDPR, other privacy rules the past uh you know 10, 15 years.
00:09:21.200 --> 00:09:33.279
But still, I actually before um we got on this call, I was uh I start to ponder things and I I actually thought to myself, you know, how how many words are in like Meta's privacy statement, right?
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How many words are in Google's?
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How many words in Telstras or CBA's or you know, you know, or or Grab or you know, you and aim your company.
00:09:40.799 --> 00:09:42.080
Well, it's thousands.
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I mean, just to give you a sense, Meta has 9,000 words, you know, uh, Google has 8,000 words, you know, even the banks in Australia six, 7,000 words in the privacy statements.
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Now, how long would it take you to read that and absorb it?
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And it probably would take you, uh and I've tried, takes you hours, right?
00:09:57.919 --> 00:10:02.480
There's all kinds of deles and nomenclature understand, and click here to read another document.
00:10:02.720 --> 00:10:05.519
And you know, here's what does GDPR do and not do?
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Does it apply to you?
00:10:06.639 --> 00:10:08.080
And all these definitions.
00:10:08.240 --> 00:10:12.879
So the reality is, now which is the irony, is none of us understand that.
00:10:13.039 --> 00:10:22.480
Yet in the age of regenerative AI, you know, I can type anything I want into one of these, uh, you know, one of these Gen AI chatbots, and I get, you know, here's a PhD on any topic in the world.
00:10:22.559 --> 00:10:27.039
Yet I'm still like left to read your 9,000 word privacy statement.
00:10:27.200 --> 00:10:31.519
So I think brands are not putting themselves in a in a position to win.
00:10:31.759 --> 00:10:40.320
It's simply they're they've got a very clunky old way of understanding what are the rules and and then how do I move as a consumer?
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Where do I move the the the cursor along, you know, from super private to more open in in a sort of an exchange with you?
00:10:48.399 --> 00:10:51.440
So that's uh just some thoughts about where the moment we're in.
00:10:51.519 --> 00:10:59.919
And I think you know, I think brands are still still kind of living in the old world that we all, many of us grew up in, but the new world is very, very different.
00:11:00.159 --> 00:11:01.440
Yeah, I couldn't agree more.
00:11:01.519 --> 00:11:03.039
And it's moving at pace, right?
00:11:03.120 --> 00:11:04.240
Like the the speed.
00:11:04.320 --> 00:11:14.960
I mean, I'm um Gary Hamilton, I'm a big fan of, and I remember him saying a long time ago, and it it couldn't be more true today, is change is changing in itself in terms of the pace and rate of change.
00:11:15.039 --> 00:11:36.240
And that's putting a huge pressure, like you said, on an architecture that powers a lot of the businesses that is quite data, built really for the 19th and 20th century, if you really think about where a lot of the models that are still being used by businesses is really inhibiting their ability to keep pace with um uh their consumer base that and and employees that are serving them, right?
00:11:36.320 --> 00:11:52.000
I think that's another thing we often talk about customers, but it's also where is the the role of the employee in this picture also is how do we ensure that when they're having those conversations with customers, they're also being uh given the capabilities to explain what the privacy statement is, for example.
00:11:52.159 --> 00:11:56.480
Like you said, I would hate to try to imagine the difficulty I'd have doing that.
00:11:56.720 --> 00:12:03.360
Maybe um that's a good way to sort of if I because I like thinking in terms of people, process, and technology, uh Stephen.
00:12:03.519 --> 00:12:09.279
Um, and we as a technologist, people expect me to always go to technology straight away.
00:12:09.360 --> 00:12:20.639
But I really feel, and I'd love to get your thoughts on this, the importance of really exploring the impact of, you know, if we think about business transformation, we need to always start with the people side of the equation.
00:12:20.720 --> 00:12:26.399
And that's ultimately the customers we're serving, the employees that are going to serve them, and even the partners that are involved in that process.
00:12:26.639 --> 00:12:38.879
So with that in mind, I mean, how do you see businesses ultimately successfully uh successfully empowering their employees to champion the importance of balancing privacy and transparency and personalization?
00:12:39.039 --> 00:12:41.039
I mean, you know, the privacy policy.
00:12:41.120 --> 00:12:42.399
Again, someone wrote that, right?
00:12:42.720 --> 00:12:50.240
So, you know, how do we how do we set our employees up for success in navigating this new world?
00:12:51.360 --> 00:12:59.279
Yeah, I it's interesting because I I've been building a company in AI in and very sensitive data the past few years.
00:12:59.360 --> 00:13:02.399
The business I built in brain AI called it's called omniscient.
00:13:02.720 --> 00:13:06.320
And we're looking into the heart of what it is to be human.
00:13:06.480 --> 00:13:14.879
I mean, we're decoding people's brains, we're seeing things that or could see things that are no more personal than any data you have anywhere else.
00:13:15.279 --> 00:13:17.120
It's it's essentially your your soul.
00:13:17.279 --> 00:13:18.879
We can start to almost decode.
00:13:19.279 --> 00:13:25.279
And um we have our very we think we're very thoughtful and ethical about how we build in that world.
00:13:25.440 --> 00:13:35.039
And we tried to build the company from uh the first principles have been around ethics and and giving people agency over their data.
00:13:35.279 --> 00:13:42.799
Now, um partly this is true for us because my um one of my co-founders is a is a medical doctor.
00:13:42.879 --> 00:13:46.559
We build into the medical system today, the healthcare system, and there are a lot of controls there.
00:13:46.639 --> 00:13:53.200
You know, you're in most countries in the world, there's there's no data that's more protected than medical and healthcare data in every country in the world.
00:13:53.279 --> 00:13:58.960
So we don't see, for example, we never, even though I'm building a map of your brain, I don't know, I don't see personal personal data view.
00:13:59.039 --> 00:14:00.320
Everything we have is anonymized.
00:14:00.480 --> 00:14:08.960
We're not allowed to see P what's called PHI personal health, uh personal health information that we actually doesn't sit on our service, doesn't come into our cloud.
00:14:09.200 --> 00:14:15.840
But still, one thing I worry about is giving people agency over their data and their healthcare data.
00:14:16.000 --> 00:14:33.360
And there's a and data not just about what you did on the internet or you know, your social security number or your, you know, your any other identifying data, but data that's related to your biology, your genomics, your other omics, your connectomics, which is your connections, your brain.
00:14:33.519 --> 00:14:38.399
And then having agency over that data in a way that um you can make sensible decisions in your life.
00:14:38.559 --> 00:14:42.240
Now, the great thing about generative AI is it it's what is it?
00:14:42.320 --> 00:14:44.559
It's a copilot, it's an agent, an assistant.
00:14:44.720 --> 00:15:01.279
So I see a future, I'm not building this company, but I'd like I want to build it where there's agents that can help me monetize or control or control access to my data in a way that doesn't force me to read every 9,000 page or 9,000 words.
00:15:01.360 --> 00:15:04.000
So it seems like 9,000 page privacy statement, right?
00:15:04.080 --> 00:15:05.679
Of all the apps and tools that I use.
00:15:05.759 --> 00:15:21.200
Now, coming back to empowering employees, as you said, what we've tried to do is build a culture of transparency, disclosure, um, building with privacy by design in how we build everything that we do.
00:15:21.440 --> 00:15:24.080
And I think there's again, there's legacy companies.
00:15:24.159 --> 00:15:27.840
We we started five years ago, so we've been born in the age of AI.
00:15:28.000 --> 00:15:35.600
But companies that have been born, you know, decades ago or 100 years ago, you have legacy systems, legacy processes, legacy cultural norms.
00:15:35.919 --> 00:15:45.519
I really think you need to revisit and really work hard on privacy by design, which may run completely counter to how you do things today.
00:15:45.600 --> 00:15:57.679
And there's a lot of hard choices, I think, that need to be made inside organizations about, you know, what is truly right for the customer or for the ethical decisions you want to make as a business versus what's right for the bottom line.
00:15:57.759 --> 00:16:07.039
Those are not easy decisions, but I think having an honest discussion and debate with your organization and making sure people understand, you know, this is where we've landed as an organization.
00:16:07.200 --> 00:16:10.639
And these are the trade-offs that we understand we're making by landing there.
00:16:10.799 --> 00:16:16.000
So I find many um many businesses don't have that discussion with their employees.
00:16:16.159 --> 00:16:20.960
We we haven't really had that in many, many um, particularly legacy businesses.
00:16:21.120 --> 00:16:26.559
And I think that's really important, not just discussion to have, but we, you know, what's the new landing place that we need to get to?
00:16:26.799 --> 00:16:29.279
So that's sort of my my macro view.
00:16:29.360 --> 00:16:34.720
And I've got a lot of uh passion about it because of the company I've just been building the past few years.
00:16:35.039 --> 00:16:38.879
Well, I mean, yeah, it couldn't come from uh a better person.
00:16:39.039 --> 00:16:43.440
Obviously, you're living and breathing this now as an owner and builder of a business.
00:16:43.679 --> 00:16:54.480
I I yeah, I often say to folks, you is your company even AI ready before you even embark on unlocking this next generation of AI?
00:16:54.559 --> 00:16:58.320
And that's also an important distinction to make because I think AI has been around for a while, right?
00:16:58.399 --> 00:16:59.440
Like predictive AI.
00:16:59.519 --> 00:17:04.319
I mean, actually, AI as a term was coined back in 1953, machine learning three years later.
00:17:04.400 --> 00:17:07.039
So these aren't new concepts, they've been around for a while.
00:17:07.279 --> 00:17:23.359
But I think what we've seen is the convergence of sort of, you know, um, you know, the different technologies or capabilities coming together in recent times, which has obviously thrust this topic back into the spotlight in a in a way that is driving transformation.
00:17:23.440 --> 00:17:35.359
So therefore, we do need to think about, to your point, how do we prepare the organization and and and ensure that we're ultimately moving in the right direction and understanding what the roles and responsibilities are.
00:17:35.519 --> 00:17:36.640
Is that a fair statement?
00:17:36.799 --> 00:17:49.839
Yeah, yeah, I think that's a great what's happened the last few years, you're right, AI has been around a long time, but what has changed in the past couple years is the rise of generative AI on LLMs, which really we didn't have until three years ago.
00:17:50.079 --> 00:18:05.440
And now with the rise of that, what's it meant it's AI is much more accessible, much more usable, the user interface and the the natural language and human interface, the multimodal way human humans work, which is by vision, by by by sound, by by language.
00:18:05.680 --> 00:18:07.279
AI is now conversing in the same way.
00:18:07.359 --> 00:18:10.960
You don't to be a coder, you don't need to learn coding no learner coding language anymore.
00:18:11.119 --> 00:18:13.680
You can just you can just speak whatever language you speak.
00:18:13.839 --> 00:18:15.200
That's a huge change, right?
00:18:15.279 --> 00:18:16.720
That didn't exist before.
00:18:16.880 --> 00:18:23.599
And yet organizations are kind of as they need to be, they need to leap and get on to the AI revolution quickly.
00:18:23.680 --> 00:18:27.680
But the point you make, you need to be, you need to be, your culture needs to be AI ready.
00:18:27.759 --> 00:18:33.839
And I think I think there's a lot of organizations that are making mistakes in playing ahead of their culture.
00:18:34.160 --> 00:18:55.440
And you may not see the damage today, but the damage may start to come out in the next couple of years as we see wrong decisions being made, AI being applied in ways it shouldn't be, um disruption or destruction of customer trust and value when um you're trying to you're trying to the opposite, you're trying to make better experiences and you wind up making it worse.
00:18:55.759 --> 00:19:12.000
So um, and the re the reason I think we get there is and this is why I with this assumption I see a lot in a lot of business leaders that you know we know what's right for even even though you talk about customer centricity, there's still this assumption that, well, we know what's right for customers.
00:19:12.079 --> 00:19:17.759
They want more technology, they want more AI, they want more um options, they want more.
00:19:18.000 --> 00:19:19.680
And I don't think that's always true.
00:19:19.839 --> 00:19:24.880
I don't think that customers always want more to more technology, more AI, or even more options.
00:19:25.119 --> 00:19:31.359
I think they would just want to get to what matters quickly and they want to have some control over the nature of the relationship.
00:19:31.440 --> 00:19:38.480
Just like back in the old days, you know, when you when you walked into the Toyota dealership, it's what you told that dealer is what you disclosed.
00:19:38.640 --> 00:19:39.920
You were in control of it.
00:19:40.079 --> 00:19:43.920
Rather than, you know, you you shook his hand and he said, Oh, good to meet you.
00:19:44.079 --> 00:19:48.240
I'll tell you all about your needs as a as a car buyer because I know you're better than yourself.
00:19:48.400 --> 00:19:55.839
That might say sound exciting um as a personalization experience, but I think in terms of a privacy experience, it's it's not very exciting at all.
00:19:55.920 --> 00:19:57.839
It's a little, it's it's it's intrusive.
00:19:58.000 --> 00:20:06.160
So that balance, I think we're not with AI, we we are don't have cultures that are built to really make the right choices on that balance today.
00:20:06.480 --> 00:20:08.240
No, I I I couldn't agree more.
00:20:08.319 --> 00:20:26.319
And actually, I think it's um a nice little quick segue into where I want to double-click next um is uh really exploring this uh notion of the role of AI and and how we'll ultimately be collecting data and consent that enables that personalization.
00:20:26.400 --> 00:20:32.400
I I thought the Toyota example is a good example there, like in terms of where we've come from and where we're where where we are now.
00:20:32.720 --> 00:20:34.240
Um, how do you yeah?
00:20:34.319 --> 00:20:43.759
So, what do you see the role of AI being when it comes to collecting data and and you know playing a role in the consent uh that process that enables that personalization?
00:20:44.240 --> 00:20:47.680
I think there's an opportunity, a huge opportunity for brands.
00:20:47.839 --> 00:20:50.240
Um, and I've I've spoken about this before.
00:20:50.400 --> 00:20:56.240
I I think we've entered an age of permission-based marketing or consent-based marketing.
00:20:56.480 --> 00:21:05.359
And by that I mean getting permission and consent from consumers to go deeper into data collection, personalization, use of AI.
00:21:05.519 --> 00:21:10.319
I think that's what winning brands are going to do, rather than assuming there's a default setting for everybody.
00:21:10.400 --> 00:21:13.680
I think we've got an opportunity to say, no, where do you want your setting to be?
00:21:13.920 --> 00:21:20.000
And I just as an aside, I think one of those settings should be I want no AI in my product or service with you.
00:21:20.079 --> 00:21:24.000
I'm I'm I'm happy to go back to the the the analog way.
00:21:24.079 --> 00:21:27.519
You know, maybe I want to live an AI-free uh world.
00:21:27.759 --> 00:21:39.759
And and I almost think, I mean, I don't I'm not a big family regulation, but I almost think in some ways you know the government should encourage um you know many services and brands that they have to provide an AI-free alternative.
00:21:39.920 --> 00:21:45.279
Now I'm I'm big on AI, but I also believe that I think an AI free alternative should be available.
00:21:45.359 --> 00:21:52.319
So if you want to deal with your bank in a way that involves no AI, you should have the right to do that, or your telco or your or your social media provider, whoever.
00:21:52.480 --> 00:21:58.799
So I and it's just uh uh an aside, if I if you want to live an AI free life, I think you should have the right to do that.
00:21:59.039 --> 00:22:07.359
Um But coming back to data collection and AI, so uh I mean I said that I said before, what do people know about me and what are they doing with it?
00:22:07.519 --> 00:22:10.480
Well, that was hard enough before Generative AI came along.
00:22:10.640 --> 00:22:13.839
Now I would argue it's it's it's impossible.
00:22:14.720 --> 00:22:19.200
It truly is impossible to know what does uh generative AI know.
00:22:19.279 --> 00:22:28.079
What even even the you know the architects, the you know, even open AI doesn't know how open how ChatGPT is making its decisions or how it's uh processing things.
00:22:28.319 --> 00:22:31.359
And so we're living with black boxes all around us.
00:22:31.519 --> 00:22:43.279
I think the thing that's going to change though is one thing the opportunity, one is I said allowing consumers to s to to choose their setting in terms of how how AI fied they want their experience with you to be.
00:22:43.359 --> 00:22:51.200
I think that's uh that's an important way to, and that's and includes the data collection that takes place and or the data processing as well that takes place.
00:22:51.519 --> 00:22:59.839
But I think the second thing is to uh to allow consumers to uh I'm sorry, let me step back, not allow consumers.
00:22:59.920 --> 00:23:09.119
What's going to change is this, and it's changing already, is it's not going to be a my AI, you know, company X's AI talking to the consumer or approaching the consumer.
00:23:09.200 --> 00:23:12.400
It's going to be company X's AI talking to my AI.
00:23:12.559 --> 00:23:12.880
All right.
00:23:13.039 --> 00:23:16.640
So, and being another step removed from that consumer.
00:23:16.880 --> 00:23:19.039
Now, think about that challenge, right?
00:23:19.200 --> 00:23:29.759
So if I want to, if if if I'm a company and and I'm going to get to you, Nick, by to give you service or sell your product or show you an ad, but you've got your AI and you're talking to my AI.
00:23:29.920 --> 00:23:33.599
Well, now I got to get through your AI to get to your wallet somehow.
00:23:33.839 --> 00:23:39.599
And so optimizing this world is is happening, it's it's it's arrived.
00:23:39.759 --> 00:23:50.000
So optimizing for how what's the data exchange, what's the value exchange, what's the consent exchange in that interface, I think is going to be where again we're winning brands win.
00:23:50.640 --> 00:23:53.119
Ah, I couldn't agree more so much there.
00:23:53.279 --> 00:23:59.680
Um, yeah, definitely um the battle is going to be won or lost in that space.
00:23:59.759 --> 00:24:13.680
And I think it's also like we've obviously for the longest time marketers lived with the you know, relied on third-party data as a fuel to power their ability to personalize at scale.
00:24:13.839 --> 00:24:27.359
And, you know, I think where we've quickly moving to, and we'll even this is going to present some of the challenges you spoke about with you know the AIs working with one another, is the importance of first party and even zero-party data.
00:24:27.440 --> 00:24:39.039
And we define the latter as being the data that you know you willingly share with a brand, knowingly, you know, rich data that tells that brand who I am, what what I like, what I'm looking for, etc.
00:24:39.359 --> 00:24:52.880
And you know, obviously first party data being the data that you know I share, maybe not consciously or subconsciously and not aware of what what it's how it's being used, but those two data sets coming together and being used in a way that can really individualize that engagement.
00:24:53.200 --> 00:24:58.240
But there has to be a catalyst in order for me to want to share that data.
00:24:58.319 --> 00:25:00.480
And I think trust is a big part of that, right?
00:25:00.720 --> 00:25:04.480
So, you know, that trust anchors ultimately everything.
00:25:04.640 --> 00:25:10.400
And, you know, we need to create a, I guess as a business, you need to be creating a value proposition.
00:25:10.640 --> 00:25:18.640
If we go back to your your own endeavor in this space, obviously that is highly personal data that folks are sharing, right?
00:25:18.720 --> 00:25:27.119
So you've got to look after that data, cherish that data, and create a use the data in a way that actually creates a value back to the the giver of that data, right?
00:25:27.200 --> 00:25:28.400
Is that a fair statement?
00:25:28.640 --> 00:25:29.200
Yeah.
00:25:30.960 --> 00:25:31.440
Absolutely.
00:25:32.319 --> 00:25:40.960
I mean, there's a um we have a sort of truism on our business around, you know, we we hold nothing that's not necessary, right?
00:25:41.039 --> 00:25:44.720
That so anything that's not necessary, we we do not hold.
00:25:44.960 --> 00:25:52.160
And and secondly, giving as much sovereign control to the owner of that data as we possibly can.
00:25:52.319 --> 00:26:03.359
In fact, trying to look for ways to give more control to them and more agency to them, I think is the long term is going to benefit not just uh our business, but I think will benefit the the world.
00:26:03.440 --> 00:26:06.319
And we're trying to build tools that benefit humanity.
00:26:06.480 --> 00:26:16.160
And I think without giving humans agency over all their data and true transparency and control, the world is not going to be a better place.
00:26:16.319 --> 00:26:18.880
So that's like a meta thing that I believe in.
00:26:19.039 --> 00:26:21.599
Meta meta meaning big, not necessarily Facebook.
00:26:21.839 --> 00:26:24.400
Um and I know not all companies necessarily agree with that.
00:26:24.559 --> 00:26:34.559
And so, and perhaps all regulators don't agree with that, but that's the that's the philosophy that we have with our business because we're dealing with the most important data set in the world, which is which is your brain.
00:26:34.640 --> 00:26:37.359
There's nothing more critical and personal than that.
00:26:38.319 --> 00:27:00.240
And when it comes to looking after that data, um, you know, either in your sort of past roles or even in the current um capacities, what what processes do you recommend companies implement to prevent accident accidental exposure of personal um identifiable information during that collection aggregation process?
00:27:00.400 --> 00:27:05.359
Is there any sort of um pitfalls that can be avoided?
00:27:05.519 --> 00:27:05.759
Yeah.
00:27:06.480 --> 00:27:14.880
I mean, we we we have three buckets or three ways of thinking about safeguarding personal data in terms of processes, policies, et cetera.
00:27:14.960 --> 00:27:18.400
One is like the what are the organizational safeguards we put in place, right?
00:27:18.480 --> 00:27:25.279
So that's the what's the I mean there's a term there's like binding corporate rules and you know what are the what are the rules that we establish?
00:27:25.359 --> 00:27:26.559
How do we train our people in it?
00:27:26.640 --> 00:27:32.799
How do we how do we audit that um either internally or have external auditors audit that?
00:27:32.960 --> 00:27:42.160
The second is around sort of the technical safeguards, which is the deep space around, you know, you know, what are all the technical safety ones for if you're ICL compliance or SOC2 compliance?
00:27:42.240 --> 00:27:46.559
And a lot of that is you know laid out by other bodies, so it's not that you're dreaming up.
00:27:46.640 --> 00:27:48.160
There's there's ways to become compliant.
00:27:48.400 --> 00:27:50.960
And sometimes in our space, you have to be compliant.
00:27:51.119 --> 00:27:58.400
You know, a hospital won't deal with us unless we are so certified, SOC2 compliant, HIPAA compliant, all these, all these things, hip in the US.
00:27:58.559 --> 00:28:01.359
It's about healthcare, uh, how we control healthcare data.
00:28:01.599 --> 00:28:25.039
And then there's the contractual safeguards, not just that you have with customers, but it's how you choose your partners and your um, you know, the the trusted network of third parties that you have, because it's never just you and the customer, there's always others that have a potential access and potential positive and negative effects around security and the use of data.
00:28:25.200 --> 00:28:29.680
That's, you know, this is where vulnerabilities come in and cybersecurity becomes so important.
00:28:29.920 --> 00:28:39.279
You know, all these uh, you know, the data breaches we all hear about aren't, you know, rogue employees, they're they're third-party vulnerabilities generally that come through the door.
00:28:39.599 --> 00:28:45.920
So those three, those are the three chunks we think through, sort of organizational, technical, and then contractual.
00:28:46.160 --> 00:29:00.880
And we have kind of checkpoints for figuring out each one of those and whether we and you know, whether we're robust enough in each, and then continue to evolve it as our technology evolves, as rules and regulations evolve, as consumer uh expectations evolve.
00:29:00.960 --> 00:29:03.039
You know, do we evolve those as well?
00:29:03.279 --> 00:29:07.839
Because right now, as you know, particularly the AI, regulations changing fast.
00:29:08.160 --> 00:29:13.200
Consumer expectations are really almost unknown and certainly going to change fast.
00:29:13.440 --> 00:29:21.839
And then the data, the importance of data and this and the nature of data, the cleanliness of data is more important than ever.
00:29:22.000 --> 00:29:34.480
So there's a there's such a it's moving so quickly, it's almost like a, you know, these are living, living documents, living processes that need to be almost updated in real time as the world moves forward so quickly.
00:29:35.359 --> 00:29:36.400
Couldn't agree more.
00:29:36.559 --> 00:29:38.720
And actually, I love what you were saying there.
00:29:38.880 --> 00:29:43.839
Um uh it's a constantly evolution uh evolutionary process, right?
00:29:44.559 --> 00:29:49.440
It's not a once and done, let's put it on the shelf, come back, dust it off in a year's time and update.
00:29:50.079 --> 00:29:58.640
Um, interestingly, uh again, uh, I think what is faster than government regulation is actually human expectation.
00:29:58.880 --> 00:30:04.319
And uh that that's the real uh tip of the spear, right, in terms of trying to keep up with that.
00:30:04.480 --> 00:30:16.319
And that's where I think there is pressure on businesses, the smart businesses, to stay ahead of that as best as they can, because regulation, like you said, is moving to address issues that are surfacing up.
00:30:16.400 --> 00:30:20.160
But that still takes a little bit of time to work its way through the process.
00:30:20.640 --> 00:30:27.759
But our expectation as consumers isn't isn't uh is is is always going to be preceding that process, right?
00:30:27.839 --> 00:30:37.440
And therefore, brands, if they want to build that trust, need to be trying to anticipate where the changes need to occur before they actually occur, right?
00:30:37.599 --> 00:30:38.880
Is that a fair statement?
00:30:39.839 --> 00:30:40.319
Absolutely.
00:30:40.480 --> 00:30:48.799
Consumers change on a turn on a dime, regulators take years to catch up, um, and companies are caught in the middle, right?
00:30:48.960 --> 00:30:54.799
Trying to deal with the regulatory changes that are always lagging, but the consumers are always out ahead.
00:30:55.039 --> 00:30:56.720
And uh you said something earlier.
00:30:56.799 --> 00:31:07.359
I just wanted to give a it sort of sparked something in my mind, and and maybe the the the audience will definitely have this experience uh as consumers or as as business people.
00:31:07.759 --> 00:31:11.440
The um and this is my personal experience.
00:31:11.680 --> 00:31:17.200
I want to be able to choose where I get hyper-personalization, right?
00:31:17.279 --> 00:31:18.640
I I don't want it chosen for me.
00:31:18.720 --> 00:31:21.759
Now maybe that's just me, but I do think a lot of people are like this.
00:31:21.920 --> 00:31:25.039
And and I find I'll give you an example the other day.
00:31:25.200 --> 00:31:29.440
I um I was uh I had I was booking an airline, a flight on an airline.
00:31:29.920 --> 00:31:31.359
We'll go unnamed.
00:31:31.519 --> 00:31:33.279
Um, and uh great airline.
00:31:33.359 --> 00:31:41.279
I fly them a lot, and uh it was a frequent flyer flight, a lot of points, and it was going to be for somebody else in my family who's a miner.
00:31:41.440 --> 00:31:45.440
She's she's under 14, and so and she was gonna fly alone, unaccompanied.
00:31:45.680 --> 00:31:49.680
Okay, so online you can't do that for certain legal reasons.
00:31:49.759 --> 00:31:51.119
You have to then call in.
00:31:51.279 --> 00:31:52.160
And then I called in.
00:31:52.240 --> 00:31:59.680
They said, Well, you need to book it online as if it was an adult, then you need to call this number, and then they'll be able to change it to a to a uh unaccompanied minor.
00:31:59.759 --> 00:32:02.559
Okay, and they charge you a fee for that as well, which is good.
00:32:02.720 --> 00:32:07.119
So um they really they hit you every time they can, which is great.
00:32:07.279 --> 00:32:09.440
Um, but anyway, okay, got it.
00:32:09.519 --> 00:32:14.640
So when I called back, the person I spoke to, I'd explained everything, you know, and I my time is precious.
00:32:14.799 --> 00:32:19.680
My wife couldn't do it for me because she's not the cangle holder, it's my point, so I had to do it, you know.
00:32:19.759 --> 00:32:25.599
And then I wind up talking to a human being, and the truth is that human being had an accent that didn't really understand, it wasn't a good line.
00:32:25.680 --> 00:32:27.440
I'm like, why isn't AI doing this?
00:32:27.519 --> 00:32:36.400
You know, and then she said she couldn't handle it, and so she transferred me to somebody else, and then I had to wait on hold and eventually that other person comes on, and then they said, How can I help you?
00:32:36.640 --> 00:32:41.039
And all I said was, Didn't your colleague explain to you what my what my query is?
00:32:41.119 --> 00:32:41.759
No, they didn't.
00:32:41.920 --> 00:32:43.279
I had to re-explain it all again.
00:32:43.359 --> 00:32:53.839
And again, I'm sitting there going, like, I would have pressed the have a gen AI solve my problem button now on the phone, like choose one because I don't want to do this, right?
00:32:54.000 --> 00:32:58.160
This is not a big thing, and and it's a process.
00:32:58.319 --> 00:33:07.440
It took me, it took me 55 minutes to sort that out, and it's the simplest thing, uh, that at least in you know my experience.
00:33:07.599 --> 00:33:12.160
So in that case, I wanted hyper-personalization and I want it solved immediately.
00:33:12.240 --> 00:33:17.119
Yeah, but then other cases, I don't want to be hyper-personalized things, I want to be more anonymous.
00:33:17.200 --> 00:33:19.519
So, but I don't have the right to choose.
00:33:19.759 --> 00:33:22.640
And so I think that's a that's a big opportunity again.
00:33:22.720 --> 00:33:26.400
It's a challenge, but it's an opportunity, I think, for brands to to give that level of choice.
00:33:26.720 --> 00:33:34.799
No, I I love I love that example because I think uh most people will connect with that in one way, shape, or form, uh, having gone through that.
00:33:34.960 --> 00:33:38.079
And I think you you also referenced earlier the toggling idea, right?
00:33:38.160 --> 00:33:45.440
Like being able to toggle um sort of where you want that deeper personalization, but other areas where you won't want that.
00:33:45.519 --> 00:33:56.240
And I think this is again where the new frontier is of opportunity for a lot of brands, is to start thinking about how they can give that, you know, hyper individualization, dare I say it, right?
00:33:56.480 --> 00:33:59.920
In terms of what I'm comfortable with and what I'm not comfortable with.
00:34:00.079 --> 00:34:16.480
But also I think it's really important in the spirit of transparency, because we at Twitter we talk about accountability, transparency, and responsibility as being the three core pillars and how we think about AI, both not in terms of just how we build that into our products, but how we use the tools internally ourselves, right?
00:34:16.800 --> 00:34:24.239
Um, and I think being um transparent with uh customers about when they're using an AI is really important.
00:34:24.480 --> 00:34:26.400
And also creating off-ramps, right?
00:34:26.480 --> 00:34:31.679
I think like a good example you gave there, you may maybe I I am comfortable with AI chatbots.
00:34:31.760 --> 00:34:43.840
I want to start with that, but also if it gets complicated, or if this is a you know uh really important topic or you know, there's risk involved, i.e., fraud in my account, whatever it might be, I want to then talk to a human.
00:34:44.079 --> 00:34:50.719
So I think that's Stephen is where we're what we also see is a new opportunity for folks in how they work with AIs.
00:34:50.880 --> 00:34:52.239
Do you would you agree?
00:34:52.639 --> 00:35:02.719
I love the idea of off-ramps because I think there's this idea that once you're on the AI highway, you're on the AI highway, whether the consumer wants it or not.
00:35:02.800 --> 00:35:12.719
And I think this idea that I'm happy that or I prefer to step off or step into another uh lane, I think should be uh should be offered.
00:35:12.880 --> 00:35:15.760
Um again, I think winning brands will will figure that out.
00:35:15.920 --> 00:35:18.400
I think the other thing, you just mentioned transparency, right?
00:35:18.480 --> 00:35:28.559
And I and we're talking about processes, and um I find a lot of brands still don't really think deeply about transparency and maybe think about the present.
00:35:28.639 --> 00:35:30.480
So I'll give you I'll give you an example.
00:35:30.719 --> 00:35:32.320
Pricing is a great example.
00:35:32.559 --> 00:35:35.360
So why does something cost what it does?
00:35:35.519 --> 00:35:39.599
Now there's all kinds of detail behind that, right?
00:35:39.679 --> 00:35:47.360
Like everybody, Twilio, my company, anybody listening, you price your product a certain way for certain consumers for a reason.
00:35:47.679 --> 00:35:52.880
But 99% of the time, you the you do all you tell all you tell the consumer is the price.
00:35:53.039 --> 00:35:54.880
You don't tell them what's behind it.
00:35:55.280 --> 00:36:00.400
And I think that's an opportunity to start to uh build trust, coming to building trusts.
00:36:00.480 --> 00:36:08.880
And again, with AI, this become much more dynamic, but to build trust with consumers about exactly why is that why is that price there versus somewhere else?
00:36:09.199 --> 00:36:14.000
And giving people agency about uh maybe what they want to pay.
00:36:14.079 --> 00:36:16.320
I mean, I'll give you an example from years ago.
00:36:16.480 --> 00:36:25.199
I was working in the auto industry, this is like 25 years ago, and we had this big debate around um the around in car dealerships.
00:36:25.440 --> 00:36:27.280
And if you've ever bought a car, this happened yourself.
00:36:27.360 --> 00:36:33.440
If you walk in a dealership, you know, you negotiate, the car costs 50,000 or 70,000, and then you start to haggle.
00:36:33.519 --> 00:36:44.400
And the old um joke that, you know, I'll go talk to the sales guy says, I'll go talk to my boss and see if I can, and he doesn't talk to anybody, he just goes off and has a cigarette and comes back.
00:36:44.719 --> 00:36:48.400
But the problem is you don't know how much that guy is making.
00:36:48.559 --> 00:36:58.559
Like if we we did a survey, and the survey showed of consumers that they always assumed it was saying it's a$50,000 car, they assumed the sales guy was making like$10,000 on that sale.
00:36:58.719 --> 00:37:03.280
And the reality is the sales guy's making like$1,500, right, for solving that car.
00:37:03.360 --> 00:37:11.599
It's not making that much money, but because of this disparity in uh in assumptions, you they the consumer would like try to negotiate hard.
00:37:11.679 --> 00:37:17.760
And the reason the sales guy stops stops is I'm not gonna make any money on the sale if the price goes too low.
00:37:18.000 --> 00:37:26.159
And so I would argue that in that case, it's maybe it's better to tell the consumer, hey, I'm only making a little bit of money on this, you know.
00:37:26.480 --> 00:37:30.559
I'm I'm doing it, I'm we're on the same side here, but you know, I still need to pay my bills.
00:37:30.639 --> 00:37:31.840
I got and I got a family.
00:37:31.920 --> 00:37:34.639
And and they're trying to establish that human relationship.
00:37:34.719 --> 00:37:36.719
That's what good salespeople do, right?
00:37:36.800 --> 00:37:38.000
I it's human human.
00:37:38.239 --> 00:37:45.280
And so I don't I think with AI, you could you could supercharge those sorts of opportunities around true transparency.
00:37:45.360 --> 00:37:48.400
And maybe pricing is one place every brand could start.
00:37:48.719 --> 00:37:50.000
I I couldn't agree more.
00:37:50.079 --> 00:38:14.000
And again, um, you know, I you the word transparency is used a lot, and I think it does require double clicking into that and really exploring how we can apply that from pricing to how we manage your data through to um uh even how we would respond to it being uh breached in some way, shape, or form and being open with community.
00:38:14.239 --> 00:38:21.440
So I think that is increasingly gonna become more and more important in how brands ultimately that connection and ultimately trust.
00:38:21.599 --> 00:38:26.400
Um, and we sort of we've been moving towards a bit more focus on technology.
00:38:26.480 --> 00:38:33.119
I'm gonna use that as a segue because I knew we're gonna uh be able to fill an hour easily in terms of conversation here.
00:38:33.280 --> 00:38:49.599
I want to go to the next poll um because uh I'd like to get the audience back in here and really get their view on what is your biggest trust or challenge, sorry, biggest challenge when it comes to using technology to balance privacy and personalization.
00:38:49.920 --> 00:39:05.119
Um, we've got a few choices here, ensuring data security while providing personalized experiences, gaining customer trust through transparent data practices, managing compliance with evolving privacy regulations or something else entirely, let us know in the chat.
00:39:05.199 --> 00:39:12.559
Um, I've now figured out what my problem was with the poll, I think, before I was it was user error, it wasn't technology glitch.
00:39:12.719 --> 00:39:15.360
So um I can now see the poll.
00:39:15.599 --> 00:39:19.840
Um, so I'll give it give folks a little bit of a moment to fill that in.
00:39:19.920 --> 00:39:32.960
But if you think about this, both in terms of whether it's for you, Stephen, or or brands you've worked with in the past, what do you see as being the biggest challenge when it comes to technology's use in balancing privacy and personalization?
00:39:33.280 --> 00:39:35.119
I think it's what I referred to before.
00:39:35.199 --> 00:39:43.119
It's the idea that because a technology exists doesn't necessarily mean you should you should interpose it between you and the consumer.
00:39:43.440 --> 00:39:59.199
And you know, being truly focused on what's the what's the how do I build trust and and and confidence in that consumer that I'm going to treat them in the way that they want to be treated at that point in their journey.
00:39:59.519 --> 00:40:18.880
And I think there's so many technologies now, there's not just AI, there's you know different channels, different ways of uh, you know, different ways of using data, different ways you can build you can build data and technology into your product in a way that wasn't possible before, that you almost get dazzled by it as a as a as a brand.
00:40:19.119 --> 00:40:23.360
But I think you're gonna pull back from that dazzle to say, what am I trying to achieve here?
00:40:23.519 --> 00:40:25.119
What's what matters?
00:40:25.440 --> 00:40:42.000
And I think with with with that framing about what really matters and what comes from that human connection, that human need of the consumer, that's then where you will figure out how to and where to apply that technology, either in the back end or in the front end when you're interfacing with them.
00:40:42.239 --> 00:40:49.199
And I think again, too many times we just the technology almost takes over, it's like uh Frankenstein's monster.
00:40:49.280 --> 00:40:55.440
It just kind of takes over what you're doing without really thinking about the person at the other end of it.
00:40:55.599 --> 00:41:03.039
And I and I no, I see options you have in the poll reflects the yeah, it does actually, yeah.
00:41:03.119 --> 00:41:07.599
Uh, and uh, I think it looks like the top ones actually, there's two of them are pretty close.
00:41:07.679 --> 00:41:15.760
So ensuring data security while providing personalized experiences and gaining uh customer trust through transparent data practices are the two top ones there.
00:41:15.840 --> 00:41:17.440
But I I love what you were saying again.
00:41:17.599 --> 00:41:25.360
Um, sometimes can or two leave people surprised by this, but you know, I I love the quote from Steve Jobs.
00:41:25.440 --> 00:41:30.159
Um, but when he said he talked start with a customer experience and work back to the technology.
00:41:30.320 --> 00:41:40.960
Um, don't start with the technology, is always my advice um when working with customers, because um, you really need to really be clear and understanding what is the problem I'm trying to solve.
00:41:41.119 --> 00:41:48.639
Because nine times out of ten, I don't know about you, Stephen, but what I see is folks addressing symptoms and not prop the core pro root cause of the problem.
00:41:48.719 --> 00:41:58.239
Um, and that can lead you down a completely wrong path, especially when it comes to then selecting the right technology solutions that you are ultimately really need to get where you want to get to.
00:41:58.400 --> 00:42:02.400
And look, you know, one thing's for sure, you we need technology, right?
00:42:02.480 --> 00:42:03.360
There's no doubt about that.
00:42:03.440 --> 00:42:08.480
That's ultimately going to be the enabler of any sort of business transformation.
00:42:08.719 --> 00:42:13.119
But again, that's not the starting point, is what I'm hearing from you, because there's just so many choices.
00:42:13.199 --> 00:42:16.159
And I think folks get overwhelmed as a as a result of that.
00:42:16.400 --> 00:42:19.280
Well, Apple's Apple's a really great example.
00:42:19.440 --> 00:42:30.559
I mean, let's you know, tip our hat to the greatest, one of the greatest companies in the world, um, in terms of the technology they've built and the impact they've had and the tech and the industries they've disrupted.
00:42:30.639 --> 00:42:41.440
But if you go back to the to a technology choice here, which was grounded in consumer behavior and consumer need, and someone in the audience will remember this moment.
00:42:41.920 --> 00:42:50.880
And there was a moment when the we'll remember the Blackberry was the personal, you know, the personal device of dominance, right?
00:42:51.039 --> 00:42:57.039
And the Blackberry's big differentiator was just the clicky keyboard that we all remember.
00:42:57.280 --> 00:43:00.079
Um, and there was even a film about this, right?
00:43:00.159 --> 00:43:06.639
There's a there's a film about Blackberry, it's a funny film, but it's got a very profound kind of message in there.
00:43:06.719 --> 00:43:17.119
And one of the messages, several messages, but one of them is the idea that they were obsessed by the idea that no, it the keyboard, the keyboard with your thumbs matters.
00:43:17.199 --> 00:43:21.039
People want to feel the clicking, they want the tech, the tactile nature of it.
00:43:21.599 --> 00:43:32.480
The choice around technology that Jobs made was that no, you you need to not have any buttons that are permanent, you need to have a touch screen where you can put any button you want on that screen.
00:43:32.639 --> 00:43:40.320
Now, that was not an easy technology to build or to deploy, but it turns out Steve Jobs and Apple were absolutely right.
00:43:40.480 --> 00:43:44.800
The touch screen was where people wanted to go, not the not the keyboard.
00:43:45.039 --> 00:43:54.480
And yet all the evidence in the early in those days showed that you know people were obsessed and loved the tactile uh keyboard that that Blackberry had.
00:43:54.559 --> 00:43:59.519
But but Jobs had another insight that went a completely different way, and there was a big risk.
00:44:00.320 --> 00:44:13.599
So I think that, you know, getting deep in what customers really want and really starting to and see the, almost see like, I don't want to say the long distance future, but see the next evolution about where you can take consumers.
00:44:13.840 --> 00:44:20.480
Again, I think brands really need to think about not just what they want today, but where are they going to go tomorrow and then how can you take them there?
00:44:20.559 --> 00:44:22.639
And that's where the winning brands are going to be.
00:44:22.880 --> 00:44:23.920
Oh, I couldn't agree more.
00:44:24.000 --> 00:44:30.239
I mean, uh, I was working for a company at the time that was working with BlackBerry from a global partnership perspective.
00:44:30.320 --> 00:44:40.800
And I remember working with some pretty senior people at Blackberry, and this is around 2008, and um, the company I work for was a global enterprise software company.
00:44:40.960 --> 00:44:45.280
Um, and I said, guys, I'm seeing my execs starting to use the iPhone.
00:44:45.679 --> 00:44:47.760
I think there's a change afoot here.
00:44:47.920 --> 00:44:51.679
And they were so sure, certain that that wasn't happening.
00:44:51.760 --> 00:45:00.480
But once you see execs in a company switching devices or to a new technology, there's a good potential uh signifier that there's a change afoot.
00:45:00.559 --> 00:45:03.679
But there was a hubris, I think, that gets that existed.
00:45:03.760 --> 00:45:17.119
And I think that's the risk for all companies is that you've got to not get so focused on what you do, and to your point, have an over-the-horizon sort of uh uh focus in trying to anticipate what's coming next.
00:45:17.360 --> 00:45:28.079
Yeah, it's looking at your it's looking at your product, your service, and your experience for your consumer and saying, what's the clicking keyboard in our world that like it seems to be the right thing today?
00:45:28.239 --> 00:45:33.280
But the truth is we could use technology to make it a lot better or to transform it.
00:45:33.519 --> 00:45:35.280
And where are we at risk, too?
00:45:35.360 --> 00:45:45.039
That's some something about our product or service, our our experience for our consumers, it risks going down the route of black of a Blackberry clicking keyboard.
00:45:45.199 --> 00:46:04.559
Um, and I think a again, a lot of brands I think aren't aren't grappling with that because uh generative I is this great, I mean, the best, uh the great that we haven't had a technology in 30 years or longer that's been so potential for such transformation of custom consumer experience as generative AI.
00:46:04.719 --> 00:46:13.920
And yet I see brand after brand of brand, I think, doing kind of simple, dumb, you know, not the smartest things, um, and or doing nothing or not getting it.
00:46:14.000 --> 00:46:17.119
I mean, when I talked to the airline the other day, I'm like, why haven't they solved this problem?
00:46:17.599 --> 00:46:23.840
Literally, I mean it's that is you would you don't need generative AI to tell the next caller that what I called about.
00:46:24.000 --> 00:46:30.719
Um, and so it's so in some of that's just that stuff needs to just still be ironed out even before we get to generative AI.
00:46:30.960 --> 00:46:41.840
Well, maybe maybe jumping in there, what role do you see AI and machine learning playing when it comes to optimizing personalization and privacy and compliance?
00:46:42.000 --> 00:46:44.400
I mean, yeah, maybe we can explore that.
00:46:46.320 --> 00:46:47.039
Compliance.
00:46:47.840 --> 00:46:58.639
Yeah, this should be the compliance used to be the topic I hated the most, like the idea that you know, uh, you know, we need to uh you know, you have guardrails, safeguards, all this sort of stuff.
00:46:58.719 --> 00:47:07.599
And I when I worked at Facebook back in the day, look, I was in the I was in the commercial side of the organization, not in the technical side of the business.
00:47:07.920 --> 00:47:16.960
But the idea of putting guardrails on things and can you know and worrying about compliance was almost foreign to the the culture and the and the business.
00:47:17.199 --> 00:47:25.519
I think it's part of the reason that Facebook made uh did great things, but also made some mistakes along the way because we didn't have enough of those guardrails.
00:47:25.679 --> 00:47:34.960
Now, since I've come over to building AI uh for the human brain, the first products and applications we're building are into the healthcare system and into medical land.
00:47:35.119 --> 00:47:40.320
Well, there you don't understand compliance and safety and security.
00:47:40.480 --> 00:47:41.679
You will not survive.
00:47:42.239 --> 00:47:45.039
You need to deal with the TA or the FDA.
00:47:45.119 --> 00:47:46.880
Your product needs to be safe and effective.
00:47:46.960 --> 00:47:48.800
You you get audited all the time.
00:47:48.880 --> 00:47:52.079
If there's anything that goes wrong, it has to be reported.
00:47:52.159 --> 00:47:55.519
You know, you have to uh document everything, nothing gets swept under the rug.
00:47:55.760 --> 00:48:03.760
And so we've now built a much more uh I've we had a project in the early days of the company which was called up, which was called Project Comply.
00:48:03.920 --> 00:48:05.119
That was literally the name of it.
00:48:05.280 --> 00:48:18.400
And I fell in love with Project Comply because I realized the better we were at compliance, the better we would be able to make our products and services for our customers and the more successful our business would be.
00:48:18.719 --> 00:48:28.719
So I went for it's almost a joke inside the company about how I fell in love with Project Comply after I was, you know, that word would have repelled me before.
00:48:28.960 --> 00:48:43.039
And so in the age of AI around compliance and how do we think about it, you know, we've got uh we've got so many opportunities and challenges, fraud, risk, you know, there's a huge space now.
00:48:43.199 --> 00:48:54.880
Um how do we how do we get a unified view of our customer and how do we make sure that all that data is accurate and we're using it in an appropriate way with the right safeguards and transparency?
00:48:55.280 --> 00:49:05.360
Um, how do we incorporate AI into our existing platforms, customer experience platforms, CRM, you know, um customer SaaS platforms.
00:49:05.679 --> 00:49:25.280
So um, and what's the what's the right level of and the balance between constraining yourself and in our in our business we have to be quite constrained because we build for the world of healthcare, but also thinking about how can we where where's the white space?
00:49:25.440 --> 00:49:36.880
Where can we actually be less how can compliance not slow us down in terms of innovating, pushing the boundaries, building new things for customers, um, and moving fast.
00:49:37.119 --> 00:49:41.039
So that balance, I think AI's only made it more challenging.
00:49:41.199 --> 00:49:45.840
And I think it's going to be not just true for my company, but for every company in the world.
00:49:46.239 --> 00:49:48.800
I think I was just thinking, I love again, I love that.
00:49:48.960 --> 00:49:52.000
I think that constraint, though.
00:49:52.559 --> 00:49:56.079
So the comply piece, I love that journey of you you had there.
00:49:56.320 --> 00:50:05.360
Um again, the the the the objective of complying is ultimately end of the day to still deliver a great experience and product to the end customer, right?
00:50:05.440 --> 00:50:06.320
That's the intent there.
00:50:06.400 --> 00:50:18.960
So if that is at the center of what you're trying to do, but also the constraints that that created for you guys obviously then forces you to be more creative in thinking around how do you solve for that, I would imagine.
00:50:19.199 --> 00:50:20.480
Is that a fair statement?
00:50:20.559 --> 00:50:24.559
And that that those constraints can help you actually innovate.
00:50:24.800 --> 00:50:25.440
Yeah.
00:50:25.920 --> 00:50:34.239
So if if you look at great artists, I would when I started my career as a long, long time, I was a musician, I was a classical pianist and violinist.
00:50:34.320 --> 00:50:38.320
I didn't have the talent to go to where I wanted to go, so I left it behind.
00:50:38.559 --> 00:50:45.599
But the thing you learn about when you're uh particularly let's take music, for example, is um music is full of compliance, right?
00:50:45.679 --> 00:50:49.199
Which is, you know, you have to tune your instrument a certain way.
00:50:49.360 --> 00:50:55.280
There's certain notes that are part of the you know, the part of how you play, right?
00:50:55.599 --> 00:51:00.000
How different instruments play with each other all has to comply to the same rules.
00:51:00.159 --> 00:51:05.199
There's you know, there's tonal and there's melodic rules about how at least Western music is produced.
00:51:05.280 --> 00:51:07.039
Why do things like Indian music sound different?
00:51:07.199 --> 00:51:08.320
Because the rules are different.
00:51:08.559 --> 00:51:16.000
The tonal structures and the and the the melod, the melodic structures or the the the frameworks that they use are different.
00:51:16.079 --> 00:51:16.960
That sounds different.
00:51:17.039 --> 00:51:25.360
But Western music, you know, if you hear something that sounds dissonant or it's uh it's uh or it's out of tune, it's like, oh, this might hits my ear wrong.
00:51:25.679 --> 00:51:26.480
Your ears fine.
00:51:26.639 --> 00:51:31.440
It's just that you're used to a complied, a compliance framework around how music is produced.
00:51:31.599 --> 00:51:45.599
So being a former musician, what happens is with when you put constraints on people, constraints don't um they don't inhibit creativity, they they encourage creativity within those constraints.
00:51:45.760 --> 00:51:52.960
So, you know, why was there's been there's been hundreds and hundreds of classical music composers over the centuries, thousands.
00:51:53.280 --> 00:51:55.679
But why does Mozart stand above?
00:51:56.079 --> 00:52:02.719
Is it was it because he broke all the rules and used the different uh different instruments or used different uh tonal scales?
00:52:02.880 --> 00:52:07.599
No, no, he used the same, he was in the same rules inside the same box of compliance to everybody else.
00:52:07.760 --> 00:52:15.679
But what he did is he he would he was more creative within that those that box of compliance, and so it's not a constraint uh at all.
00:52:15.840 --> 00:52:21.280
Um, it's you you have to draw a box somewhere, and then within that box, you can be a genius.
00:52:21.519 --> 00:52:35.199
And so I tell our company that doesn't matter, we can be geniuses within this box, uh, and we have to be a genius within that box because without some compliant compliance and constraint, you don't have a business.
00:52:35.280 --> 00:52:43.519
You have a you're you have you're an anarchy, and you don't have something that's safe and effective in the in the world of what we build, brain-related technology.
00:52:44.000 --> 00:52:49.199
But I I also think that that's fully transferable, irrespective of your and uh your industry.
00:52:49.360 --> 00:53:01.599
That's why I wanted to double-click on that, because I feel what you just shared there for those that are listening, irrespective of the industry in, you know, don't see compliance and privacy and um you know as a restriction.
00:53:01.760 --> 00:53:03.840
See it as well, it is a restriction.
00:53:03.920 --> 00:53:12.880
There, there's there's it's it's it's gonna be a forcing mechanism for you to be more creative in in thinking through how you could solve for those specific needs.
00:53:13.039 --> 00:53:20.800
Because at the end of the day, it is about delivering your customer that ability to trust that you have their best interests at heart, right?
00:53:20.960 --> 00:53:23.440
I think that's that's sort of what I take away from that.
00:53:23.519 --> 00:53:25.920
So I I really love the fact that you you shared that.
00:53:26.000 --> 00:53:26.480
That was brilliant.
00:53:26.639 --> 00:53:28.639
I knew look, we're we're coming up on time.
00:53:28.800 --> 00:53:36.880
I've got a uh one final question for you, then I'm gonna throw to the to the audience for um, I think one final survey.
00:53:36.960 --> 00:53:38.000
Oh no, no, we don't.
00:53:38.079 --> 00:53:43.119
Um actually, I'll just wrap up with you on one final question and then we'll wrap up the session.
00:53:43.360 --> 00:53:57.599
What do you think um is the single most important thing that companies need to do differently um right now in striking the right balance between privacy and personalization?
00:53:57.760 --> 00:53:58.400
Yeah.
00:53:59.760 --> 00:54:16.559
So I think coming back to something I said earlier about giving choice across the spectrum, I think the ability for consumers to choose their level of personalization with your product or service is going to become the new expectation.
00:54:16.719 --> 00:54:18.719
I I it's up to me to choose.
00:54:18.960 --> 00:54:24.079
So many brands, many companies, there it's more of a one, it's a one size fits all.
00:54:24.159 --> 00:54:27.920
We will, you know, everybody gets the same type of personalization.
00:54:28.000 --> 00:54:35.119
So we're not we're not all getting the same message or the same experience anymore, but we're all getting the same le assumption about the level that we want.
00:54:35.280 --> 00:54:36.400
I think that's wrong.
00:54:36.559 --> 00:54:39.199
I think the age of AI, what's AI?
00:54:39.360 --> 00:54:41.679
AI is hyper-personalized everything.
00:54:41.840 --> 00:54:44.400
I mean, no more searching Google and getting blue links.
00:54:44.559 --> 00:54:50.480
No, no, the the the answer is hyper-personalized to your uh you know, to your your prompt engineering.
00:54:50.719 --> 00:54:52.880
By the way, is that that's a term that needs a rebrand.
00:54:52.960 --> 00:54:56.320
I think it's worse sounds painful, prompt engineering.
00:54:56.480 --> 00:55:01.519
But prompt engineering is just asking the right questions and asking a question that's specific to your needs.
00:55:01.760 --> 00:55:12.960
So that idea that you can give different levels of choice around privacy and personalization to every single customer and giving off ramps, that I think is the number one thing that brand should be thinking about today.
00:55:13.280 --> 00:55:13.760
Awesome.
00:55:13.840 --> 00:55:15.199
I I I couldn't agree more.
00:55:15.280 --> 00:55:17.920
I think it's a great insight to share with the audience.
00:55:18.159 --> 00:55:22.000
Um I I really want to thank you.
00:55:22.079 --> 00:55:40.559
Um, I'm gonna actually ask you, I didn't sort of set this up, so uh I would like to ask you what is a resource that you go to to stay abreast of the latest and greatest, or a thinker that really influences or is having an influence on you in how you navigate um, you know, today's business world.
00:55:40.960 --> 00:55:42.239
So that's good.
00:55:42.639 --> 00:55:46.320
You know, I'm sure each one of us has I spent a lot of time in AI.
00:55:46.960 --> 00:55:57.360
I try to figure out not just what are the big things going on, but also like what's happening at the core face of of consumer experience of how companies are running themselves.
00:55:57.519 --> 00:56:03.920
And so there is a um uh uh through LinkedIn and through social media, there's a there's something called the rundown.
00:56:04.079 --> 00:56:05.760
I think it's called the rundown of AI.
00:56:06.159 --> 00:56:10.239
And so the rundown is I'm sure there's other newsletters, but it's a really simple.
00:56:10.480 --> 00:56:12.159
I get it in my inbox every day.
00:56:12.320 --> 00:56:33.760
You can go to you can go online to find out socials, but the rundown is a really good summary of just like the what are the big things happening in AI and some folks on AI today, but also more importantly, like what are the two it's like spotlight on different tools, different apps, different edge and AI tools that are coming out, and you know, a little and discussions about you know pros and cons of them, what are different alternatives, etc.
00:56:34.159 --> 00:56:35.119
I cannot keep up.
00:56:35.280 --> 00:56:38.079
I was just went to uh Google's website the other day.
00:56:38.159 --> 00:56:42.000
I mean, they had like 321 different use cases for generative AI.
00:56:42.159 --> 00:56:44.480
Like that was literally the the title.
00:56:44.719 --> 00:56:49.199
And there's thousands of use cases for generative AI, but you can't even keep up with it all.
00:56:49.360 --> 00:56:51.760
So the rundown AI I find pretty useful.
00:56:51.840 --> 00:56:53.840
I think it has several million subscribers.
00:56:54.000 --> 00:56:55.119
That's a good one for me.
00:56:55.360 --> 00:56:58.719
You're uh the audience will probably have other ones they find uh useful as well.
00:56:58.800 --> 00:57:01.360
There's only so many hours in the day I can spend digging in.
00:57:01.440 --> 00:57:05.199
I've got to still run my business, but that's been a really useful one for me.
00:57:05.519 --> 00:57:06.000
Perfect.
00:57:06.079 --> 00:57:08.480
Look, I I've just shared the link with the team.
00:57:08.639 --> 00:57:10.480
Hopefully they can push it out to the audience.
00:57:10.719 --> 00:57:11.840
I'm gonna subscribe.
00:57:12.000 --> 00:57:14.800
That wasn't one uh that I was subscribed to.
00:57:14.880 --> 00:57:15.599
So definitely doing it.
00:57:15.760 --> 00:57:18.159
Look, I really want to thank you, Mighty, for taking the time out.
00:57:18.239 --> 00:57:36.480
Um, again, the goal with this series is to share insights that can hopefully help the audience uh go back into their offices tomorrow or today and start noodling on ways that they can drive the business forward in you know, meeting the challenges that sit before ahead of us all, right?
00:57:36.559 --> 00:57:37.840
We're all grappling with this.
00:57:37.920 --> 00:57:39.920
So really appreciate that.
