Stefan Leslie 00:05
Welcome to the Beyond Research Podcast and the Idea Machines Podcast. I’m Stefan Leslie, CEO of Research Nova Scotia, and Ben Reinhardt is the CEO of Speculative Technologies. Both Ben Reinhardt and I have our own podcast for our respective organizations. We’ve got Beyond Research. So, if you’ve heard some relatively neutral music, that’s the Canadian version. And then if you’re listening to the Idea Machines Podcast, that’s the more dramatic American music, that’s Ben’s. We discuss research funding organizations that are challenging the traditional status quo to fill gaps in the system and support work that is uncertain, but if true, will lead to significant shifts and tackle big societal problems. Our organizations lead two different initiatives that fit under this umbrella of coordinated research programs. We explore the similarities and differences between our programs, the structures of them and the key players, the risks and challenges as well as the strengths and the possibilities. Ben’s Speculative Technologies is a nonprofit industrial research lab focused on materials and manufacturing technologies that don’t have a home in other institutions. It finds scientists with deep technical expertise with a clear vision of big-if-true technologies that don’t fit with large companies and startups that focus on profit and growth because their work is uncertain and don’t fit in the academic system that tends to prioritize novelty and academic outputs over usefulness. SpecTech works with these scientists to figure out how to build those technologies and help them execute on that plan. Research Nova Scotia is also a nonprofit, but one funded by Nova Scotia to organize, coordinate and support the research in the province. Although we do lots of different things, we’ve launched Focused Research Investments, or FRI, to support research driven by and in service of society. We are selecting teams to drive this research, providing substantial, secure and flexible funding they need to realize ambitious projects and achieve societal outcomes. We’re recording this in June, so we’re right in the middle of the development process. Two organizations, but both working to find creative ways to fund really important research. The reason why I wanted to talk to you and have us on each other’s podcasts is I actually think our organizations are working in much the same space, and
Ben Reinhardt 02:42
Yes
Stefan Leslie 02:43
that space can be probably defined as occupying a set or interested in a set of questions that is neither covered by the kind of research activity that is just purely based on discovery, advancing the frontiers of human knowledge, a really important and interesting part of what makes us human, but nor are we really involved in that other end of that spectrum, which is kind of the direct application, where there’s an immediate market for something, but there’s that unoccupied, or less occupied, middle space where there’s really important outcomes that can be identified, but they haven’t necessarily been formulated as research questions that can then be can be brought to the research community. And so, this is the space of where you’re interested in how systems work, you know, platform technologies, or platform ideas that can be applied in a range of different areas, monitoring and observation, which doesn’t get picked up by other things. In this bucket or in this category, there’s all sorts of really important and interesting work, and lots of different organizations that are having little pieces of it. And I think SpecTech, or Speculative Technologies, is one of them, and Research Nova Scotia is another. And so, I’m going to start just by asking a question of, well, first of all, do you agree with the way I’ve laid out and what is your piece in that? Like, what does SpecTech do within that middle space?
Ben Reinhardt 04:10
Where I see Speculative Technologies as sitting within that is what I describe us as doing is like, I’m making air quotes for people who can’t see, I call it like pre-commercial technology research, which is not an official term. It is a term I made up. In particular, I see us as doing four major like, quote, unquote pieces of work where it’s like one identifying things. It’s even hard to, like, identify ideas that are in this space, right? These like big-if-true ideas that don’t have a home in other institutions, road mapping out what work needs to be done to sort of get them to a point where they can be part of sort of a more traditional institution, identifying the like the key risks to those technologies, and then actually like doing the work to address those key risks, build the technology and then get it out into the world. That’s sort of where I see us as sitting. Finding people who can do that, building teams around them, helping them work with other institutions. And then also, just like providing the right incentives to some extent of you’re not focused on publishing papers and discovering things as you would in academia, but you’re also not focused on maximizing profit and shareholder value as you would be at a startup or a large company.
Stefan Leslie 05:37
Maybe a common feature of this area is that there’s no market signal on quality.
Ben Reinhardt 05:45
Yes, yeah.
Stefan Leslie 05:47
For discovery research or the exploration side of things without any discernible, immediate purpose. The market, it’s a surrogate market, but the kind of the peer system, and there are all kinds of limitations and notable failures around the functioning of the peer review system, but nevertheless, it is in essence an attempt to ensure that the quality of ideas is advanced by an acceptance of the community as being more truthful or more, a better description or understanding of a natural phenomenon or social system. There’s a more obvious market function for the other end of that spectrum, because if you’re working in an R and D area, you either develop a product that the market is willing to buy, that it meets its quality expectations, or if it’s more kind of government driven, or that kind of immediate challenge driven, did you get to the moon or not? Is, you know, that’s something of a signal that you can take back about success or not. All of the stuff that we’re talking about, I don’t think, has an ability to receive an indicator along the way, or even at the end of whether you reached it, whether you achieved that goal. Because the goals may be diffuse. They’re hard to describe. They may accrue over the course of years to decades. So you know, we struggle with this for sure, on how you define what something, what problem you ought to take on, and what you should be looking for in success.
Ben Reinhardt 07:25
I had never really thought about the marketplace of ideas as a market signal. With some of the things that we’re doing, I think it’s like you can imagine knowing whether you did the thing, but it’s so unclear whether the work that you’re doing right now will get there, that nobody’s willing to, like a rational actor would not invest in it, whether it’s from the government side, saying like ah yes, like this will clearly get us to the moon. There’s too much uncertainty about whether the thing that you’re doing is directly connected to any sort of outcome that someone wants, whether it is a profit number or some other kind of goal.
Stefan Leslie 08:10
So, you describe the space as bigger than we perhaps commonly talk about it. This is the space of DARPA and its variants, ARPA E and ARPA H, Focused Research Organizations or FROs. It’s certainly the space of FRIs, which we’re doing, Focused Research Investments. It’s the space that you guys are in kind of foundation-based things like carbon to C, and there’s other sort of organizations that are doing this. And what I think is really interesting and important about these sorts of conversations is those of us who are up to our elbows, sleeves rolled up, trying to make stuff happen in this space, probably don’t spend enough time looking for what are the common elements in the problems, in how they’re defined and how they’re attacked or addressed? What kind of teams do you need? How do you need to find ways to effectively coordinate or manage them? What metrics do you set up? How do you monitor them and I know that you know Speculative Technologies is not just an organization or a not-for-profit, that has identified a handful of these areas where you think you can move the needle on something, but clearly you’ve identified a market gap in being able to identify what those problems are and finding people who have those characteristics. And so I think there’s a huge challenge to be able to convey what it is we’re trying to achieve, like, what problems do we think are well suited to programs set up like this? And when I say like this, I mean some form of active coordination, you know, like that you’ve chosen the right problem and there is a group of people who recognize that their purpose is to achieve, to solve, you know, to achieve something at the end. And that there is a need for them to find a way to hold themselves to account to that, but also all of their other participants in that grand activity, you know, other PIs or the researchers, they need to have a functioning interaction system to always be able to determine whether their collective effort is optimally arranged to move towards that end, right? And that there’s a functioning mechanism to take corrective action. And, you know, that’s a, I can’t imagine that all of us aren’t confronted by a similar set of challenges, right? And we may be doing one thing, you may do the other, but we need to figure that out if we’re going to make progress in that middle space.
Ben Reinhardt 10:41
I call the like umbrella of all of that space of like Coordinated Research Programs, just because it is these like large things, they require coordinating a whole bunch of people, whether that’s like within a single organization, across different organizations and I think to some extent the problem, almost by definition, is that there’s no, like, one sized fits all, step-by-step approach to all of these problems. And so like, to a large extent, you’re kind of making it up as you go. You have to, like, you have to make up the process of what you’re doing every time, and so like that, that’s what each of us is struggling to do, is to, like, make up a process, and that’s why it’s hard and to some extent, like, the space is defined by problems that, like, don’t already have an existing process, because if they did, they would fit well into an existing institution. We’re trying to, like, create this, like, meta process of like, how do you figure out what the process is?
Stefan Leslie 11:47
Yeah, and I think
Ben Reinhardt 11:48
This is very abstract, but that’s what’s fun about it.
Stefan Leslie 11:52
One major difference between how we’re going about and what you’re doing is that we are using taxpayer dollars, right? We are also an arm’s length not-for-profit organization, but we are set up by the province of Nova Scotia with legislation that’s where the majority of our funding flows from, and so we have, we’re accountable to ensure that we are spending that money wisely, right? And Spec Tech or Speculative Technologies, if I understand your funding model, you have some core funding around making sure the organization runs, but then as you find good people and good ideas, and can find these sorts of, you can kind of nucleate around a particular issue and the right people, then you need to find a way to fund that, right? Is that kind of the model?
Ben Reinhardt 12:44
Right now, yes. We have dreams of being able to have a large enough pool of money that we can just go and fund it internally without having to do that sales process for every program. But as it stands right now, yes, we do, which is tricky, because, almost by definition, these things are hard to justify. And in order to fund any specific program, you then need to find people and justify to them and be like, this is why we need to do this particular program. If I could interject, I assume that it is a riff on the Focused Research Organization concept. How would you describe that?
Stefan Leslie 13:25
Yeah, so, you’re absolutely right that Focused Research Investments are a riff on Focused Research Organizations and the white paper that that those guys did, the two authors did a couple of years ago, because they openly invited people to say, here’s an idea, here’s a concept, but make it your own. Try. Convergent said, you know, try what is going to work in your jurisdiction. And so, what makes FROs different from FRIs, so FROs being the kind of the core description of an idea that came out a few years ago in FRIs, which we’ve launched here, is that FROs are very much, as I understand it, an organization in and of itself that is a performer of research. So, you actually set up a new organization and attract all of the different people or kind of talent, some of it may be contracted, but there’s a nucleus at least of those who are going to perform. And critically, it exists for a defined period of time to accomplish its goal, and then it winds up. Now, it may continue on as a new not-for-profit, or may spin off for profit companies, whatever it is, but whatever those are kind of two clearly defined characteristics of an FRO, whereas an FRI, and the reason why we chose here to set it up a little differently is getting back to how we pulled this off in Nova Scotia is probably got a couple of major parts. The first is that we’re a bit of a mesocosm sized experiment in the research world, right? So, we’re big enough that we do have enough funds that we can flow to support that very costly endeavor that is research. But we’re also small enough that and small in size of us working in Research Nova Scotia, but also the research community is small enough that we can kind of engage meaningfully with that group to understand what their capacity might be, what the uptake might be on a series of issues, and that we had some confidence that people would respond. And so what the major difference is that as a publicly funded organization, working with other publicly funded organizations, like the universities, but also what we call here the health authorities, the deliverers of health care in this province, is that we needed to find a way to mobilize those public resources provided to us for those other resources that had already been invested. It didn’t make sense to us in such a small, relatively small community, and where there’s already been this huge investment to make sure that, we’ve got all these great research capacity, all this great research capacity in universities, we should really find a way to force multiply that, right? Like, to make good use of that.
Ben Reinhardt 16:22
I’d love to understand, like, what was your pitch to the government to do this? Because, like, it’s very unique. And then two, when you call them, like, Focused Research Investments, what does that mean?
Stephan Leslie 16:37
We were set up with the explicit instructions to use research to create outcomes and opportunities. So, it was organized around certain key provincial priorities, what are sort of the urgent needs of this province? But this recognition that research, if it is carefully identified and managed and then integrated at the kind of transition out of the research side into the application side that you need to find a mechanism that is going to be different than simply, here’s a good idea, we’re going to issue a grant, and just by virtue the fact that you are working in an important area, we’re just going to assume or hope that the value will come back to those who are kind of ultimately footing the bill. And the other kind of in the final element is, I really mean it when we call it an investment, right? Like lots of things in government world are, which would otherwise, in another era be called, you know, expenses or costs, or whatever it might be. And the word investment has been sort of taken over, as government always invests in something it doesn’t spend. But in this particular case, what we want to do is consistent with the idea of what an investment is, that we want to see the value tomorrow, whenever that tomorrow is to be greater than the cost adjusted for risk and the time value of money that we’re going to put in now. And so, it kind of forces us, and those who are kind of willing to come on to this bumpy ride with us, to be able to articulate what does that value proposition at the end look like? You know, what outcome can we conceive of contributing to that matters to society? It isn’t, and you know, we’re not just in technology, we’re in a whole host of different areas, right? But we need to be able to convincingly articulate what that value is, and that there is a plausible pathway that has effectively managed the risks, all those different potential reasons why you could get thrown off it, such that there’s a likely chance that you’re going to reach that outcome.
Ben Reinhardt 18:52
Being able to define that value and sort of chart the path there, at what point in an FRI do you see that coming, in the sense that, like, if you could do that from day one, there’s not as much of a market failure, yeah. So, like, how do you think about that? If we could say, like, okay, this is, like, there’s a clear path for this thing, and if we did it, it would be awesome. Then it’s like, you can, sort of, like, there are a lot of mechanisms for, like, pulling that from the future.
Stefan Leslie 19:22
Yeah, so, the way I look at it is you cannot expect that to come together before you launch, before you get into it. And if you could, there’s probably another mechanism that’s frankly, a little easier or a little more straightforward that you could pursue. Part of what marks this territory that we are in, and you are in, and various others working, is that this stuff needs to be adaptive and built along the way. That, in my view, is not an excuse to fail to think about it at the outset, but it’s a recognition that what matters more at this stage are two things. The first is this really clear understanding of what that outcome at the end can plausibly be, right? And for us, for FRI, we just to be clear on kind of the scale that we’re talking about, we’re looking to choose between two and three as the initial kind of the launch cohort, right? Two or three of these teams and that each will be provided with between five and 20 million dollars and five to seven years. And that within that time frame, they have to be able to articulate, by dint of the effort, the research effort that they’re going to put in over that time frame, what do we now see at the end point? So, they need to be able to answer, you know, to what end is this investment going to be made? What is its purpose? What is the end point look like? And why is this a priority? Like, why this thing? And that final element is important in kind of two different dimensions. It’s both within the field. Why is that the bottleneck, or the impeding factor, or the governor on the engine that’s keeping it unnecessarily constrained Why is this the thing that needs to happen in order to unlock other value, but also, how is it that this is really the most important aspect or most important challenge to go after, amongst all the other challenges that we have in front of us? Like, there’s a lot of stuff that we can work on, a lot of risks, that we’re trying to manage, a lot of value that we’re trying to achieve. Why this? Like, who is really worried about this? Who is your, who’s supposed to benefit from this? And so, to get people to work through what those questions ought to look like at the outset, and then, as we then put together, and as you call them, Coordinated Research Programs, is, I think, what you called them, so once those kind of evolve into a Coordinated Research Program, then developing a set of metrics that’s appropriate to the outcome that you’re looking for, such that you’re managing to the outcome, not managing to the metric. And I think, you know, you and I could probably have a whole other hour on the woes of metrics that become your de facto management objective, which I think we desperately need to avoid.
Ben Reinhardt 22:19
Yeah, you’re touching on the thing that I call fat ideas versus like thin ideas. In the sense of a fat idea is an idea that needs a lot of investment in order to even know whether it’s like worth pursuing, right? Like, as opposed to, like, a thin idea where you can, you know, do some napkin math, or spend, you know, six months and just sort of like know whether it’s even worth pursuing or not. Whereas a fat idea, you actually do need to invest these, like, millions of dollars in order to even know whether it’s a good idea, and, like, what those metrics should be. And I feel like the these fat ideas are the market failure, right? So, like, when it’s a thin idea, like, that’s where those sort of like pull mechanisms from the future come from, whether it’s venture capital or just government investment. Eventually, you do want to have that value proposition and the pathway there, but like, the whole point is that you actually do need to invest a lot of time and a lot of money to even get to that point, and doing that work is where the market failure is, because people will look at it be like, well, like, what you’re not doing the work to actually do the thing right now. You’re doing the work to like chart out the path to the thing. But often, that’s just what is necessary.
Stefan Leslie 23:47
Do you think, having worked in this area for a few years and have stood up a couple of these attempts, what is the organizational structure that fits best? And I don’t mean, do you need to set up a brand new institution, because I think it can be, our hypothesis is that you can use existing institutions, but maybe selecting for certain types of ideas and people who choose to work in a certain way, but is that, do you think that will bear out, or are those institutional models that even though they seem like what has always been, are really a relatively new phenomenon in the full course of history. You know that kind of a post war, post Second World War model, these have now become kind of developed in a certain area that makes it hard for them to make this transition. So do we need, do we need to think about this problem differently from kind of an organizational way?
Ben Reinhardt 24:48
Like all good answers, I think it depends, in the sense that working with and coordinating existing institutions is to some extent, like the ARPA model, right? And that has had really good results. One of the extraordinary things about DARPA is like how consistently it has had good results from the 1970s all the way through now. And so that’s certainly a proof point that that is possible, right? That coordinating existing organizations is possible. The question that I have, actually maybe, is like whether it is efficient, and what constraints it puts on you, in the sense that people working at all of those institutions have their own incentives, academics have their incentives to publish and graduate grad students, and then startups have their incentives to get out a product and do all that work and everything in between. This is going to sound like gross or Machiavellian, but like, everybody has their price. And so, you know, it’s like, there is some amount of money at which everybody will shift their incentives, right? You often start up enough money and they will switch what they’re doing from the product that they’re getting out to whatever project you want them to do. That is the nature of the world. I think the question is, like, how expensive is that? And also, just like, how much wasted time and effort is there trying to do that, as opposed to standing up a different organization, you know, hiring people directly, what have you. My sort of more radical take is that I’ve actually sort of shifted more towards the latter, in the sense that, like, I think that is very hard to shift people’s incentives. But like, it depends on what specific sort of project we’re talking about, like, what the actual work needs to be. This is where I go back to this, like, pre-commercial technology development. I think that that particular set of work, like, actually, like building prototype systems, iterating on them, before it’s a product. I think is very hard to do in either academia or startups, but then other classes of work in this big gap that we’re talking about, I think probably are more well suited to academia or startups.
Stefan Leslie 27:13
The opportunity we opened was open to everyone, right, like there was certainly a very strong incentive for university based researchers to apply, but it was available to everyone else. Now, the majority did come in from universities, but we also have, so the stage we are in this process is we opened up an expression of interest, which is relatively short application, from which we then selected nine teams to go forward to develop a full proposal, and that’s the stage that we’re in right now. So we’re taping here at the end of June. They have until the end of July to develop this full proposal, right and from which we will choose, as I said before, two to three and the sorts of teams who came forward to propose tackling the sorts of projects or programs probably suited the kind of system that we’ve just been talking about, right? That it could fit within the academic or not exclusively academic, but kind of the stereotypical academic model. Those were the sorts of problems that emerged, and then the challenge that will come is, then to systematically work through all the other elements that do represent a different way of working from a standard, and I don’t even want to say standard academic model, but a standard kind of project based research system model, right where you don’t really have that, it may be multidisciplinary, but you don’t have this true Teach and Learn model between the different component parts and that’s one of the challenges in the academic model is, of course, they’re teaching and they’ve got a variety of other research efforts, and there’s a big institution, lots of responsibilities into their areas. And what we’re asking, and what we’re kind of selecting for is who’s coming up and saying, I found my life’s work for the next five to seven years, right? Like, and I don’t think putting money, as Machiavellian as you put it, it’s, for me, a marker to say this is really important. Like, if we are going to provide you, your team, your group, your set of researchers and your partners with this kind of level of funding with flexibility and all the rest of it, then we’re serious in wanting to achieve that outcome, right? And so, then we have to work with them to figure out how to make that happen. And I think this, the space that we’re in is underdeveloped for an experimental method itself, right? Like, there’s all sorts of things that we are experimenting with, including, how do you work with these teams? And in the process of developing these nine expressions of interest into nine full proposals, from which we’ll have to select only a handful, like we’ve got a almost full time person working with those teams to kind of fully elaborate their ideas and work through the governance challenges, and how are you going to manage this, and how you’re going to work with your partners, and how do you kind of measure impact? And all these sorts of questions that itself has become kind of a shared challenge, even though we’re in a kind of a more traditional nomenclature, we are the funder, because the cheque is going to cut from us to them, but we want to work with them to figure out how can we best develop this. That works in this instance. It’s not necessarily transferable to every other environment or every other problem.
Ben Reinhardt 30:59
For like, the different FRIs, do you like, do you have a sense of, like, some kind of leader, or is it really, like a group of peer organizations that will sort of, like, go forward?
Stefan Leslie 31:15
These are problems that are challenging and big enough that they’re going to need a team, but I think the reality of how these things actually work well is that team does need to have leadership, right, and that that doesn’t necessarily mean there is an individual PI to rule them all who kind of calls the shots, but there has to be a functioning management system embedded within that research team that allows decisions to get made, and choices sometimes what may be hard choices about how best to proceed. So yeah, we’re going to be, we have to, like, kind of figure out how that’s going to work.
Ben Reinhardt 31:56
Yeah, I mean, look, honestly, I’m intrigued at how you can get that to happen without like, one person in charge. Like, my bias is that, like you kind of just, like that that needs some kind of program manager, CEO type person. So, I’ll be very interested to see other structures that can actually do that, well. Make those hard decisions.
Stefan Leslie 32:18
And I think that just because you mentioned CEO or I think there’s actually two major disciplines that have to work in concert here. There’s kind of scientific direction, or research choices, scientific choices. And then there’s the more management, operational choices, making sure that the system is working properly. But I think for these things to function well, they need to have a model that understands that there’s got to be a decision structure around scientific choices and a decision structure around how you actually manage.
Ben Reinhardt 32:57
How are you thinking about logging what you’re doing and like, are you going to, like, publish, like, lessons learned? How are you gonna get what you’ve learned out into the world?
Stephan Leslie 33:06
Yeah, as we’re in the middle of it, the majority of our focus is on every day there’s something that comes up that we didn’t really think of, that we kind of have to figure out how to move forward on. We are doing what we can to kind of capture those key decision points. And of course, even though we only launched a few months ago, I’ve been thinking about this for some time, and kind of been putting this together carefully. And therefore, we’ll be looking for certain things. And then there are other kind of more concrete elements, like we want to make sure that in that time between when the nine teams submit their final proposals, that then we’ll have to review and work through and all the rest of it, and ultimately choose, between that point and the time we actually say we’re picking you, you and you, or you and you. We want to have someone sit with them, kind of like an exit interview on for an employee like and work with them on how did this work for you? Like, did you understand what they were getting at? Did this make sense to you? Did you feel like this was a worthwhile investment of your time, regardless of whether you’re successful or not? That’s why it has to be done at that point, so that we kind of harvest that. Because there are definitely things that we did not do as well as we could had we known now what we did when we started the process right? And so if we have the chance to do a round two, we want to make sure we learn from round one. Then the second part of your question, or the second kind of important element to your question, is for this really to matter more than just how we happen to galvanize or not, part of the research community in Nova Scotia is we want to be able to both teach and learn from others who are working in this area, and the reality of that means having, you know, 100 conversations with people like you and who are in the space, but also to write it down and to get that work out into a variety of different domains targeted at different aspects of the challenge, you know. So, there may be a somewhat more detailed, somewhat almost academic, you know, we are doing a meta science or a macro science experiment here the this was the kind of the hypothesis. This is how we tested it. This is what we learned discussion. And then there needs to be, I think, alongside that, a more kind of user friendly or more broadly available understanding of that we tried something here, and of course, it didn’t all didn’t work out perfectly, but we tried, and this is what we think is worth taking from that. And so if you’re of a mind, no matter where you are and whether you’re part of the kind of professional research community, or you’re another funder, or you’re a foundation, and you’re looking for good ways to invest your money in issues that you care about, there’s some things here that you can take from or look at and say, well, that’s not quite how it works here, so we’re not going to choose that. We’re going to choose this instead. Like, we have, this would be consistent with this idea that we’re here to support research that not just solves an immediate challenge, but is more broadly applicable, you know, other communities, other areas, other issues are going to benefit, or could use it. Similarly, what we are doing here needs to have an ambition that’s broader and that takes a distribution method.
Ben Reinhardt 36:31
Yeah, the thing that we still need to learn is how best to do that. Yeah, we’re sort of like building the airplane on the way down. Like, not only how do we do the thing, but how do we communicate the thing so that other people know how to do the thing.
Stefan Leslie 36:46
Right, and one thing I’m interested in the process, or the kind of the approach that you take, is that you’ve got a more, I’m going to get kind of the names wrong, but you kind of have a three stage process, right? Because we kind of just went in boots and all right, like we, this was, you know, done pretty fast, and sure we’re working with them, but we’re going straight to pull together big projects, people, or a big, comprehensive research programs. So maybe something we’ll learn is there could be another method to pull that off.
Ben Reinhardt 37:18
Yeah, well, I mean, so I would describe our process as having four steps, in the sense of like, step one is like road mapping, in the sense of like, saying what needs to happen to get this idea to a point where it can get out into the world? What are the biggest risks? What are sort of like, the different pathways? Step two would be derisking like, so addressing those specific biggest risks. The third step is like, actually building the technology, right? And then the fourth step is getting out into the world. The caveat, though, is like, to some extent, perhaps this like step wise process is enforced by the discipline of not having a huge amount of money. So, like, we have the money to, like, do step one and maybe a little bit of step two, and then we need to use that, like, the evidence from those two steps to raise money for steps three and four, right? So, to some extent, our process is bred by constraints, and maybe it is much better just like, just do the thing.
Stefan Leslie 38:21
But there’s a certain pragmatism to that, right? Because presumably what you’re building in step one and step two, by doing it in that measured fashion, is going to pay dividends in a more efficient step three.
Ben Reinhardt 38:32
That is the hope. That is the story I tell myself. And it would be like, I mean, the thing that I don’t know the answer to is like, you know, we do our thing, you do your thing. How would we compare? Like, how would we know? Imagine that we’re both successful. We both like, do awesome stuff. You know, 10 years from now, we sit down and we’re like, which way was better? I don’t have a good sense of like, how to know that?
Stefan Leslie 38:59
Yeah, that’s going to be, have to be a whole other episode, other conversation. That’s a, really important one, because this is such a long term effort, right? Like by, almost by definition, you’re not working on things that would have that really immediate return. Even our efforts, which we’ve got the funds to be able to launch a couple of these things, they have that time frame of five to seven years. Achieving those outcomes aren’t just an output of a research process that you know, they’ve got to go into the world. And so there’s a whole series of other things that are going to have to happen.
Ben Reinhardt 39:36
We’re going to go do some stuff and see how it goes.
Stefan Leslie 39:40
And then we’re gonna check back and I’m gonna learn what you did better than us.
Ben Reinhardt 39:43
And I’m gonna learn what you did better than us.
Stefan Leslie 39:46
That’s good way to end it right there.
Ben Reinhardt 39:48
Alright.
Stefan Leslie 39:49
Great to see you, Ben.
Ben Reinhardt 39:50
Great to see you.
Stefan Leslie 39:53
While Speculative Technologies and Research Nova Scotia are structured differently and have different purposes, they are two examples of organizations passionate about making a difference and believe that uncertainty on the pathway towards specific outcomes is okay and perhaps necessary. With focused, coordinated teams and projects and clear roadmaps to the outcomes, these less traditional research models can have a significant return on investment more broadly. If you’ve enjoyed this episode, head over to Ben’s podcast, Idea Machines, where he has conversations with experts in different innovation systems. Thank you for listening. Check out some of our other episodes, like the two-part episode with Melissa Flagg, Former U.S. Deputy Assistant Secretary of Defense for Research, where we discuss Gaps and Opportunities in the Current Research System and Addressing the Gaps: Focused Research Investments.
Welcome to the Beyond Research Podcast and the Idea Machines Podcast. I’m Stefan Leslie, CEO of Research Nova Scotia, and Ben Reinhardt is the CEO of Speculative Technologies. Both Ben Reinhardt and I have our own podcast for our respective organizations. We’ve got Beyond Research. So, if you’ve heard some relatively neutral music, that’s the Canadian version. And then if you’re listening to the Idea Machines Podcast, that’s the more dramatic American music, that’s Ben’s. We discuss research funding organizations that are challenging the traditional status quo to fill gaps in the system and support work that is uncertain, but if true, will lead to significant shifts and tackle big societal problems. Our organizations lead two different initiatives that fit under this umbrella of coordinated research programs. We explore the similarities and differences between our programs, the structures of them and the key players, the risks and challenges as well as the strengths and the possibilities. Ben’s Speculative Technologies is a nonprofit industrial research lab focused on materials and manufacturing technologies that don’t have a home in other institutions. It finds scientists with deep technical expertise with a clear vision of big-if-true technologies that don’t fit with large companies and startups that focus on profit and growth because their work is uncertain and don’t fit in the academic system that tends to prioritize novelty and academic outputs over usefulness. SpecTech works with these scientists to figure out how to build those technologies and help them execute on that plan. Research Nova Scotia is also a nonprofit, but one funded by Nova Scotia to organize, coordinate and support the research in the province. Although we do lots of different things, we’ve launched Focused Research Investments, or FRI, to support research driven by and in service of society. We are selecting teams to drive this research, providing substantial, secure and flexible funding they need to realize ambitious projects and achieve societal outcomes. We’re recording this in June, so we’re right in the middle of the development process. Two organizations, but both working to find creative ways to fund really important research. The reason why I wanted to talk to you and have us on each other’s podcasts is I actually think our organizations are working in much the same space, and
Ben Reinhardt 02:42
Yes
Stefan Leslie 02:43
that space can be probably defined as occupying a set or interested in a set of questions that is neither covered by the kind of research activity that is just purely based on discovery, advancing the frontiers of human knowledge, a really important and interesting part of what makes us human, but nor are we really involved in that other end of that spectrum, which is kind of the direct application, where there’s an immediate market for something, but there’s that unoccupied, or less occupied, middle space where there’s really important outcomes that can be identified, but they haven’t necessarily been formulated as research questions that can then be can be brought to the research community. And so, this is the space of where you’re interested in how systems work, you know, platform technologies, or platform ideas that can be applied in a range of different areas, monitoring and observation, which doesn’t get picked up by other things. In this bucket or in this category, there’s all sorts of really important and interesting work, and lots of different organizations that are having little pieces of it. And I think SpecTech, or Speculative Technologies, is one of them, and Research Nova Scotia is another. And so, I’m going to start just by asking a question of, well, first of all, do you agree with the way I’ve laid out and what is your piece in that? Like, what does SpecTech do within that middle space?
Ben Reinhardt 04:10
Where I see Speculative Technologies as sitting within that is what I describe us as doing is like, I’m making air quotes for people who can’t see, I call it like pre-commercial technology research, which is not an official term. It is a term I made up. In particular, I see us as doing four major like, quote, unquote pieces of work where it’s like one identifying things. It’s even hard to, like, identify ideas that are in this space, right? These like big-if-true ideas that don’t have a home in other institutions, road mapping out what work needs to be done to sort of get them to a point where they can be part of sort of a more traditional institution, identifying the like the key risks to those technologies, and then actually like doing the work to address those key risks, build the technology and then get it out into the world. That’s sort of where I see us as sitting. Finding people who can do that, building teams around them, helping them work with other institutions. And then also, just like providing the right incentives to some extent of you’re not focused on publishing papers and discovering things as you would in academia, but you’re also not focused on maximizing profit and shareholder value as you would be at a startup or a large company.
Stefan Leslie 05:37
Maybe a common feature of this area is that there’s no market signal on quality.
Ben Reinhardt 05:45
Yes, yeah.
Stefan Leslie 05:47
For discovery research or the exploration side of things without any discernible, immediate purpose. The market, it’s a surrogate market, but the kind of the peer system, and there are all kinds of limitations and notable failures around the functioning of the peer review system, but nevertheless, it is in essence an attempt to ensure that the quality of ideas is advanced by an acceptance of the community as being more truthful or more, a better description or understanding of a natural phenomenon or social system. There’s a more obvious market function for the other end of that spectrum, because if you’re working in an R and D area, you either develop a product that the market is willing to buy, that it meets its quality expectations, or if it’s more kind of government driven, or that kind of immediate challenge driven, did you get to the moon or not? Is, you know, that’s something of a signal that you can take back about success or not. All of the stuff that we’re talking about, I don’t think, has an ability to receive an indicator along the way, or even at the end of whether you reached it, whether you achieved that goal. Because the goals may be diffuse. They’re hard to describe. They may accrue over the course of years to decades. So you know, we struggle with this for sure, on how you define what something, what problem you ought to take on, and what you should be looking for in success.
Ben Reinhardt 07:25
I had never really thought about the marketplace of ideas as a market signal. With some of the things that we’re doing, I think it’s like you can imagine knowing whether you did the thing, but it’s so unclear whether the work that you’re doing right now will get there, that nobody’s willing to, like a rational actor would not invest in it, whether it’s from the government side, saying like ah yes, like this will clearly get us to the moon. There’s too much uncertainty about whether the thing that you’re doing is directly connected to any sort of outcome that someone wants, whether it is a profit number or some other kind of goal.
Stefan Leslie 08:10
So, you describe the space as bigger than we perhaps commonly talk about it. This is the space of DARPA and its variants, ARPA E and ARPA H, Focused Research Organizations or FROs. It’s certainly the space of FRIs, which we’re doing, Focused Research Investments. It’s the space that you guys are in kind of foundation-based things like carbon to C, and there’s other sort of organizations that are doing this. And what I think is really interesting and important about these sorts of conversations is those of us who are up to our elbows, sleeves rolled up, trying to make stuff happen in this space, probably don’t spend enough time looking for what are the common elements in the problems, in how they’re defined and how they’re attacked or addressed? What kind of teams do you need? How do you need to find ways to effectively coordinate or manage them? What metrics do you set up? How do you monitor them and I know that you know Speculative Technologies is not just an organization or a not-for-profit, that has identified a handful of these areas where you think you can move the needle on something, but clearly you’ve identified a market gap in being able to identify what those problems are and finding people who have those characteristics. And so I think there’s a huge challenge to be able to convey what it is we’re trying to achieve, like, what problems do we think are well suited to programs set up like this? And when I say like this, I mean some form of active coordination, you know, like that you’ve chosen the right problem and there is a group of people who recognize that their purpose is to achieve, to solve, you know, to achieve something at the end. And that there is a need for them to find a way to hold themselves to account to that, but also all of their other participants in that grand activity, you know, other PIs or the researchers, they need to have a functioning interaction system to always be able to determine whether their collective effort is optimally arranged to move towards that end, right? And that there’s a functioning mechanism to take corrective action. And, you know, that’s a, I can’t imagine that all of us aren’t confronted by a similar set of challenges, right? And we may be doing one thing, you may do the other, but we need to figure that out if we’re going to make progress in that middle space.
Ben Reinhardt 10:41
I call the like umbrella of all of that space of like Coordinated Research Programs, just because it is these like large things, they require coordinating a whole bunch of people, whether that’s like within a single organization, across different organizations and I think to some extent the problem, almost by definition, is that there’s no, like, one sized fits all, step-by-step approach to all of these problems. And so like, to a large extent, you’re kind of making it up as you go. You have to, like, you have to make up the process of what you’re doing every time, and so like that, that’s what each of us is struggling to do, is to, like, make up a process, and that’s why it’s hard and to some extent, like, the space is defined by problems that, like, don’t already have an existing process, because if they did, they would fit well into an existing institution. We’re trying to, like, create this, like, meta process of like, how do you figure out what the process is?
Stefan Leslie 11:47
Yeah, and I think
Ben Reinhardt 11:48
This is very abstract, but that’s what’s fun about it.
Stefan Leslie 11:52
One major difference between how we’re going about and what you’re doing is that we are using taxpayer dollars, right? We are also an arm’s length not-for-profit organization, but we are set up by the province of Nova Scotia with legislation that’s where the majority of our funding flows from, and so we have, we’re accountable to ensure that we are spending that money wisely, right? And Spec Tech or Speculative Technologies, if I understand your funding model, you have some core funding around making sure the organization runs, but then as you find good people and good ideas, and can find these sorts of, you can kind of nucleate around a particular issue and the right people, then you need to find a way to fund that, right? Is that kind of the model?
Ben Reinhardt 12:44
Right now, yes. We have dreams of being able to have a large enough pool of money that we can just go and fund it internally without having to do that sales process for every program. But as it stands right now, yes, we do, which is tricky, because, almost by definition, these things are hard to justify. And in order to fund any specific program, you then need to find people and justify to them and be like, this is why we need to do this particular program. If I could interject, I assume that it is a riff on the Focused Research Organization concept. How would you describe that?
Stefan Leslie 13:25
Yeah, so, you’re absolutely right that Focused Research Investments are a riff on Focused Research Organizations and the white paper that that those guys did, the two authors did a couple of years ago, because they openly invited people to say, here’s an idea, here’s a concept, but make it your own. Try. Convergent said, you know, try what is going to work in your jurisdiction. And so, what makes FROs different from FRIs, so FROs being the kind of the core description of an idea that came out a few years ago in FRIs, which we’ve launched here, is that FROs are very much, as I understand it, an organization in and of itself that is a performer of research. So, you actually set up a new organization and attract all of the different people or kind of talent, some of it may be contracted, but there’s a nucleus at least of those who are going to perform. And critically, it exists for a defined period of time to accomplish its goal, and then it winds up. Now, it may continue on as a new not-for-profit, or may spin off for profit companies, whatever it is, but whatever those are kind of two clearly defined characteristics of an FRO, whereas an FRI, and the reason why we chose here to set it up a little differently is getting back to how we pulled this off in Nova Scotia is probably got a couple of major parts. The first is that we’re a bit of a mesocosm sized experiment in the research world, right? So, we’re big enough that we do have enough funds that we can flow to support that very costly endeavor that is research. But we’re also small enough that and small in size of us working in Research Nova Scotia, but also the research community is small enough that we can kind of engage meaningfully with that group to understand what their capacity might be, what the uptake might be on a series of issues, and that we had some confidence that people would respond. And so what the major difference is that as a publicly funded organization, working with other publicly funded organizations, like the universities, but also what we call here the health authorities, the deliverers of health care in this province, is that we needed to find a way to mobilize those public resources provided to us for those other resources that had already been invested. It didn’t make sense to us in such a small, relatively small community, and where there’s already been this huge investment to make sure that, we’ve got all these great research capacity, all this great research capacity in universities, we should really find a way to force multiply that, right? Like, to make good use of that.
Ben Reinhardt 16:22
I’d love to understand, like, what was your pitch to the government to do this? Because, like, it’s very unique. And then two, when you call them, like, Focused Research Investments, what does that mean?
Stephan Leslie 16:37
We were set up with the explicit instructions to use research to create outcomes and opportunities. So, it was organized around certain key provincial priorities, what are sort of the urgent needs of this province? But this recognition that research, if it is carefully identified and managed and then integrated at the kind of transition out of the research side into the application side that you need to find a mechanism that is going to be different than simply, here’s a good idea, we’re going to issue a grant, and just by virtue the fact that you are working in an important area, we’re just going to assume or hope that the value will come back to those who are kind of ultimately footing the bill. And the other kind of in the final element is, I really mean it when we call it an investment, right? Like lots of things in government world are, which would otherwise, in another era be called, you know, expenses or costs, or whatever it might be. And the word investment has been sort of taken over, as government always invests in something it doesn’t spend. But in this particular case, what we want to do is consistent with the idea of what an investment is, that we want to see the value tomorrow, whenever that tomorrow is to be greater than the cost adjusted for risk and the time value of money that we’re going to put in now. And so, it kind of forces us, and those who are kind of willing to come on to this bumpy ride with us, to be able to articulate what does that value proposition at the end look like? You know, what outcome can we conceive of contributing to that matters to society? It isn’t, and you know, we’re not just in technology, we’re in a whole host of different areas, right? But we need to be able to convincingly articulate what that value is, and that there is a plausible pathway that has effectively managed the risks, all those different potential reasons why you could get thrown off it, such that there’s a likely chance that you’re going to reach that outcome.
Ben Reinhardt 18:52
Being able to define that value and sort of chart the path there, at what point in an FRI do you see that coming, in the sense that, like, if you could do that from day one, there’s not as much of a market failure, yeah. So, like, how do you think about that? If we could say, like, okay, this is, like, there’s a clear path for this thing, and if we did it, it would be awesome. Then it’s like, you can, sort of, like, there are a lot of mechanisms for, like, pulling that from the future.
Stefan Leslie 19:22
Yeah, so, the way I look at it is you cannot expect that to come together before you launch, before you get into it. And if you could, there’s probably another mechanism that’s frankly, a little easier or a little more straightforward that you could pursue. Part of what marks this territory that we are in, and you are in, and various others working, is that this stuff needs to be adaptive and built along the way. That, in my view, is not an excuse to fail to think about it at the outset, but it’s a recognition that what matters more at this stage are two things. The first is this really clear understanding of what that outcome at the end can plausibly be, right? And for us, for FRI, we just to be clear on kind of the scale that we’re talking about, we’re looking to choose between two and three as the initial kind of the launch cohort, right? Two or three of these teams and that each will be provided with between five and 20 million dollars and five to seven years. And that within that time frame, they have to be able to articulate, by dint of the effort, the research effort that they’re going to put in over that time frame, what do we now see at the end point? So, they need to be able to answer, you know, to what end is this investment going to be made? What is its purpose? What is the end point look like? And why is this a priority? Like, why this thing? And that final element is important in kind of two different dimensions. It’s both within the field. Why is that the bottleneck, or the impeding factor, or the governor on the engine that’s keeping it unnecessarily constrained Why is this the thing that needs to happen in order to unlock other value, but also, how is it that this is really the most important aspect or most important challenge to go after, amongst all the other challenges that we have in front of us? Like, there’s a lot of stuff that we can work on, a lot of risks, that we’re trying to manage, a lot of value that we’re trying to achieve. Why this? Like, who is really worried about this? Who is your, who’s supposed to benefit from this? And so, to get people to work through what those questions ought to look like at the outset, and then, as we then put together, and as you call them, Coordinated Research Programs, is, I think, what you called them, so once those kind of evolve into a Coordinated Research Program, then developing a set of metrics that’s appropriate to the outcome that you’re looking for, such that you’re managing to the outcome, not managing to the metric. And I think, you know, you and I could probably have a whole other hour on the woes of metrics that become your de facto management objective, which I think we desperately need to avoid.
Ben Reinhardt 22:19
Yeah, you’re touching on the thing that I call fat ideas versus like thin ideas. In the sense of a fat idea is an idea that needs a lot of investment in order to even know whether it’s like worth pursuing, right? Like, as opposed to, like, a thin idea where you can, you know, do some napkin math, or spend, you know, six months and just sort of like know whether it’s even worth pursuing or not. Whereas a fat idea, you actually do need to invest these, like, millions of dollars in order to even know whether it’s a good idea, and, like, what those metrics should be. And I feel like the these fat ideas are the market failure, right? So, like, when it’s a thin idea, like, that’s where those sort of like pull mechanisms from the future come from, whether it’s venture capital or just government investment. Eventually, you do want to have that value proposition and the pathway there, but like, the whole point is that you actually do need to invest a lot of time and a lot of money to even get to that point, and doing that work is where the market failure is, because people will look at it be like, well, like, what you’re not doing the work to actually do the thing right now. You’re doing the work to like chart out the path to the thing. But often, that’s just what is necessary.
Stefan Leslie 23:47
Do you think, having worked in this area for a few years and have stood up a couple of these attempts, what is the organizational structure that fits best? And I don’t mean, do you need to set up a brand new institution, because I think it can be, our hypothesis is that you can use existing institutions, but maybe selecting for certain types of ideas and people who choose to work in a certain way, but is that, do you think that will bear out, or are those institutional models that even though they seem like what has always been, are really a relatively new phenomenon in the full course of history. You know that kind of a post war, post Second World War model, these have now become kind of developed in a certain area that makes it hard for them to make this transition. So do we need, do we need to think about this problem differently from kind of an organizational way?
Ben Reinhardt 24:48
Like all good answers, I think it depends, in the sense that working with and coordinating existing institutions is to some extent, like the ARPA model, right? And that has had really good results. One of the extraordinary things about DARPA is like how consistently it has had good results from the 1970s all the way through now. And so that’s certainly a proof point that that is possible, right? That coordinating existing organizations is possible. The question that I have, actually maybe, is like whether it is efficient, and what constraints it puts on you, in the sense that people working at all of those institutions have their own incentives, academics have their incentives to publish and graduate grad students, and then startups have their incentives to get out a product and do all that work and everything in between. This is going to sound like gross or Machiavellian, but like, everybody has their price. And so, you know, it’s like, there is some amount of money at which everybody will shift their incentives, right? You often start up enough money and they will switch what they’re doing from the product that they’re getting out to whatever project you want them to do. That is the nature of the world. I think the question is, like, how expensive is that? And also, just like, how much wasted time and effort is there trying to do that, as opposed to standing up a different organization, you know, hiring people directly, what have you. My sort of more radical take is that I’ve actually sort of shifted more towards the latter, in the sense that, like, I think that is very hard to shift people’s incentives. But like, it depends on what specific sort of project we’re talking about, like, what the actual work needs to be. This is where I go back to this, like, pre-commercial technology development. I think that that particular set of work, like, actually, like building prototype systems, iterating on them, before it’s a product. I think is very hard to do in either academia or startups, but then other classes of work in this big gap that we’re talking about, I think probably are more well suited to academia or startups.
Stefan Leslie 27:13
The opportunity we opened was open to everyone, right, like there was certainly a very strong incentive for university based researchers to apply, but it was available to everyone else. Now, the majority did come in from universities, but we also have, so the stage we are in this process is we opened up an expression of interest, which is relatively short application, from which we then selected nine teams to go forward to develop a full proposal, and that’s the stage that we’re in right now. So we’re taping here at the end of June. They have until the end of July to develop this full proposal, right and from which we will choose, as I said before, two to three and the sorts of teams who came forward to propose tackling the sorts of projects or programs probably suited the kind of system that we’ve just been talking about, right? That it could fit within the academic or not exclusively academic, but kind of the stereotypical academic model. Those were the sorts of problems that emerged, and then the challenge that will come is, then to systematically work through all the other elements that do represent a different way of working from a standard, and I don’t even want to say standard academic model, but a standard kind of project based research system model, right where you don’t really have that, it may be multidisciplinary, but you don’t have this true Teach and Learn model between the different component parts and that’s one of the challenges in the academic model is, of course, they’re teaching and they’ve got a variety of other research efforts, and there’s a big institution, lots of responsibilities into their areas. And what we’re asking, and what we’re kind of selecting for is who’s coming up and saying, I found my life’s work for the next five to seven years, right? Like, and I don’t think putting money, as Machiavellian as you put it, it’s, for me, a marker to say this is really important. Like, if we are going to provide you, your team, your group, your set of researchers and your partners with this kind of level of funding with flexibility and all the rest of it, then we’re serious in wanting to achieve that outcome, right? And so, then we have to work with them to figure out how to make that happen. And I think this, the space that we’re in is underdeveloped for an experimental method itself, right? Like, there’s all sorts of things that we are experimenting with, including, how do you work with these teams? And in the process of developing these nine expressions of interest into nine full proposals, from which we’ll have to select only a handful, like we’ve got a almost full time person working with those teams to kind of fully elaborate their ideas and work through the governance challenges, and how are you going to manage this, and how you’re going to work with your partners, and how do you kind of measure impact? And all these sorts of questions that itself has become kind of a shared challenge, even though we’re in a kind of a more traditional nomenclature, we are the funder, because the cheque is going to cut from us to them, but we want to work with them to figure out how can we best develop this. That works in this instance. It’s not necessarily transferable to every other environment or every other problem.
Ben Reinhardt 30:59
For like, the different FRIs, do you like, do you have a sense of, like, some kind of leader, or is it really, like a group of peer organizations that will sort of, like, go forward?
Stefan Leslie 31:15
These are problems that are challenging and big enough that they’re going to need a team, but I think the reality of how these things actually work well is that team does need to have leadership, right, and that that doesn’t necessarily mean there is an individual PI to rule them all who kind of calls the shots, but there has to be a functioning management system embedded within that research team that allows decisions to get made, and choices sometimes what may be hard choices about how best to proceed. So yeah, we’re going to be, we have to, like, kind of figure out how that’s going to work.
Ben Reinhardt 31:56
Yeah, I mean, look, honestly, I’m intrigued at how you can get that to happen without like, one person in charge. Like, my bias is that, like you kind of just, like that that needs some kind of program manager, CEO type person. So, I’ll be very interested to see other structures that can actually do that, well. Make those hard decisions.
Stefan Leslie 32:18
And I think that just because you mentioned CEO or I think there’s actually two major disciplines that have to work in concert here. There’s kind of scientific direction, or research choices, scientific choices. And then there’s the more management, operational choices, making sure that the system is working properly. But I think for these things to function well, they need to have a model that understands that there’s got to be a decision structure around scientific choices and a decision structure around how you actually manage.
Ben Reinhardt 32:57
How are you thinking about logging what you’re doing and like, are you going to, like, publish, like, lessons learned? How are you gonna get what you’ve learned out into the world?
Stephan Leslie 33:06
Yeah, as we’re in the middle of it, the majority of our focus is on every day there’s something that comes up that we didn’t really think of, that we kind of have to figure out how to move forward on. We are doing what we can to kind of capture those key decision points. And of course, even though we only launched a few months ago, I’ve been thinking about this for some time, and kind of been putting this together carefully. And therefore, we’ll be looking for certain things. And then there are other kind of more concrete elements, like we want to make sure that in that time between when the nine teams submit their final proposals, that then we’ll have to review and work through and all the rest of it, and ultimately choose, between that point and the time we actually say we’re picking you, you and you, or you and you. We want to have someone sit with them, kind of like an exit interview on for an employee like and work with them on how did this work for you? Like, did you understand what they were getting at? Did this make sense to you? Did you feel like this was a worthwhile investment of your time, regardless of whether you’re successful or not? That’s why it has to be done at that point, so that we kind of harvest that. Because there are definitely things that we did not do as well as we could had we known now what we did when we started the process right? And so if we have the chance to do a round two, we want to make sure we learn from round one. Then the second part of your question, or the second kind of important element to your question, is for this really to matter more than just how we happen to galvanize or not, part of the research community in Nova Scotia is we want to be able to both teach and learn from others who are working in this area, and the reality of that means having, you know, 100 conversations with people like you and who are in the space, but also to write it down and to get that work out into a variety of different domains targeted at different aspects of the challenge, you know. So, there may be a somewhat more detailed, somewhat almost academic, you know, we are doing a meta science or a macro science experiment here the this was the kind of the hypothesis. This is how we tested it. This is what we learned discussion. And then there needs to be, I think, alongside that, a more kind of user friendly or more broadly available understanding of that we tried something here, and of course, it didn’t all didn’t work out perfectly, but we tried, and this is what we think is worth taking from that. And so if you’re of a mind, no matter where you are and whether you’re part of the kind of professional research community, or you’re another funder, or you’re a foundation, and you’re looking for good ways to invest your money in issues that you care about, there’s some things here that you can take from or look at and say, well, that’s not quite how it works here, so we’re not going to choose that. We’re going to choose this instead. Like, we have, this would be consistent with this idea that we’re here to support research that not just solves an immediate challenge, but is more broadly applicable, you know, other communities, other areas, other issues are going to benefit, or could use it. Similarly, what we are doing here needs to have an ambition that’s broader and that takes a distribution method.
Ben Reinhardt 36:31
Yeah, the thing that we still need to learn is how best to do that. Yeah, we’re sort of like building the airplane on the way down. Like, not only how do we do the thing, but how do we communicate the thing so that other people know how to do the thing.
Stefan Leslie 36:46
Right, and one thing I’m interested in the process, or the kind of the approach that you take, is that you’ve got a more, I’m going to get kind of the names wrong, but you kind of have a three stage process, right? Because we kind of just went in boots and all right, like we, this was, you know, done pretty fast, and sure we’re working with them, but we’re going straight to pull together big projects, people, or a big, comprehensive research programs. So maybe something we’ll learn is there could be another method to pull that off.
Ben Reinhardt 37:18
Yeah, well, I mean, so I would describe our process as having four steps, in the sense of like, step one is like road mapping, in the sense of like, saying what needs to happen to get this idea to a point where it can get out into the world? What are the biggest risks? What are sort of like, the different pathways? Step two would be derisking like, so addressing those specific biggest risks. The third step is like, actually building the technology, right? And then the fourth step is getting out into the world. The caveat, though, is like, to some extent, perhaps this like step wise process is enforced by the discipline of not having a huge amount of money. So, like, we have the money to, like, do step one and maybe a little bit of step two, and then we need to use that, like, the evidence from those two steps to raise money for steps three and four, right? So, to some extent, our process is bred by constraints, and maybe it is much better just like, just do the thing.
Stefan Leslie 38:21
But there’s a certain pragmatism to that, right? Because presumably what you’re building in step one and step two, by doing it in that measured fashion, is going to pay dividends in a more efficient step three.
Ben Reinhardt 38:32
That is the hope. That is the story I tell myself. And it would be like, I mean, the thing that I don’t know the answer to is like, you know, we do our thing, you do your thing. How would we compare? Like, how would we know? Imagine that we’re both successful. We both like, do awesome stuff. You know, 10 years from now, we sit down and we’re like, which way was better? I don’t have a good sense of like, how to know that?
Stefan Leslie 38:59
Yeah, that’s going to be, have to be a whole other episode, other conversation. That’s a, really important one, because this is such a long term effort, right? Like by, almost by definition, you’re not working on things that would have that really immediate return. Even our efforts, which we’ve got the funds to be able to launch a couple of these things, they have that time frame of five to seven years. Achieving those outcomes aren’t just an output of a research process that you know, they’ve got to go into the world. And so there’s a whole series of other things that are going to have to happen.
Ben Reinhardt 39:36
We’re going to go do some stuff and see how it goes.
Stefan Leslie 39:40
And then we’re gonna check back and I’m gonna learn what you did better than us.
Ben Reinhardt 39:43
And I’m gonna learn what you did better than us.
Stefan Leslie 39:46
That’s good way to end it right there.
Ben Reinhardt 39:48
Alright.
Stefan Leslie 39:49
Great to see you, Ben.
Ben Reinhardt 39:50
Great to see you.
Stefan Leslie 39:53
While Speculative Technologies and Research Nova Scotia are structured differently and have different purposes, they are two examples of organizations passionate about making a difference and believe that uncertainty on the pathway towards specific outcomes is okay and perhaps necessary. With focused, coordinated teams and projects and clear roadmaps to the outcomes, these less traditional research models can have a significant return on investment more broadly. If you’ve enjoyed this episode, head over to Ben’s podcast, Idea Machines, where he has conversations with experts in different innovation systems. Thank you for listening. Check out some of our other episodes, like the two-part episode with Melissa Flagg, Former U.S. Deputy Assistant Secretary of Defense for Research, where we discuss Gaps and Opportunities in the Current Research System and Addressing the Gaps: Focused Research Investments.
