

How can science solve all of our problems?
Category: Society Published: September 25, 2013

Science can not solve all of our problems. While scientific understanding can help battle things like disease, hunger, and poverty when applied properly, it does not do so completely and automatically. Furthermore, there are many areas of life where science can have little impact. Let us look at some of the reasons why this is so.
First of all, there is a huge difference between knowing something and acting on it. Science is concerned with accumulating and understanding observations of the physical world. That understanding alone solves no problems. Individual people have to act on that understanding for it to help solve problems. For instance, science has found that regular exercise can lower your risk of heart disease . Knowing this fact is interesting, but it will do nothing for your personal heath unless you act on it and actually exercise. And that's the hard part. Reading an article about exercise is easy. Getting into an actual routine of regular exercise is harder. In this sense, science really solves no problems at all. Problems are only solved when people take the knowledge (or tool, or pill, or whatever) provided by science and use it. In fact, many of humanity's biggest problems are caused by lack of action, and not lack of knowledge.
Take world hunger, for example. There is currently enough food produced on the earth every year to comfortably feed every single person. The world produces about 700 trillion grams of rice each year. With seven billion people on the planet, 365 days in the year, and about 40 grams per typical serving of rice, there is enough rice on the planet to feed every single last person seven servings of rice every day. And this is just rice. Similar numbers hold up for wheat, corn, meat, etc. Science has done an amazing job in the last 50 years of making farms productive. And yet, millions of people in the world still suffer starvation. Why? Because of actions. If all it took was science to solve problems, no one would go hungry anymore because there is enough food. We could fill books with the analysis of human actions that cause world hunger if we wanted to, but let's just focus on a few factors to illustrate the point. A large portion of the world's food is simply wasted by lazy humans. People in affluent countries buy more food than they need, so that much of their food goes rotten and must be tossed before it is eaten. Or they pile more food on their plate than they could possibly eat and much of the food ends up in the trash. Another major factor is corrupt or incompetent governments who hoard food among a select few, poorly distribute food, or refuse to adopt modern agricultural methods. Tyrants sometimes even use forced hunger as a way to subdue the masses or punish opponents. Science can make an acre of farmland amazingly productive, but it can't force a dictator to give back the food he has stolen from his people.
Secondly, science can only tell us what exists and not what we should want as humans. Science can answer questions such as "is the average global temperature increasing?" but can never answer questions such as "what should humans do about global warming?" Such a question really depends on what humans want. Some humans want to be free to enjoy gas-guzzling trucks regardless of what long-term impacts this may have on the environment, while others want to force everyone to give up such freedoms in order to protect the environment. Settling who is "right" in such a debate is largely a matter of ethics, morality, and opinion; not science. If I am personally on the environmental side of the debate and am frustrated that countries can't pass more stringent environmental laws, my real problem is that too many people want something different (freedom) from what I want (environmental controls). Science can build cars that emit less pollution, but it cannot force people to drive those cars. It takes laws to force people to drive environmentally friendly cars, and laws are just the written wishes of the majority of the people (or of dictators).
Many of the "problems" that are discussed in the political sphere are not really problems at all in the scientific sense. They are simply a clash of human wants: one large faction wants one thing and the other faction wants something else. No one is really "right" in the scientific sense in such cases (although, fervent partisans are usually convinced they are always right and their opponents are always wrong). For instance, is it better to let the free market run a nation's healthcare system or should the government take over? The answer to this question really depends on how you define "better", which depends entirely on what you personally want. To people that want freedom above all else, "better" will mean letting the free market provide healthcare. To humans that want a uniform system that won't let people fall through the cracks, "better" may mean centralized medicine. The point is that neither side of the debate is "better" in a scientific sense, so science can never solve this problem. Science can save more lives through medical breakthroughs, and can even streamline the healthcare bureaucracy, but it can't find out if government-run or market-run healthcare is better, because "better" is so subjective. The same situation exists for many "problems" debated in the political sphere. For this reason, scientists do not make good political leaders. The role of political leaders is to ascertain and carry out the wants of the people, which science is fundamentally not equipped to do.
Lastly, many areas of life are simply too non-physical to be satisfactorily addressed by science. Love, hate, relationships, poetry, art, music, literature, and spirituality are all outside the realm of science. Any problems that arise in these areas cannot be completely solved by science.
Topics: healthcare , politics , science in politics , world hunger
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November 15, 2022
Episode 21: To Solve Societal Problems, Unite the Humanities With Science
By Kaye Husbands Fealing , Josh Trapani
How can music composition help students learn how to code? How can creative writing help medical practitioners improve care for their patients? Science and engineering have long been siloed from the humanities, arts, and social sciences, but uniting these disciplines could help leaders better understand and address problems like educational disparities, socioeconomic inequity, and decreasing national wellbeing.
On this episode, host Josh Trapani speaks to Kaye Husbands Fealing , dean of the Ivan Allen College of Liberal Arts at Georgia Tech, about her efforts to integrate humanities and social sciences with science and engineering. They also discuss her pivotal role in establishing the National Science Foundation’s Science of Science and Innovation Policy program, and why an integrative approach is crucial to solving societal problems.

- Read Kaye Husbands Fealing, Aubrey DeVeny Incorvaia, and Richard Utz’s Issues essay “ Humanizing Science and Engineering for the Twenty-First Century ” for our series “ The Next 75 Years of Science Policy ,” supported by the Kavli Foundation
- Visit Kaye Husbands Fealing’s webpage at Georgia Tech
- Read Julia Lane’s Issues piece “ A Vision for Democratizing Government Data ”
- Read National Science Board members Ellen Ochoa and Victor R. McCrary’s Issues essay “ Cultivating America’s STEM Talent Must Begin at Home ”
- Read John H. Marburger’s 2005 piece in Science “ Wanted: Better Benchmarks ”
- Look at the National Academies 2014 summary of the Science of Science and Innovation Policy (SciSIP) principal investigators’ conference
- View the webpage for the SciSIP program (renamed Science of Science: Discovery, Communication, and Impact) at the National Science Foundation
Josh Trapani: Welcome to The Ongoing Transformation , a podcast from Issues in Science and Technology . Issues is a quarterly journal published by the National Academies of Science, Engineering, and Medicine and Arizona State University. I’m Josh Trapani, senior editor at Issues . I’m truly excited to be joined by Kaye Husbands Fealing, who is something of a living legend in the science policy community. Kaye is the dean of the Ivan Allen College of Liberal Arts at Georgia Tech. She previously taught for 20 years at Williams College and served in several positions at the National Science Foundation, including playing a pivotal role in creating the Science of Science and Innovation Policy, or SciSIP, program. On this episode, I’ll talk with Kaye about her work at Georgia Tech on integrating science and technology with humanities, arts, and social sciences, referred to as HASS. We’ll also talk about her career, and of course, I cannot pass up the opportunity to get her insights on the science of science policy. Kaye, thank you so much for being here.
Kaye Husbands Fealing: Thank you, Josh. It’s really great to be here with you today.
Trapani: I’m really delighted to have a chance to speak with you, because even though our paths first crossed directly only recently, I’ve heard your name numerous times in virtually every position I’ve held in Washington, DC, over the last 17 years. And your work particularly on science and science policy, as well as on science and innovation indicators, looms large over my career and those of many people who work in science and technology policy. And I’d like to ask you about some of that work. But let’s start with the piece that you and co-authors, Aubrey DeVeny Incorvaia, and Richard Utz have just published in Issues . In the piece, you argue science and technology education must be better integrated with humanities and social sciences, and describe some of the work you’ve been doing to make this happen. One thing you mentioned that really struck me is that more than 75 years ago, Vannevar Bush, in Science, the Endless Frontier , warned against this separation. And we listened to Bush on so many things, but not on this. Why do you think this challenge has been so longstanding, and what is science missing by not doing it better?
Husbands Fealing: Great question, Josh. And I wanted to take that question in two parts. First, talk about the challenge that has been so longstanding that Aubrey and Richard and I have been working on, and then I’d like to turn it and talk a little bit about what’s missing or what we can do better. So along the lines of the challenges, the premise of our article is that creative possibilities that lie at the intersection of science, engineering, art, humanity, social sciences, that the investment has not been pulled together in those areas the way they could be for a terrific return. So Vannevar Bush wrote that to set up a program under which research in the natural sciences and medicine was expanded at the cost of the social sciences, humanities, and other studies that are so essential to national wellbeing, that to set up programs that way, we would be missing something.
He also said science cannot live by and unto itself. So I just want to expand on that a little bit, because that was really what drew me into thinking about writing about this issue regarding science policy. Richard is a humanist, and Aubrey is a terrific social scientist. So we wanted to combine those areas to really explore this idea of humanities, arts, and social sciences integrated with STEM, science, technology, engineering, and mathematics. So for example, if you think about, and you go back and look at science advisors, go back, let’s just not go back that far. Let’s just go back to Holdren and look at the priorities that were written by him for OSTP fiscal years 2010 to fiscal year 2017. Here is what you see. Calls out these priorities, needs of the poor, clean water and integrity of the oceans, healthy lives, clean energy future while protecting the environment, safe and secure America and weapon-free world, economic growth, and jobs. Added to that, in the same set of priorities, STEM education, high performance computing, advanced manufacturing, and neuroscience.
So you see the difference. Some are big topics, big global issues, where clearly HASS and STEM coming together can really address issues of the human condition. So go forward to Lander and Nelson. The most recent priority memo was written by Alondra Nelson. And there we see pandemic readiness, Cancer Moonshot, climate change, security, economic resilience, STEM education, but also innovation for equity, open science and community engaged R&D. So then you see that scale back to something that is a larger context where the humanities and social sciences and even the arts come together with STEM and R&D to try to move us forward as a country.
So my observation is that there could be an increasing laser focus on competitiveness, and there’s nothing wrong with that. But with that, you see the increased focus on very specific areas in science and engineering. But these big topics; needs of the poor, clean water, safety, security, economic growth jobs, those certainly do require this kinship between HASS and STEM.
So for me, that sort of disciplinary fragmentation is the challenge and something that we can actually try to work through better as a group of science agencies. So let me address the what is missing part. What is missing by not doing it better was your question. And as we wrote in the paper, STEM and HASS domains intersect in the challenges and threats that people face every day. So we’re trying to get back to those issues of the human condition where the humanistic lens is needed to elucidate problems, imagine solutions and craft interventions. And we also think of it as these lenses allow us to think not only downstream about communicating science and communicating to either senators, congressmen, the populists, international leaders. We’re not just talking about the communication part of it, but we’re thinking upstream about also trying better to have that understanding of what the problem is, the discovery process.
And we think that it is important to have this discovery, design, solutions and communication process integrated into this combination at the intersection of HASS and STEM. Now, let me say just one more thing, and that is, it sounds as though we’re saying that this is easy, it’s not. It sounds as though we’re saying without it that we’re failing. We’re not, we don’t want to give that impression. In fact, accolades for our scientific progress surely are very well founded. So we’re not saying that that’s not the case or that arts and humanities need the sciences to buttress them. We’re not saying that either. What we’re saying is that there is a possible adaptivity that can accelerate progress in STEM, in science, technology, engineering, mathematics, and also in the arts and humanities and social sciences if we could work together. And the other issue is that it’s also not easy because we have to develop a common lexicon. We have to develop trust across the sciences and the humanities to allow the benefits that we foresee to come about.
So we need a way of creating learning pathways, experimental pathways to see this happen, to see this take off. And I think it’s worth our attention to see how we could get about many of the discoveries and then solutions to issues that continue to plague us.
Trapani: Well, thank you so much for that great answer. That was really, really clear. And it just shows the importance of taking the holistic approach. The end of your answer actually teed up my next question perfectly, because I was wondering why it’s been so hard to develop and scale up integrative approaches to building these things together in education network. And also because you’ve been leading the way at Georgia Tech, what are some of the things that you and your colleagues have been doing to bridge the gaps?
Husbands Fealing: I want to answer your question by talking through a few things that we’re doing here at Tech and then really address this issue of the difficulties of developing these and also the scalability. So some examples of what we’re doing at Georgia Tech. For one, a two-semester junior capstone sequence where that is co-taught between computer science and technical writing faculty. So what’s interesting about this, this is an arrangement that not only sharpens students’ communication skills, but it also inspires them to situate their scientific work in a larger context. For example, by considering how it will be received in a field rife with gender or racial bias. And so having the writing experts and scholars working directly with folks in computing, and then that allows both to advance, right? Because, also these writing scholars are technical writers, which we all know we need at NSF or at the National Academies or places like that.
So having that flow between the two, HASS and STEM, STEM and HASS, that’s an example. There’s another example of EarSketch, which is now used by more than a million students worldwide. And EarSketch integrates coding education with music competition. So using music as a pathway to get the students to learn to code worldwide. And so it’s really fantastic here to see that interdisciplinarity between the College of Liberal Arts and the College of Design, putting together with college computing, and more than a million students worldwide are using something that’s in the arts music to learn to code. So it’s really important that students are trained to think across a range of disciplines to leverage their exposure to diverse methodologies, to better understand and tackle complex problems. So why is this so difficult, and how can it be scaled? I think the difficulty goes back to something I said a little earlier, which is, we do need to develop a common lexicon and we do need to develop a sense of trust across these disciplines.
Even if you’re working just within HASS, the social scientists, economists, sociologists, political scientists are not all coming from the same place and they now are working with computer engineers or working with biomedical engineers or working across different avenues. Another area of difficulty, which we can work on it, there are ways of dealing with this. How do you assess the return on investment to having this complex combination of humanities and science, or arts and engineering, how do you figure out what the return on investment is from those? And typically we’re looking at number of papers, number of patent’s, number of grants, how much are you funded in those grants? But those are not necessarily the ways in which we should be assessing the breakthroughs that come at this intersection. And there are ways of quantitatively but also qualitatively measuring those breakthroughs. And I will put on the table that one important product is this talent pool, amazing talent pool.
And it’s not just the first job that they get and then we measure, think about, well, how much did they earn. But it’s really five years, 10 years down the road, sometimes even longer, where you see the amazing results of resilience and agility of the students that are coming out of these programs.
The second part of your question here about scale up, I think that we miss opportunities by focusing only on the private sector in terms of the outputs of R&D and that there are many ways in which innovation benefits the nonprofit sector and the government sector. There is innovation in government administration and there are ways of using some of these outcomes and some of these products to really have innovation in sectors other than just the private sector. Although the private sector, obviously, industry is really one of the main recipients of our investments in R&D, and it should be. There’s no reason to argue that. But I’m just trying to say here that we could expand on that a little bit.
A second part is that, I’m an economist, so I have to say, when I think of scale, I think of economies of scale and economies of scope. And it’s one thing to say scale up the same, and it’s another thing to say, well, look for the different use cases, things that are combined, how can they be used in the environmental area, or in the health area, or in the security, all the things that we talked about at the beginning, including getting to zero poverty, things that are really primarily top of mind to the ordinary citizen. And so thinking of not only how these combinations can be used to advance science and also to advance the social sciences, the arts and humanities, but also what are those use cases? Those are the things that are salient, those are the things that sing. Those are the things that really make sense to the ordinary citizen, and therefore that support for these investments, I hope, can be better articulated when we’re able to do those types of combinations and actually do that kind of communication.
Trapani: Your background as an economist came through loud and clear in that answer, and I wanted to turn to that next. So beyond your distinguished academic career, you’ve also played important roles outside the academy, including some key ones in science policy. In particular, you played a seminal role in developing and leading the National Science Foundation’s Science of Science and Innovation policy program, as well as leading the Science of Science policy Interagency Task Group. Now, before I came to issues, I also served briefly as an NSF program director, and I can say based on my experience that most program directors don’t get to start new programs, lead interagency groups, and work directly with the director of the White House Office of Science and Technology Policy, or OSTP, as you did with Jack Marburger. So I’ve been curious to talk to you for a long time and to ask you if you could talk a bit about that time and how you first got involved, and what you and others who were working on it were hoping to achieve.
Husbands Fealing: Thank you. That was a great time. I got to NSF, National Science Foundation, in 2005, was a program director in the economics program, one of three program directors. In my 11 months, so forward fast to 2006, I was asked by David Lightfoot, he was an associate director of the Social Behavioral and Economic Sciences directory, and he said Jack Marburger gave a talk at AAAS in 2005 where he called out the social sciences and said, “You need to stand up and be really part of this process of trying to get the evidentiary basis for funding science,” and that we needed to stand up and take that responsibility to do so. David Lightfoot, Mark Weiss, Wanda Ward, they were all in SVE at the time, and they said, we have social, behavioral, and economic scientist, so behavioral sciences also are part of this.
And we also have an arm. At the time it was SRS, now it’s the National Center for Science and Engineering Statistics. So we also had this quantitative part of us as a directorate. So they said, well, what can you do to draft something that would give us the platform to start something called science metrics. That’s what they called it, science metrics. But yet they want the sociologists and the behavioral scientists and others to be part of it. So it couldn’t just be metrics. So we knew it had to be science of science, which was something that existed, which means basically, what are the frameworks, the models, the tools, the data sets that are needed to make good decisions on funding science, or to make good decisions on how teams should be assembled to do science and so on. That’s the scientific foundation for science. So Science of Science and Innovation policy made sense, because at the end of the day, we want to have the evidentiary basis for policymaking. And that’s precisely what Dr. Marburger said he wanted.
So by the fall of 2006, I had finished writing with a lot of input from a lot of folks that were, at the time, in 2006, at NSF and finished this prospectus and showed it to Dr. Marburger. Obviously, David Lightfoot did that, I was a program director and came back, and they said, it’s a go. So we wrote the solicitation that fall. We were on continuing resolution. February, the continuing resolution lifted in 2007. Solicitation went out by that summer. We ran the panel, funded a number of proposals, and we had our first wrap. So from the summer of 2006 to the summer of 2007, prospectus, solicitation, proposals came in, proposals vetted, funded. It was a quick clock. I won’t give you all the details, but here are the categories that we funded in the first round: human capital development and the collaborative enterprise related to its science, technology and innovation outcomes.
So we did a lot there, including some work on the US, Mexico and Brazil. Biomedical, nano, hydrology, it’s all that foundational work behind funding those types of sciences. Another was returns to international knowledge flows, and once, test case was biofuels. A third, creativity and innovation. This is really interesting. This came out of the behavioral sciences, cognitive models of scientific discovery and innovation. Chris Schunn from Pitt was doing work where he would observe how engineers did work in labs and what were the cognitive processes that were going on so that we can understand ingenuity. So not just the commercialization, but all the way back to the ingenuity and that process. We funded that, we funded that project. Another set of projects, knowledge production systems, and looking at big systems, risk and rewards, low carbon energy technologies and things like that. And the last category was science policy implications.
And at the end of the day, everyone always wanted to know. Not only did you find the evidence behind how to fund or arrange activities in science better, but how did it affect science policy? And I’d say that we had the foundations of that even in the first round in 2007 in the SciSIP program. Very pleased about that. Dr. Marburger was very pleased about that, and forward fast to when Julia Lane, she took over after I left as program director, Stephanie Shipp and Dr. Marburger, the four of us wrote the preface of a book and then had many collaborators give contributions to the Science of Science handbook. And we finished that, I think it was published in 2012, but it was fun working on that with Dr. Marburger. So that does a little bit of background on the Science of Science and Innovation policy. Dr. Marburger really did give the charge for this, but it was fun. And yes, program directors at NSF get to do a lot of other things. So it was good for us.
Trapani: Well, that’s really remarkable. Thanks for telling that story. I don’t know that I’d ever heard it quite so succinctly and concisely, the very early days. So I guess it’s been 10 years or more though since then and I was wondering from your perspective, how has the landscape for the Science of Science policy evolved since those days, and how far do you think we’ve come in meeting some of these challenges and what remains to be done?
Husbands Fealing: I think that the advances that have been made, we have better models, I think, and frameworks that integrate across economic sociology especially. I think the original setup of this program envisioned having more domain scientists working with the social scientists especially, and behavioral scientists, and I think we’re making advances there. We’ve made many advances on the data side. I think the part where we could do more, we could do more in the behavioral space. I don’t think that we pulled in as much in the Science at Science, now has been renamed Science of Science, the behavioral piece as we wanted to at the beginning. In the prospectus, there was a real emphasis on creating a community of practice, and that would not only be academics, but it would also be individuals who are in the variety of agencies. The Interagency Task Group had representatives from 17 agencies that were part of the NSTC in the subgroup on social, behavioral, and economic sciences.
And the idea was to try to get more of the agencies to take on this Science of Science approach, but it would need funding, it would need to be a priority, it would need leadership. So I think that that’s something that’s still ongoing. I think the biggest question we get often is, well, how has this affected policy. And I don’t think that we’ve done the work to show that mapping distinctly between the science and science and policy changes. It’s hard to do. But I think that that is something where we still have a way to go. And the last thing I would add, Kellina Craig Henderson is now the AD for Social Behavioral and Economic Sciences. She and I rotated to NSF the same year, 2005, and she’s been there for a long time. And back then she really was working hard and diligently on the science of broadening participation in STEM.
And it is something still that to this day we’re still thinking about and talking about it. Dr. Panchanathan, the current director of NSF, is very focused on this. The NSB is very focused on the missing millions. And they just even created a new program called GRANTED to get R-2s and other universities the infrastructure so that they can apply effectively to NSF and get the grants to perform science and engineering activities at their institutions. And so I think the Science of Science, or SciSIP, depending on what you want to term it, I think we have an area to contribute on the science of broadening participation. And this is the time, because this is something that Pancha’ is talking about all the time, National Science Board and others. And it is in the priorities, the innovation for equity, that is in the priorities from OSTP. So I think we have an opportunity to keep moving along this line of Science of Science, or Science of Science and Innovation policy, especially at this time.
Trapani: Well, while I was there, I briefly ran the Science of Science program. We put out a special call that we called BP Innovate, and it was about building an understanding of the science behind what leads people to enter entrepreneurial activities or to not, and the sort of incentives and disincentives that are there and how that varies across people’s race and gender and geographic background. And that was a time thing, but I think it’s something that they are planning to repeat. I’ll just add that you mentioned a lot of names and places that I know. And I would just mention that Julia Lane just had a piece in Issues in Science and Technology that lays out a vision for the evidence-based policy making act.
And one more Issues plug before I move on—you mentioned the National Science Board, and last year we had a piece by the chair and co-chair of the National Science Board, and it was partly focused on the need to broaden participation. So this is very much the conversation that’s going on today. My sense is that when it comes to this field, the Science of Science policy, or Science of Science, is multidisciplinary, as you described, led by the quantitative social sciences. But to get back to your piece, you called for more than just that. You wanted more multidisciplinary, including the humanities, to be built into science policy. And I wonder if you could speak a bit just to what that would look like and what benefits you think it would bring.
Husbands Fealing: I’d like to see, for example, use cases where we can actually see the advancement of science using these activities. And also, I’d love to be able to see, and this I got from talking to our executive vice president for research who read the article and he came back and said, but we also need more science in art. And so consider that. Consider that. I want the listeners to think about what that means. So the art in science, there’re ways of visualizing, there’s something called medical humanities. So there’re ways of using those activities within the arts and music to improve not only outcomes in medicine for individuals, but also hopefully to really get at the kernel of issues in an interesting way using maybe art or visualization techniques that come from the humanities, arts and social science side. But the other challenge here was also, well, what if someone that is using materials or different types of paint understood the chemical processes or the composition in a way that actually enhance the product in the art side.
So that’s the vision, it may be out there a bit. It’s off the beaten path, but one of the things we’re trying to do here at Georgia Tech is create an area called Art Square. Now, Art Square, on a continuum, on campus is on somewhat of the periphery, but they’re building Sciences Square not far away. So imagine if we could really collaborate across those. And we’re also not far from the new Lewis Center, so the DEI aspect or DEIA aspect of this could come into play as well. So it could be a fulcrum, it could be a hub, it could be an area where we can really see advances that we hadn’t thought about by doing this. And for me, it’s an experiment. It’s something that’s worth investing in. We are doing much of it here at Tech. And so I don’t want to make it sound as though we’re not doing this, but with so much more that we can do to see this type of integration.
Another area is that we want to be able to understand how this intersection of HASS and STEM will improve policy. So it goes back to your previous question about the Science of Science and Innovation policy, that foundational element behind policy. Well, could it be crisper, more nuanced, more connected to communities if it includes the humanities part of it? And the National Academies report branches from the same tree. That is something that is important for us to remember, is that this cleaving, this disproportionate investment over these many decades, we really have to give back to the fact that maybe that didn’t need to happen, or we can do something that corrects that split and see better integration and investment in that integration. So that’s the vision.
Trapani: This has been such a wide-ranging conversation. I really appreciate your time and your insights, but I have one more question before we go. I was wondering if you have any advice or perhaps lessons learned from your experience for younger people who are interested in or getting started with careers related to science and technology policy who want to have a positive impact?
Husbands Fealing: Sure. I like that question very much because I’ve been in the business, so to speak, for more than 33 years. So I’ve been a professor for a long time and students are a top priority and it’s really important for us to have some takeaways that students can dig into.
I have three things I want to put on the table. Broaden your networks. And we’re not just talking HASS and STEM now. We’re talking just the networks that students can really utilize, not just to get access or economic and social mobility, but also to find pathways and career pathways, and those networks will really allow that to happen. The second piece is the focus on humanities or social sciences. If you’re an engineer, it’s not a distraction. It’s actually an enhancement in your area of expertise in the sciences and engineering and computing. So I’d like to just put that on the table, that oftentimes you may be chided, that, “Well, why are you doing that? Just spend 10 more hours in the lab and it’ll be better.” I want to say no. There’s a lot of benefit from looking at and having these other lenses to really do the exploratory work.
So humanities or social sciences is not a distraction, it could really be additive. And the third thing I’d like to say, because I had to really think about as you asked the question, what else would I want to put here? And I have to say, right, I have a math degree and an econ degree, and I was not a writer. I was not a person that did a lot of writing. I crunched equations. I loved QED at the end, especially when I knew I was right. And when I was a math major, the task was to solve the proof in as few steps as possible. I love that. But I will tell you the good writing, great communication, telling the story, there’s nothing more salient than that to put all of that hard work into people’s minds so that they understand what you’re talking about.
It even is important if you want to be an entrepreneur, it’s important if you want to set policy, it’s important if you want to let other students understand what you’re working on in terms of these peer effects that I talked about before. So please write, figure that out. It’s not always that easy, but it’s so incredibly important.
Trapani: As an Issues editor, I’m going to transcribe the part of your answer about writing. We’re going to put it on our homepage and I’m probably going to put it on a t-shirt too and wear it everywhere. Thank you. Kaye, it’s been delightful to talk with you. Thank you so much for being here.
Husbands Fealing: Thank you. This was a pleasure.
Trapani: This has been a wonderful conversation. And thank you to our listeners for joining us. As Kaye notes in her piece, Yo-Yo Ma once said, “Culture turns the other into us.” Science and technology has for so long seen the humanities and arts as other, and it’s time we turn them into us.
To learn more about how we can achieve that, read Kaye Husbands Fealing, Aubrey DeVeny Incorvaia, and Richard Utz’s piece in Issues , entitled “ Humanizing Science and Engineering for the Twenty-First Century .” Find a link to this piece and the others we mentioned in our show notes. Subscribe to The Ongoing Transformation wherever you get your podcasts. You can email us at [email protected] with any comments or suggestions. Thanks to our podcast producer, Kimberly Quach, and audio engineer, Shannon Lynch. I’m Josh Trapani, senior editor of Issues in Science and Technology . See you next time.
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- Can Social Science Matter?
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Social Science and Contemporary Social Problems
Published in March of 1969, this essay by then SSRC president Henry Riecken grapples with many of the same issues raised by Prewitt and his interlocutors in “ Can Social Science Matter? ” The major upheavals of that historical moment are not discussed in any detail in Riecken’s essay, but they clearly influenced the timing and the content, as Riecken discusses how social science can contribute to addressing public problems, the differences between the social sciences and the natural sciences and engineering in this regard, and the limits to the ways in which social science can contribute given how it is organized and incentivized. Riecken concludes with an extremely prescient analysis of the ethical dimensions of certain kinds of social science work, specifically social experimentation and the collection and use of what we now call “big data.”
The social sciences, like the physical or biological sciences, are intellectual subjects, directed primarily toward understanding, rather than action. It would of course be a curious kind of “understanding” that had no implications for action, and this is perhaps especially true for the social sciences. Nevertheless, there is a difference between enlarging one’s understanding of human behavior and society on the one hand and trying to solve a social problem on the other. The social sciences are distinct from social problem solving, but each can contribute to the other.
During the last few years there has been a significant change in popular attitudes and expectations in the United States regarding social change and social problems. A renewed determination to ameliorate certain long-standing, as well as recently developed, ills of the society has arisen along with a sense of power and confidence in its ability to do so.
In looking for ways in which to implement this desire for self-control, for directed rather than accidental improvement, a good many leaders of society have begun to turn, increasingly expectant, to the social sciences. Some have asked what the social sciences can contribute to the venture. Others have assumed that these sciences have a great deal to contribute to a better society and that they need only to be force-fed (the recommended diet varies from prescriber to prescriber) in order to grow faster and to make their contribution larger.
The social sciences do have a contribution to make to social practice, but not so large a contribution as they will make if helped to develop properly. At this point in history, the magnitude of major social problems exceeds the capacity of social scientists to solve them.
Such expectations have been entertained before. In the latter part of the nineteenth century and the first decade or so of the twentieth, social scientists of the day offered advice to the progressive political and social movements of the times. As David Truman has pointed out, these political scientists and sociologists operated not only from a weak position in the political structure, but also with an almost total lack of theoretical sophistication, quite nonrigorous methods, and few facts about the systems on which they were advising. 1 David B. Truman, “The Social Sciences and Public Policy: Maturity Brings Problems of Relevance and Training,” Science , 160: 508-512, May 8, 1968. They were intellectually premature and too ready to claim relevance. Their efforts fell far short of expectations, both their own and expectations of those who, from outside the disciplines, had called upon them.
Social scientists had another try during the early years of the New Deal when economists especially, but sociologists and political scientists too, were invited into government and other institutions to develop programs, plans, and social devices for dealing with the Great Depression. The novel thinking of agricultural economists and the resultant development of institutions for what was then known as “farm relief” were considerably more successful than the efforts of the social reformers of the early 1900s had been.
One reason for the relatively greater success of the applied economics of the New Deal was that there had been developing in the United States a considerable sophistication in economics as a discipline, together with a good empirical base of data that had been accumulated over the prior decades. In comparison with today’s data base, that of the 1930s was poor and small; but it was a vast improvement over the virtual data vacuum of 1900. Another reason for the relative success was probably the degree of desperation that gripped the country and led to a willingness to try the somewhat radical measures that were proposed by economists; partly because people were willing to try the measures, they were successful. Still another opportunity for the social sciences came during World War II when psychologists and anthropologists especially made significant contributions to the prosecution of the war and the government of occupied territories.
Social scientists are currently being offered a fourth opportunity to display what they have to offer toward the solution of what is now a fairly well-standardized, if incomplete, list of problems: poverty, racial segregation and discrimination, urban decay and the strangulation of transportation, human and mechanical pollution of the environment, and a perceived increase in the incidence of crimes of violence. Will social scientists succeed better this time in living up to the expectations that face them? What can and should be done to make possible greater success?
There are several purely scientific difficulties in applying social science successfully to the solution of social problems. Limitations of space prevent their adequate discussion here. 2 These issues are taken up in the longer article in Social Science Information cited below. Their importance is such that they must at least be mentioned, however, and they require persistent scientific effort in order to improve the capacity of the social science disciplines to cope with social problems. There are three major scientific issues: so-called “Hawthorne effects” or changes in behavior which result from the fact that individuals are subjects in an experimental study; the inadequacies of existing data about social problems and individual behavior and the defects of indirect data; and finally the manipulability of social factors that are variables in social scientific analyses of problems. These are difficult scientific problems, but not impossible of solution. Furthermore, much headway can be made in applying social science without fully solving them.
Over the decades in the social sciences, the tendency has been to develop internal concerns, to define their own problems and not to accept, as their subject matter, the social problems of the contemporary and surrounding society. This tendency is attributable to forces intrinsic to the disciplines themselves, especially to conceptual redefinition of problems and to methodological or technical developments. A social scientist who undertakes to work on a practical problem, not as a wise man or a clever consultant, but as a scientist, quickly finds that the popular, or commonsense, statement of the problem is either incomplete or misleading; that “the” problem is really many problems, only some of which fall within the disciplinary or scientific scope; and that there are severe inadequacies in the methodological or technical equipment that he has for dealing with “the” practical problem. Sometimes the scientist examines the “real world” because some part of it has solved a problem and the scientist wants to know how the solution works. After he understands how it works he can sometimes improve upon the solution, but the basic movement of his thought is always away from the practical and toward abstract knowledge.
The social scientist gets driven back to more fundamental questions that bear less and less resemblance to the practical problem until they appear to be irrelevant; furthermore, some of the more fundamental questions raised in this way take on a life of their own and become genuinely dissociated from practical problems. They form, instead, the central conceptual or methodological core of the science as such. Thus, over a period of time, a social science can grow more abstract and become increasingly concerned with questions that confront it as an intellectual enterprise per se and that require solutions whether or not they bear upon the social problems of the day.
If these intrinsic intellectual forces were the only ones at work, a discipline would gradually lose all relevance. However, exogenous factors also have some influence. For example, some people become social scientists who have a genuine interest in solving social problems and retain it despite the professionalizing experiences of graduate study. Market forces are also effective, especially grants from both private foundations and government agencies to support applied social research.
The opportunity for a career in an applied field of social science is a market factor of importance. The very existence of professional economic consulting firms as private, nonacademic enterprises holds out the possibility of a career outside the academic world, and may tempt a young man who finds practical affairs more challenging than the intellectual world. The development of clinical psychology was greatly aided by the demands of the Veterans Administration directly after World War II for diagnostic and therapeutic help at its hospitals and clinics.
Another factor of importance is prestige. The social sciences are primarily academic enterprises, more so than either the biological or physical sciences, and the academic portion of the discipline is not only overwhelmingly larger than other sectors but also overpoweringly more prestigious. The physical and the biological sciences, on the other hand, have substantial nonacademic sectors that are intellectually and scientifically influential, as well as of great and evident practical importance.
The prestige which most social scientists attach to academic social science may or may not be justified but it is a fact. The low status of applied work is probably undeserved, but it too is a fact, and one that may discourage some first-rate scholars who are status conscious from entering early upon a career in applied social science. The origins of this low status lie partly in the earlier relative failures of social scientists to deal adequately and successfully with social problems. Even where applied social research has developed and has attracted competent people, it still has been applied research rather than what is called “development” (in the Research and Development sense) or “engineering.”
Most applied social research has been concentrated on the analysis of situations explaining or accounting for a given state of affairs; or the measurement of outcomes—and the degree of success of some action in reaching a stated objective. There has been less attention to preparing new means for taking action or recommending how a user should proceed in order to achieve success.
The production of recommendations for action goes beyond research and indeed beyond science, into what is properly termed “development” rather than “research,” or “engineering” rather than “science.” The distinction is more than verbal—it is a whole complex: a state of mind, institutional auspices, cross-disciplinary relations, communication with nonscientists, and employment of nonscientific resources and nonscientific skills.
“Development” or “engineering” calls primarily for an inventive and constructive attitude, more than an analytic and differentiating one. The scientist is usually trying to unscramble a given complex situation to see how its components work. An engineer is usually trying to put together a device or a process to achieve a given purpose. The scientific process is analytic; the engineering process is synthetic. The scientist’s creativity is conceptual, in producing imaginative new principles or connections between concepts. An engineer’s creativity is in tangible inventions of things or processes that have a causative or productive relationship to a desired end.
Except in very limited and spotty areas, social development or social engineering does not exist. Examples of social engineering can be found in economics in the development of fiscal and monetary policies, and in psychology in new forms of psychotherapy (especially behavior therapy), programmed instruction, human relations training, the training of managers, and the social organization of production units in firms.
Organizational influences
The development of an applied social science or a social engineering may proceed faster through professional schools (especially business and medicine) than through disciplinary departments in universities. The academically based research and teaching unit in the social sciences is affected by forces that hinder this sort of development. Some are organizational, some scientific; some derive from the institutional arrangements for the conduct of research in the social sciences. Most research is done in academic settings by part-time or short-term workers, i.e., by professors and graduate students.
The former have teaching and administrative responsibilities that take up part of their time, the latter have a primary short-term interest in completing a dissertation and getting on in the world. The former work part time on a research problem, the latter leave it for other places or other problems after a relatively short time. Thus, many social science research problems are “thesis-sized” because they are selected for that reason.
This tendency is abetted by the current system of project grants which tends to emphasize short-term investigation of discrete problems rather than long-term, exploratory and persistent pursuit of a problem, a phenomenon, or a method. The absence of a tradition of long-term research careers on a full-time basis, the inflexibility of space that makes it hard to expand and contract the size of a long-term project as such changes become necessary, the varying requirements for skilled labor in interviewing and data processing (currently eased by computer applications), all contribute to sporadic interest, easy discouragement, and lack of persistence.
On the other hand, the real basic advances in social science seem more likely to occur in settings—such as disciplinary departments—that are relatively free of the pressures to devise immediate solutions, to work with client systems, and to attend to the range of extra-scientific considerations that are involved in solving social problems. A convincing argument can be made that the most pressing needs of social science are methodological and that the greatest opportunities for strengthening the social sciences lie in improving methods of research and developing more powerful theories. Indeed, a considerable amount of the advance in social science that has taken place in the last few decades has come about through basic research of this sort, conducted in disciplinary departments.
Thus conventional disciplinary departments and institutes that are genuinely embedded in universities can be counted on to provide the social scientific underpinning for solving social problems, but should not be counted on for the actual problem-oriented work itself.
The latter task should be the responsibility of institutions that have less formidable intellectual responsibilities, and are free of the primary educational obligation. Furthermore, applied social research institutions ought to have some closer firsthand contact with social problems and the agencies that can take effective action on the problems.
Requirements for social science contributions to social problems
Where then should the responsibility for social science contributions to the solution of social problems be located? The phrasing of the question suggests part of the answer for, in the first place, a social problem rarely bears a one-to-one correspondence to social science, and almost never bears such a correspondence to any single social science discipline. All social problems are interdisciplinary in the sense that they require, for adequate solution, the efforts of more than one kind of scientist and usually of more than just scientists or engineers. Hence, the first requirement of an applied social research agency is that its professional personnel be drawn from a variety of disciplines (both within and outside the social sciences).
A second requirement, much harder to achieve, is that the assembled members of these disciplines be able to work together productively and effectively. This requirement demands first-rate scholars, not only curious about the problem at hand but also inquisitive about each other’s fields and capable of learning from each other. Willingness to listen and curiosity are more important than anything else, since transfer of training among social scientists is entirely possible, and it may even help in the solution of, say, a psychological problem if an anthropologist without any particular training in psychology gets to thinking about it.
A third requirement is that the team has full opportunity to perform its functions of engineering and development. This requires certain kinds of facilities: buildings and computers—especially adequate “software” to go with the computing machinery and all the programming and other technical help that can be provided. One of the most useful techniques in social engineering is the simulation of the social processes that are believed to underlie the social problem. In many cases these simulations will have to substitute for experimentation because of the size or other intractable features of the problem.
A fourth requirement is long-term funding commensurate with the size of the social problem. It is a commonplace of American politics that social problems must be solved quickly. We are abjured to waste no more time in eliminating segregation, discrimination, poverty, crime, and unemployment. But while sense of crisis may impel movement, a lot of it is waste motion. We are too impetuous and not persistent enough in trying to solve social problems. Problems need sustained study, trials of many different kinds of solution rather than one-shot panaceas arranged overnight by agencies that are funded on an annual basis and publicly criticized for lack of instant success.
Problems in utilization of social science
One of the most interesting points about social science contributions to the solution of social problems is that the process of introducing the changes necessary to solve the problem is in itself a problem in social science.
Before introducing changes into a quasi-stationary situation, the decision maker must consider a number of factors that affect the chances of success. First, he must consider the acceptability of his proposals to all the people involved in the situation; and the harm, damage, or deprivation that some of them may experience. Next, he must assess the effectiveness of the methods he expects to use to attract the attention and arouse willingness to explore, and the capacity he has to teach people new ways of behaving. Finally, he must try to adjust the incentive and inhibitory factors in the situation so as to stabilize the new equilibrium and maintain the change he aims to bring about. Almost all of these problems exist in one form or another in utilization of the products of biological and physical sciences, too. But these sciences have not only an engineering or developmental branch that puts their ideas into usable form, but also a marketing mechanism—a set of activities and relationships that handles these problems or is so constituted that it can afford to ignore some of them.
On the whole, the marketing mechanisms for social inventions and devices do not parallel those for physical and biological technology. There are at least three reasons for this. In the first place, until recently, there have been few social inventions or devices that could not be marketed or disseminated either through existing political mechanisms in the public sector, or through publication, or through the establishment of a professional group such as clinical psychologists. It may be that marketing mechanisms will spring up in response to the appearance of new items to be marketed.
For example, there are profit-making companies which now seem to be interested in developing and selling, as well as installing, new curricular materials and instructional procedures in the schools; and industrial firms have contracted to operate schemes for the alleviation of poverty—usually through retraining of the unskilled or underskilled. This trend has yet to be evaluated, but it could alter profoundly the nature of the process of social change. Secondly, there is difficulty in protecting property rights in intangible social technology. If the product is an idea, an attitude, a routine, it is hard to copyright and generally impossible to patent. The absence of protection of exclusive rights makes the prospect of investing in a marketing organization less attractive to an entrepreneur. Thirdly, much of the technological product of the social sciences has to do with the public rather than with the private sector of the economy, and is valuable for its distributive effect on the total society rather than for its enhancement of the quality of life of one individual at a time. Add to this the fact that a good many social inventions cannot be assigned a unit value, and one can see that the marketing mechanism must be the state in some form, rather than private enterprise.
Public policy issues in the application of social science
Some questions of public policy are raised by research and development activities in the social sciences. For example, what should be the public policy toward deliberate social experimentation, especially toward concealed experiments, in which the subjects are not aware that they are involved in an experiment? There are scientific reasons for concealment but the public policy problem is whether the probable gains from conducting such an experiment outweigh the ethical undesirability of acting in a less than open fashion. There is something repugnant about concealment of purpose, even when the motives for it are disinterested and no one is harmed. There is something upsetting about discovering that what one thought was a real and natural flow of events was instead a carefully contrived sequence of moves deliberately planned to accomplish a preconceived purpose.
The benefits to the general public welfare have to be balanced against these possible disadvantages. If experimental purpose must be concealed in order to obtain valid knowledge that will lead to improved social policies at a relatively low cost, not only in money but in mistakes and discomforts visited upon citizens, then the undesirable features of a concealed experiment may be outweighed by its advantages. The judgment cannot be made a priori for all cases; it must depend in each instance on the estimated costs and the anticipated benefits. Perhaps the more significant public policy question is: Who shall make the judgment?
On a more general level, one may raise questions in terms of a conflict between two values: the advancement of knowledge, and the personal integrity and convenience of the individual citizen. Nowhere does this conflict become more explicit than in questions concerning invasion of individual privacy, especially in regard to the collection of detailed data about individuals and their maintenance in files that are presumably to be used for research purposes.
The issues here turn around safeguards as to how the data will be used, and in how much detail the data will be kept. Briefly summarized, what has been proposed is that certain kinds of data which are now regularly collected by various agencies (central and local authorities and perhaps private agencies, too), but kept in separate files and published only in aggregated forms be made available for research purposes on a disaggregated basis.
More specifically it is proposed that data about individuals such as employment, income, savings, or expenditures be collected and stored in such a way that it would be possible to match the information from these separate series, by individuals. The anonymity of the individual and the confidentiality of the information would presumably be maintained as they are now. The data system would be used for research purposes, not for administrative ones.
Whether the very existence of a national data system would tempt those with legitimate access to make illegitimate use of the data is a much more serious question, going well beyond the data system per se. The question really turns around one’s estimate of the likelihood of “big brotherism”—of a controlling government and a controlled society, and of the role the social sciences might play in bringing about such a situation or maintaining it. As our society grows in density of population, in interdependence, in complexity and technological sophistication, the need for rational planning and for the thoughtful and foresighted management of our affairs grows apace. And so does the need for vigilance in the defense of individual liberty, since there is always, as there always has been, the tempting possibility for those in power to “simplify” their problems by wielding their power in ways that constrict freedom and constrain the less powerful.
There is no reason, however, to see the social sciences as more culpable or more threatening than other kinds of science and technological development. The power of the state is increased by the development of sophisticated weapons for its police, more efficient communication among them, and by devices that enable eavesdropping at a distance and through a wall. There are dangers in pharmacological control of behavior. Individual freedom can be abridged by the architecture of our dwellings and the design of our transportation, as well as by the laws which govern minimum wages, welfare payments, and income tax exemptions.
In fact, the social sciences can help to make us aware of threats to our freedom while giving us greater power to control our own behavior in constructive ways, helping us to be more tolerant of diversity, to learn to live together in greater harmony, less violently and more satisfyingly. If we are to reap these benefits, however, we must work at understanding ourselves and our society, at perfecting a social science that is capable of meeting the challenges of our future.
Henry W. Riecken (1917–2012) was an eminent social scientist who served as president of the Social Science Research Council between 1966 and 1971. He was also the first director of the National Science Foundation’s social science division. He also served on the faculties of Harvard University, University of Minnesota, and University of Pennsylvania.
This essay originally appeared in Items Vol. 23, Issue 1 in the spring of 1969. Visit our archives to view the original as it first appeared in the print editions of Items .


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- 26 February 2020
- Clarification 04 March 2020
Economists and scientists: solve big societal problems by working together
You have full access to this article via your institution.

Economics and finance: meet science. Credit: Sebastien Micke/Paris Match/Getty
“He has enriched the world with works that will long remain monuments of science.”
Reading Nature ’s 1873 obituary 1 of the philosopher and economist John Stuart Mill, you would think economists and scientists were two sides of the same research coin — that economics was welcomed as part of the scientific tradition, and vice versa. But that was then. The age of the polymath was coming to an end and researchers were becoming single-discipline specialists. Economists and natural scientists drew apart as universities organized their researchers into engineering, humanities, science and social-science faculties.
Well over a century later, the pendulum is swinging back. Economists and scientists are moving closer, as universities and funding agencies embrace more multi- and transdisciplinary research. Over at the World Health Organization, a chief-economist post is being considered.
Nature will soon appoint an economics editor, following the lead of Nature Climate Change , Nature Energy , Nature Sustainability , Nature Human Behaviour and Nature Communications. We recognize the importance of reuniting economics with other disciplines.

When capitalisms collide
These moves could not have come soon enough. The world faces a mountain of challenges — and to find solutions, humanity must approach them in multiple ways. One of the biggest puzzles concerns the research enterprise itself. Economists have been pointing out for some years that we don’t fully understand why the results of research and innovation — which have ushered in the digital age along with other transformations — are not benefiting everyone in society, as seen for example in wage stagnation and widening inequality. But relatively few natural scientists or engineers have taken up this question.
At the same time, more economists than ever are reaching across disciplinary divides, and they want journals to recognize the results. “I have younger colleagues interested in the economics of data, artificial intelligence, pharmaceuticals. They want to work with — and publish with — scientists,” says economist Diane Coyle of the University of Cambridge, UK. But she and others say that they struggle to publish work on big societal problems — co-authored by natural scientists or social scientists from other disciplines — because such work can fall outside the remit of economics and science journals.
But it matters. In 2011, not long after the global financial crisis of 2008, Bank of England chief economist Andy Haldane worked with theoretical ecologist Robert May to harness infectious-disease modelling techniques to investigate risks and vulnerabilities in the global financial system. Their resulting Nature paper 2 showed researchers how they could collaborate to understand other complex networks, such as those involving trade or information. “I am continually surprised at how much impact that paper has had,” says Haldane.

The dangers of fringe economics in government
Jim O’Neill, former head of economics research at global investment bank Goldman Sachs in New York City, reached across the aisle to study the financing of new antimicrobial drugs (see go.nature.com/2e3bkmj ). Economics research, he says, could demonstrate the costs and benefits of investing more in public health, to encourage governments in low- and middle-income countries to make such investments. Similarly, with the pharmaceutical industry and governments still not properly funding development of a badly needed new generation of antibiotics, he says, biomedical researchers need to collaborate with economists and public-policy specialists to create a workable financial model.
The environment — including biodiversity and climate change — is one area in which natural-science researchers and economists do have a long-standing shared interest. Economics research, for example, is assessed by the Intergovernmental Panel on Climate Change, and Nature ’s research and comment sections publish influential work from ecological and environmental economists 3 .
But here, too, there’s potential for more joint problem-solving. Success in many of the United Nations Sustainable Development Goals will require an understanding of how far economies can continue to grow within planetary limits. But there are many views on this, including various intellectual traditions in economics. Some economists, for example, argue that a planet under pressure from industrialization cannot withstand continued economic growth. But for others, growth is essential to alleviating poverty — as long as growth becomes greener.
To solve these problems, economists, natural and social scientists and engineers must all engage with and learn from each other. It is often too easy to say ‘more research will help’. But here, it is necessary — especially economics research, which we look forward to publishing.
Nature 578 , 489 (2020)
doi: https://doi.org/10.1038/d41586-020-00532-4
Updates & Corrections
Clarification 04 March 2020 : An earlier version of this editorial omitted to mention Nature Communications in the list of Nature Research journals with economics editors.
Nature 8 , 47 (1873).
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Haldane, A. G. & May, R. M. Nature 469 , 351–355 (2011).
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