Science and technology have progressed exponentially, making it possible for humans to live longer, healthier, more creative lives. The explosion of Internet and mobile phone technologies have increased trade, literacy, and mobility.11 At the same time, life expectancy for the poor has not increased and is declining.9
As science fiction writer William Gibson famously quipped, the future is here, but unevenly distributed. With urgent problems from inequality to climate change, we must train more passionate and innovative peoplewhat I call public entrepreneursto learn how to leverage new technology to tackle public problems. Public problems are those compelling and important challenges where neither the problem is well understood nor the solution agreed upon, yet we must devise and implement approaches, often from different disciplines, in an effort to improve people's lives.
Problem solving has been identified as one of the most important skills a graduate of engineering and computer science, as well as graduates of other professional schools, must have in the 21st century. Yet, as someone who has been tenured in both law and engineering and taught in a public policy school, I can report that our universities are failing to teach future professionals how to tackle complex problems in a rapidly changing world.
The primacy of technology in our daily lives combined with the urgent need to design and implement solutions to public problems require a new curriculum of public entrepreneurship.
Public entrepreneurship teaches students to tackle public problems in the public interest. First, it demands working together in teams and with real-world partners across disciplinary silos. Second, it teaches participants to go beyond vague issues to define actionable problems. Third, public entrepreneurs learn to use the tools of both data and collective intelligence to get smarter about both problems and solutions. Fourth, they learn to design solutions together with those they are trying to help by adopting more participatory and democratic ways of working and, finally, they learn how to implement measurable solutions in the real world that improve people's lives.
Done right, engineering and computer science teach technological craft, but all too often without complementary instruction in how to implement solutions in the real world of institutions. In fact, engineering is too often taught without regard for cultural, social, and political context.3 Internships, while useful, are no substitute for acquiring the formal skills of problem solving.
For law students, too, we give them too limited a toolkit. Whereas public interest litigation, strategic use of contracts, and knowledge of how to craft legislation and regulation are vital mechanisms for public problem solving, the agile and flexible tools of technology, data, and innovation have been woefully absent from the curriculum.
Our public policy schools are similarly out of date. For example, of the top 25 public policy schools as ranked by U.S. News and World Report in 2019, none required studentsa to take even basic coursework in data science. Former Woodrow Wilson School Dean and head of New America Foundation Anne-Marie Slaughterb writes that our public policy schools are teaching a method of problem solving that is "built in a different time and for a different timean era with fewer citizens, a slower pace of information dissemination, and a data capacity that is a fraction of what we have today."8 In a recent public statementc by a group of leading deans and educators convened by Stanford University, we wrote: "In the United States, and other consolidated democracies, the system of educating and training people to solve public problems is radically insufficient. Often such education and training, especially for professionals, simply does not exist."
Back in 2015, 120 U.S. engineering and computer science school deans announced plans to educate a new generation of engineers expressly prepared to tackle some of the most pressing issues of the 21st century. Moreover, computer science and engineering students as much as their law and policy counterparts are keen to "do stuff that matters."
Create transdisciplinary teams. First, schools must create real-world problem-based learning opportunities that cut across the natural and social sciences by creating teams of engineering and computer science, law, and policy students to work on public interest problems in collaboration with outside institutions. Between the National Academy of Engineering's (NAE) Fourteen Grand Challengesd and the United Nations 17 Sustainable Development Goals (SDGs)e there is no shortage of important public problems. At NYU Tandon's Ability Lab,f students across CS, engineering, design, and occupational therapy are designing better tools to improve the lives of those with disabilities.
Rensselaer Center for Open Source,g the centerpiece of its computer science student-run programs endeavors to "empower students to develop open source solutions to real-world problems." In one recent project, a dozen students are helping community organizations to develop simple free tools to advance their societal impact.
Although there are often collaborative programs across different branches of engineering, such as computer and biological engineering, however, most professional schools teach problem solving only with the toolkit of their own discipline as a result of a century-long effort to professionalize a unique science for each field.10 Now we are seeing the consequences of such siloes with students underprepared to work in global cross-disciplinary and diverse teams.
Over the years of teaching public problem solving in law, policy, and engineering schools, I have found that exposing students to one another's complementary substantive knowledge and diverse problem-solving heuristics and vocabularies enables teams to get more done.
Learn to define an actionable problem. Second, professional schools must teach problem solving beginning with actionable problem definition,h rather than by handing students a problem. Too often students are taught to solve well-structured problems working from preexisting cases.
Even so-called capstone or research assistantships assign prescribed tasks to students. But real-world problems are not well structured and context specific. Empirical research has shown that only learning to solve well-structured problems does not readily enable graduates to tackle open-ended, complex real-world problems.7
A real innovator must discover the problem rather than work on a problem already presented.5 This is what educators refer to as problem-based rather than problem-solving or even project-based learning and requires learning the epistemic craft of how to define a problem, its historical and social context, and root causes.11 In How We Think, John Dewey claimed this process of defining the problem reflects the essence of the development of complex thought and that is why Maastricht University uses a problem-based learning model for all its teaching.i,j,2,4
Use diverse tools. Third, it is a commonplace to say that defining a problem depends upon understanding root causes. But, to do so well, teams must use both quantitative and qualitative methodsgetting smarter from both data and human insight to frame the problem to solve.
This means abandoning a dogmatic adherence either to human-centered design or data analysis as the exclusive means of problem discovery. The popularity of design thinking as evidenced by an increasing number of design science courses and programs, on the one hand, and of data science pedagogy, on the other, have led to a headlong rush to embrace one or the other set of tools.
Whereas data might reveal where gun violence is occurring, only talking to those with relevant professional know-how as well as police, victims, and families will reveal why it is happening. Students across disciplines must develop both sets of skills. In the Open Seventeen program, a partnership among Tsinghua, NYU, and the Universities of Zurich and Geneva, global students from computer science and informatics, design, history, policy and more, received online project coaching from the Governance Lab and learn to apply both human-centered design and data analytical methods to advance projects that respond to one of the 17 SDGs.k
From design to implementation. Fourth, we need to teach students the undervalued and more challenging task of implementing solutions, not just designing them, by assessing feasibility in the context of real-world institutions. Even public policy schools, where one would assume this is taught, says Francis Fukuyamal "train students to become capable policy analysts, but with no understanding of how to implement those policies in the real world."
Tackling social problems requires a deep understanding for engineers and computer scientists, too, of how to work with institutions to take advantage of their power, reach, and resources. Thus, to develop their lifelong clinical problem-solving capabilities, the would-be public entrepreneur must learn a deep understanding of how bureaucracy and politics can be harnessed for impact. This is why at Purdue the Engineering Projects in Community Service (EPICS) projectm offers students the opportunity to learn about the social context of the projects they do. More than clever ideas and ingenious gadgets, our ability to solve problems depends upon people with the willingness and wherewithal to deliver and spread impact.
From social enterprise to public entrepreneurship. To be sure, most schools today offer some kind of program in private entrepreneurship. Yet the pedagogy of problem solving taught in those clubs and classes has critical limitations.6 Private entrepreneurship focuses on the ego of the individual and the ability of a person to devise their own original solution, launch an app, or start a company.
But true public problem-solving demands solutions that are legitimate as well as effective. This means that, rather than learning to develop solutions oneself, students must learn participatory and democratic methods for defining problems and developing solutions with rather than for communities.
Take the example of Indian public entrepreneur and biophysicist Samir Brahmchari, former director general of the Council of Scientific and Industrial Research of the Government of India. In India, thousands of primarily poor people die every year from tuberculosis. Yet there has been no new TB treatment developed in 40 years and resistance to existing drugs is increasing. So Brahmchari became the chief mentor for the Open Source Drug Discovery project,n a crowdsourcing effort to "provide affordable healthcare to the developing world by providing a global platform where the best minds can collaborate and collectively endeavor to solve the complex problems associated with discovering novel therapies for neglected tropical diseases." By recruiting college students, academics, and scientists from around the world and across India, most in remote villages not elite universities, Brahmchari created his own inexpensive army to collect, annotate, and extract information from the scientific literature on the TB pathogen. With a $12 million grant, he coordinated the incremental contributions of 7,500 participants from 130 countries and began clinical trials for a new experimental drug at 20% of the cost of a traditional drug in 2014.1
Brahmchari is paradigmatic of the new public entrepreneur who works differently, taking advantage of new technologies, especially the tools of big data and collective intelligencebut also the convening power of institutionsto take on difficult and seemingly intractable public problems.
Complementing traditional university education in computer science and engineering as well as law and policy with public problem solving in multi-disciplinary teams to design and implement workable solutions with public institutions would allow us to cultivate more such public entrepreneurs, transforming how we educate while producing the leaders and problem solvers committed to improving people's lives that we so desperately need.
1. Ardal, C. et al. Open Source Drug Discovery in Practice: A Case Study National Center for Biotechnology Information (Sep. 20, 2012); https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3447952/
4. Farra, H. The reflective thought process: John Dewey re-visited. The Journal of Creative Behavior (Mar. 1988): https://doi-org.proxy.library.nyu.edu/10.1002/j.2162-6057.1988.tb01338.x
8. McGuinness, T. and Slaughter, A. The new practice of public problem solving. Stanford Social Innovation Review (2019); https://ssir.org/articles/entry/the_new_practice_of_public_problem_solving#
9. National Academies of Sciences, Engineering, and Medicine. The Growing Gap in Life Expectancy by Income: Implications for Federal Programs and Policy Responses. The National Academies Press, Washington DC, 2015; https://doi.org/10.17226/19015
11. Savin-Baden, M. The problem-based learning landscape. Planet (2001); https://doi.org/10.11120/plan.2001.00040004
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