Category: News

By Lisa Bauer

Robotics Professor Ken Goldberg is the first to acknowledge the public anxiety about what automation and AI might mean for future jobs. Singularity—the hypothesis that AI will become increasingly powerful, decimating professions and remaking civilization—is becoming a mainstream concept. All one has to do is read news headlines about robot-driven factories, watch movies like “Ex Machina,” and listen to public figures like Elon Musk stating that AI poses our greatest existential threat.

Yet at a recent Blum Center Faculty Salon on the Digital Transformation of Development, Goldberg, UC Berkeley’s Department Chair of Industrial Engineering and Operations Research and the William S. Floyd Jr. Distinguished Chair in Engineering, argued that such fears are exaggerated. He is among computer scientists and roboticists who believe there is inadequate evidence to support the mass unemployment theories, such as the often cited Oxford University study that estimated 47 percent of U.S. jobs are at risk of computerization.

Rather than replace human jobs, Goldberg believes artificial intelligence and robots will help to diversify human thinking. And rather than worry about a robot apocalypse, he urges a focus on what he calls Multiplicity, in which diverse combinations of people and machines work together to solve problems and innovate.

“Multiplicity is not science fiction. It’s a reality that is already a part of our daily lives,” said Goldberg.

To prove his thesis he references Google search, Amazon and Netflix’s personalized consumer recommendations, Waze navigation, and spam filtering—examples of machine learning that lead to rapid, wide-scale results. One of Goldberg’s points is that the public has long held a fascination with “creative overreach” and mechanized monsters (e.g., Pygmalion, Frankenstein, the Terminator). Yet our greatest AI successes so far have not involved walking, talking robots or even autonomous vehicles—they have involved machine learning for games, such Google DeepMind’s mastery of chess. This is because machines excel when operating in a controlled information system; whereas navigating space is dynamic and uncertain.

Goldberg said the race to develop fully autonomous vehicles exemplifies this misunderstanding. While the public has been led to believe that autonomous cars are just a few years away, engineers and computer scientists say there are many barriers to overcome because driving is not a game with set variables. It involves navigating double parked trucks, weaving bikers, kids playing, and shade and light obscuring vision. A computer program is currently not capable of responding to these myriad, unpredictable situations. Indeed, Goldberg argues we are just as likely to be headed for an “AI Winter” rather than a near future with driverless cars.

Goldberg believes that automation will both eliminate and create new jobs. Quality of work may be improved by decreasing the amount of time spent on mundane tasks. One example of this is the ATM machine, which was initially met with outcry from bank tellers who believed their jobs were doomed. Instead, the lower costs of running a branch allowed banks to open more branches and expand services, ultimately increasing the number of overall jobs while also creating new types of jobs in sales and customer services.

“People are claiming that AI will steal truck driving jobs,” said Goldberg. “but the fact is we have a shortage of truck drivers and there’s demand for more. Technology will make their jobs better.”

Proceeding further, Goldberg compared automation anxiety to anti-immigrant politics, quoting Oliver Morton’s observation that “robots are immigrants, from the future.” Historically, job losses have been blamed on immigrants; today said Goldberg, robots are the latest scapegoats.

“We need a shift in mindset, rather than ‘us against the machines,’” emphasized Goldberg. “let’s focus on ‘us with the machines,’ and explore the potential for machine collaboration—how the combined strengths of diverse humans and diverse machines can enhance the human experience.”

“Cognitive Diversity, AI & the Future of Work,” a study co-authored by Goldberg and Vinod Kumar, CEO of Tata Communications, reports that much of education today emphasizes conformity, obedience, and uniformity, while the skills of tomorrow demand creativity, diversity, and flexibility. Most of the 120 global business executives interviewed for the study believe AI will increase the number of roles in the workplace and have the potential to enhance human collaboration and cognitive diversity within groups. Among the report’s conclusions is that what we need is not new forms of welfare and unemployment, but a shift in education that will better facilitate job transitions.

Goldberg said advances in agricultural machinery at the beginning of the last century prompted a need to train people with non-farming skills, creating what would become the “High School Movement.” The impact was huge: in 1910, only 10 percent of Americans graduated from high school; by 1950, 80 percent held a high school degree.

Given this precedent, Goldberg proposes a “Multiplicity Movement” to foster uniquely human skills that AI and robots cannot replicate: creativity, curiosity, imagination, empathy, human communication, diversity, and innovation. He recommended the U.S. reinforce creative and social skills in high schools and universities, so that Americans are in position to leverage diverse machines alongside diverse groups of people to amplify intelligence and spark high impact problem solving.

In response, Laura Tyson, Blum Center chair and interim dean of the Haas School of Business, expressed greater apprehension about the effects of artificial intelligence on the future of work. She emphasized that each country and region will experience the digital transformation differently, according to factors like local policies and politics, demographics, and educational attainment. Tyson, who has years of policy experience in the U.S. federal government and international organizations, pushed the group to think more broadly—not just in terms of the future of jobs but also in terms of what she called the “future of livelihoods.”

“Individual workers should not have to bear the costs of transitions from jobs that are eliminated by technology to jobs that are created by technology,” she said. “We need to ensure that livelihoods are not compromised in the transition, and that we are counteracting rather than reinforcing economic inequality.”

Tyson contrasted concerns about the effects of AI on the future of work in the U.S. and other developed countries with the enthusiasm for AI in China where “automation anxiety” hardly exists. As a result of the largest and fastest industrialization and urbanization in history, China has a growing and thriving middle class that is heavily reliant on new technologies. Based on the rapid growth in living standards over the past 30 years, Chinese citizens expect that they will continue to benefit from new AI-based technologies.

The substitution of intelligent machines for low-cost, low-productivity workers poses the greatest challenge to the future of livelihoods in Africa. Such machines threaten the strategy of rapid development through industrialization based on low-labor costs and labor arbitrage. By 2050, Africa’s youth population is estimated to increase by 50 percent to 945 million. The continent will have the largest number of young people in the world. What kinds of work will they do? What kinds of livelihoods will be possible? What will be the place of African countries in global trade and global supply chains when the availability of comparatively cheap labor is no longer a competitive advantage?

Juxtaposing the youth explosion in Africa, the aging demographic patterns in Japan and Germany, the U.S.’s skills and wealth gap, and the success of China in rapid industrialization and global trade, Tyson posed several questions to consider: How will we ensure that all countries and communities benefit from AI and automation? How do mid-career professionals adjust if their job becomes obsolete? How will mid-career professionals gain new skills? Who pays for it? How do we prepare diverse populations for smooth economic and labor transitions?

Tyson advocated that nations develop comprehensive educational and development strategies that support the livelihoods of their citizens—and that share the benefits of intelligent machines broadly.

By Tamara Straus

On October 10 at the first Blum Center Faculty Luncheon devoted to “Digital Transformation of Development,” Michael Nacht, the Thomas and Alison Schneider Chair in Public Policy, presented on “The Nexus of National Security, Diplomacy, and Development”—and gave a sober assessment of what that nexus might produce under the Trump administration.

Nacht, who has served three tours of duty in government, most recently as Assistant Secretary of Defense for Global Strategic Affairs (2009-2010), provided an overview of government investments in the defense and development sectors. He reminded the group of Blum Center-affiliated faculty that the research which led to the atomic bomb was entirely government funded and led through national labs, including Lawrence Livermore National Lab.

“Thinking about it now years later,” said Nacht, “the community that makes up Lawrence Livermore National Lab understands things have really changed. There has been a proliferation of technologies and the vast majority of the innovative work is being done by the private sector. In fact, 85 percent of the research and development in this country is being funded by the private sector, not the government. It has spillover effects, not just in national security, but in development.”

Nacht was referencing a 2018 LLNL book on this shift he co-edited entitled Strategic Latency: Red, White, and Blue—Managing the National and International Security Consequences of Disruptive Technologies. The book looks at the implications of artificial intelligence, bioengineering, and other technological advances and underscores the consequences of disruptive paths are never straight. “We appreciate the seeming contradictions that can lead life-saving technologies in unintended negative directions, or prompt military technologies toward peace and prosperity through spinoffs or war-avoiding defenses,” Nacht and his co-editor Zachary Davis write in their introduction.

Yet Nacht has become a pessimist. He said that national security and international development interests don’t have much current geopolitical overlap. That is because national security interests are focused on Russia, China, Iran, North Korea, Islamic terrorism, cyber threats, and space-related work—and international development interests are focused on areas of high poverty, particularly Sub-Saharan Africa and Southeast Asia. “Really, the only two [developing] countries that transcend to the national security community are India and Iraq,” he said.

Also, Nacht is adamant that the current presidential administration is making defense, diplomacy, and development intersections unlikely because of what he called “the Trump team’s tremendous rejection of multilateral instruments.” He added: “There may be outright hostility in trying to apply national security interests to international development interests.”

Nacht did point out the Department of Defense under former Secretary of Defense Ash Carter (2015-2017) focused on strengthening ties between the DoD and the tech community. In August 2015, DoD established the DIUX, the Defense Intelligence Unit Experimental, with headquarters in Mountain View, to help the U.S. military make faster use of emerging commercial technologies, promote joint appointments, and imbue the defense department with a more entrepreneurial culture. Nacht said those efforts have not ceased, but it is unclear whether they are, or can be, a priority under Secretary of Defense James Mattis.

Still, Nacht pointed out that we will continue to see areas of confluence between defense, technology, and even development, especially in academia. He cited the example of UC Berkeley Bioengineering Professor Jay Keasling, whose research on the metabolic pathways inside cells led to a semi-synthetic version of the antimalarial drug artemisinin, which has driven down the cost of treatment and saved lives in Sub-Saharan Africa, creating greater equity and stability.

Yet Nacht expressed concern that new technologies, particularly AI and machine learning, could devastate the developing world. Citing a September 17, 2018 Bloomberg article on the subject, he said China has been able to leverage its large population and low costs to build a manufacturing sector that is producing better and more technology-intensive goods—while India, with its large English-speaking population and low costs, has become a hub for outsourcing low-end, white-collar jobs in fields like business-process outsourcing and software testing. Now, however, with AI’s accelerating automation of factories and customer service, corporations will bring many of these jobs back to where they are based, leading to a potentially explosive crisis.

“It’s a complicated pattern,” said Nacht. “Using technology to improve lives sometimes works and sometimes doesn’t.”

At the same time, Nacht noted that China’s investment in African and Latin American infrastructure in exchange for natural resources is a phenomenon that the U.S. cannot afford to ignore, especially as China does not proffer democracy building, human rights, or other political carrots as a condition for investment. This purely economic transaction, Nacht said, is one that the Trump administration might follow, ending decades of foreign policy initiatives.

Nacht concluded that the U.S. needs more strategic interaction between its economic and foreign policy positions in developing countries, but said reading the Trump administration’s tea leaves in this regard is next to impossible.

Among the discussants to respond to Nacht’s presentation was Joshua Blumenstock, assistant professor at the School of Information and director of the Data-Intensive Development Lab. His research lies at the intersection of machine learning and development economics, and focuses on using novel data and methods to better understand the causes and consequences of global poverty. Blumenstock noted that resource challenges arising from climate change should bring together the national security, technology, and development communities. But that the cultures of these communities are quite distinct and often at odds. He would like to see more efforts like DIUX to find commonalities between the communities.

Alice Agogino, professor of mechanical engineering and the Blum Center’s education director, said that one research effort combining climate change, development, technology, and national security is the center’s InFEWS (Innovations at the Nexus of Food, Energy, and Water Systems) program, supported by the National Science Foundation. InFEWS recognizes that food, energy, and water systems are under increasing stress, and it is thus becoming imperative to integrate social, ecological, physical, and built environments to meet growing demand for food, energy and water in the short term while also maintaining appropriate ecosystem services for the future. The Blum Center’s program is supporting graduate students working in these systems and helping them master interdisciplinary skills to create research that can be transferred out of the lab and into the field. “In essence,” said Agogino, “we are already supporting the very people who can serve at the nexus of national security and development. We call them Development Engineers.”

Brad DeLong, the Blum Center’s chief economist, ended the session with a long view of the history of war. Bringing the group to the present times, he said: “Now we find ourselves in a world with many security threats to us and to others, with a military that does not have a history to deal with the threats we face and the missions it is going to be asked to undertake. To amplify our problems, we have little idea about the form that the social practice of war will take in the 21st century. We do not expect to see the industrial total wars, the national liberation wars, the imperial little wars that we saw in the 20th century. But what will we see? What kind of U.S. military would best deal with what we are likely to see? And how can the U.S. government’s power—military, diplomatic, development—be deployed to eliminate as many 21st century war threats as possible?”

DeLong concluded: “A great deal of the potential causes of 21st-century war as a social practice, whatever form it turns out to take, are rooted or are aggravated by problems of development. And the U.S. military—with its tradition from the Black Hills-stealing army of the post-Civil War on up to the fast-moving powerful force of Desert Storm where we were tasked with being military police in a place where we did not speak the language—is not well-equipped to think about the force structure and the doctrine needed for the 21st century. Here I think we can really, genuinely help.”

By Sophi Martin

When you get a PhD, you are the world’s expert in some narrow but incredibly deep scientific realm. You have asked a question never before asked, developed a hypothesis informed by reviewing the previously collected knowledge in the space, spent significant time testing, defending, and retesting your ideas–and arrived at some new truth.

Perhaps you were part of a dynamic and interdisciplinary research group that met regularly and engaged in intellectual battles that strengthened your knowledge. Perhaps you spoke with your doctoral advisor infrequently and to other researchers even less so. Perhaps you’ve had access to a network of mentors and advisors and peers. Regardless, you emerge as an “expert,” expected to ask great questions and seek knowledge, and society generally regards you in an impressive light.

But what happens the day after you wear your tufted hat and are marked as “doctor”? The 2018 report “Graduate STEM Education for the 21st Century” from the National Academies of Sciences, Engineering, and Medicine finds that graduate programs don’t do a great job of training graduate students for non-academic careers, where complex challenges cannot be solved by one smart and dedicated individual, but rather require collaboration across many fields, with colleagues who may have other kinds of training, or perhaps no training at all. Will you be able to communicate with your peers, with your boss, with people who work for you, and with society at large in a productive way? How will you oversee other researchers when you’ve never had any exposure, let alone real training, for managing projects?

A recent National Science Foundation meeting of multidisciplinary programs highlighted various approaches to transform this graduate student experience from that of developing a lone genius toiling away in a lab to one that prepares graduate students to tackle complex new fields of knowledge–like data-enabled science or the food-water-energy nexus–while also building critical skills in communication, collaboration across multiple disciplines, and leadership.

The two-day symposium brought together over 60 NSF Research Traineeship (NRT) programs to share ideas on how to build these skills, how to assess whether the approaches work, and how programs like these might fundamentally change how graduate students are trained. The programs seek to build bridges across departments–e.g., blending civil engineering, energy sciences, environmental sciences, agricultural economics, business, and public policy, as the InFEWS program from UC Berkeley’s Blum Center does. The NRT programs also support graduate students conducting research at the intersections of these fields, aiming to build lasting bonds between the participating departments after the grant period concludes.

NRT Graduate Student Anaya Hall, said the NSF meeting provided an  “opportunity to get to know students and faculty in other programs across the country and to learn from each other on how to foster interdisciplinary research, while preparing for a variety of career paths.” She added, “It was inspiring to know the program at UCB is serving as a model for its commitment to diversity and inclusion as well as encouraging science for a broader impact.”

Dawn Culpepper and Colin Phillips of University of Maryland, College Park remarked in a joint presentation that the “NSF Research Traineeship allows students to develop competencies in framing the importance and potential impact of their work.” In addition to building academic depth, they argued that the NRTs serve to shift the values and highlight the context surrounding the academic research by exposing students to different perspectives–showing how other disciplines might view the same challenge or asking how communities might be affected by research questions. The NRT’s emphasis on communication skills trains students to clarify their role in research and explain what they are doing and why to diverse stakeholders, thus building more well-rounded researchers and job candidates.

With over 100 NRT programs nationally, there are emerging benefits–communications, ability to work in teams, seeding new areas of research–as well as consistent challenges. Repeatedly, the NRT program representatives at the meeting cited that fostering true collaboration among faculty across campuses was difficult, due to time pressures, insufficient funding for dedicated research projects, and insufficient recognition among the academic community for interdisciplinary work. Many programs discussed the bureaucratic barriers of establishing lasting cross-disciplinary programs, like certificate or degree programs, individual classes or series of classes. Almost every NRT at the meeting cited challenges in securing enduring institutional and financial support for team teaching, program staffing, and program elements such as communication skills workshops.

Finally, there is a clear mandate from NSF that programs like this must influence their own institutions, and ultimately influence other institutions nationally. With academic innovation typically taking multiple years, if not decades, it will be some time before programs that offer deep technical training plus interdisciplinary learning are the norm for STEM and other doctoral students. The harsh truth is that not all great programs are scalable or should aim to be a priori. And indeed, it is the deep personal connections between students and mentors, and student peer groups, that was cited by NRT students at the NRT principal investigator meeting as the most special, and personally transformative, part of their program. Although some coursework might move online, a whole interdisciplinary training program inherently cannot live online, in a MOOC, or some massively distributed medium. Fostering people skills takes people–in real life–and while expensive to support students, faculty time, staff time, and program cost, it is 100 percent worth it.

Since interdisciplinary learning at the PhD level has become of core national interest–undisputed in necessity by business leaders, university heads, and innovators of all walks–there needs to be federal funding available for it. For decades, educating well-rounded, articulate, technically proficient students has kept the U.S. competitive in science and technology and influential in global politics. Now, with the continuing effects of globalization, climate change, and the information and computational revolutions, we need students who can work at the intersections of fields with the greatest chances for ensuring both our survival and our most ambitious dreams for progress.

Sophi Martin is the Innovation Director at UC Berkeley’s Blum Center for Developing Economies, where she serves as the Program Coordinator for the NSF-funded InFEWS program (infews.berkeley.edu ; DGE # 1633740)

Clinton Global Initiative University (CGI U) is President Clinton’s initiative to engage the next generation of leaders on college campuses around the world. Each year, CGI U hosts a conference where students, youth organizations, and topic experts come together to discuss and develop innovative solutions to pressing global challenges with policy makers, topic experts, philanthropic, and leaders from the public, private, and NGO sectors. Participants attend plenary sessions, workshops, networking events, and a day-long service project. This year CGI U 2018 will take place at the University of Chicago from October 19 to 21.

Each CGI U student must make a “commitment to action”: a specific plan of action that addresses a pressing challenge on campus, in the community, or in a different part of the world. Students can apply within five focus areas: education, environment and climate change, peace and human rights, poverty alleviation, and public health.

This year, 31 UC Berkeley students were accepted to attend CGI U. Their projects are described below.

Artists in Residents

Students: Monica Schreiber (Public Health), Kyle Gibson (Public Health)

Summary: Artists in Residents (AiR), is an initiative of the Suitcase Clinic, a weekly student-run organization that has been serving Berkeley’s homeless community for over 30 years. In response to the mental health needs of this population, AiR seeks to provide arts and music programming within clinic spaces while leveraging the Suitcase Clinic’s unique ability to elevate and advocate for unhoused Berkeley residents. The team will partner with local community partners to implement art and music workshops, galleries, and performances. AiR will provide creative outlets for self-expression, promote mental health, and foster self-efficacy and upward mobility. Over one year, AiR will work with 30-50 individuals to provide safe spaces to practice, develop, and showcase their artistic talents. AiR won 1st place in the Art & Social Change category of the 2018 Big Ideas Contest.

Our Campus Kitchen

Students: Lucinda Laurence (Architecture), Sara Tsai (Business), Ibrahim Ramoul (Public Health)

Summary: In the 2018-2019 year, Lucinda Laurence, Sara Tsai, and Ibrahim Ramoul are committed to enact a centralized waste recovery kitchen on UC Berkeley campus. They will establish a closed-loop ecosystem that streams food waste from the dining halls and transforms them into edible meals for students at an accessible sliding-scale price model. The team plans to improve the lives of marginalized students by offering affordable meals while educating more than 35,000 students in food recovery and security. Each semester, they will lead 125 volunteers to make 600 meals daily by transforming 200 pounds of dining hall waste. Their partners include the Berkeley Student Food Collective, Berkeley Food Institute, Copia, Food Pantry, Educational Opportunity Program, University Health Services, and Cal Dining. Our Campus Kitchen won second place in the Food Systems category of the 2018 Big Ideas Contest.

Project S.a.F.E.

Students: Briana Boaz (Biology), Carrie Trible (Biology) Emily Kearney (Graduate Student – Environmental Science)

Summary: In 2018, Emily Kearney, Briana Boaz, and Carrie Tribble committed to eradicating sexual harassment/assault from fieldwork in order to create safe spaces off-campus in which everyone could contribute to science effectively. This team will survey the campus community to understand this issue and will use this information to write a code of conduct and create resources to prevent field sexual harassment/assault in partnership with several UC Berkeley campus organizations. These efforts are expected to reach everyone involved in fieldwork and increase the use and awareness of field preparation resources by 50 percent.

Project Air Mask

Students: Anirudh (Rudy) Venguswamy (Economics)

Summary: Rudy Venguswamy has committed to creating an affordable respirator mask to help reduce the number of people who die due to pollution and biomass burning related diseases in India. The team will sustainably produce a waterproof, fashionable, and functional respirator that people can wear while outside or engaged in hazardous activity. Project Air Mask will partner with hospitals to distribute masks first to pregnant women, young children, and at risk populations. The team expects to reduce the cases of chronic obstructive pulmonary disease and other respiratory infections by 20 percent in 24 months in the states in which this solution is deployed.

Brad DeLong, the chief economist of the Blum Center, has spent the past four decades researching, writing about, and influencing public policy in the areas of business cycle dynamics, economic growth, behavioral finance, political economy, economic history, international finance, and the history of economic thought. He graduated summa cum laude from Harvard in 1982, and earned a PhD in economics, also from Harvard. Thereafter, he taught economics at MIT, Boston University, and Harvard, becoming in 1991 a John M. Olin Fellow at the National Bureau of Economic Research.

DeLong joined the UC Berkeley faculty as an associate professor in 1993; however, from 1993 to 1995, he served as Deputy Assistant Secretary for Economic Policy at the U.S. Department of the Treasury under the Clinton Administration. There, he worked on the 1993 federal budget, the health reform effort, and the Uruguay Round of the General Agreement on Tariffs and Trade and the North American Free Trade Agreement. He became a full professor at Berkeley in 1997, and has since also served as co-editor of the Journal of Economic Perspectives, research associate of the National Bureau of Economic Research, and a fellow of the Institute for New Economic Thinking.

Delong is a prolific contributor to both academic thought and the popular press. Among his scholarly works are: Macroeconomics (a textbook continuously in print since 2002), The End of Influence: What Happens When Other Countries Have the Money (with Stephen Cohen), and Concrete Economics: The Hamilton Approach to Economic Growth and Policy (with Stephen Cohen). He is currently at work on The Economic History of the Twentieth Century: Slouching Towards Utopia? DeLong blogs at “Grasping Reality with Both Hands” and writes a monthly column for Project Syndicate.

The Blum Center sat down with Professor DeLong to gauge his views of the future of development.

Why did you decide to become an economist?

I would say that it was a long, slow process. As I look back, some milestonesstand out. Back when I was a child, the father of my best friend, Michael Froomkin, was an economist— Joseph Froomkin always seemed to have very interesting and smart things to say that came at the world from a different and very insightful perspective than others. When I was 12, I think, at the American Academy of Arts and Sciences meeting I got to spend a day playing with the “World Dynamics” global economic-ecological model. The model, I now realize, was very wrong—we are certainly not on any of the trajectories it forecast. But the idea that you could do such a thing was very interesting. When 1982 came around and I graduated from college, the unemployment rate was heading for 11 percent: my classmates weren’t having as easy a time getting jobs, and so staying in school seemed attractive. Becoming a lawyer seemed to involve too much proofreading of documents; becoming a lab scientist seemed to involve too much moving of small volumes of liquid from one test tube to another.

How have your views on economic policy and economic history developed over the course of your career?

I do not think that they have changed that much. If they have changed, it is in the direction of having less trust in economic theory as anything other than a shorthand way of crystallizing the lessons from history. I no longer think theory generates insights. I think theory provides a filing system for insights derived from history and practice.

What did you learn during your tenure as Deputy Assistant Secretary for Economic Policy at the U.S Department of Treasury?

Newt Gingrich was a real shock—that there actually was such a self-centered politician, for whom facts on the ground and what the consequences of policies would be for real people, was a shock. His electoral success did very bad things to the Republican Party. But outside of Gingrich and his zone of influence, I was impressed and gratified by how much everyone else in Washington, D.C. cared—about getting the facts right, about getting the policies right, about being good stewards for the country and the world, about trying to figure out how to bring us all closer to utopia.

What interests you most in the field of economic development today?

I am not sure if “interests” is the right word—perhaps “worries” is. There is the big question of the future economic role of “skilled” and “semi-skilled” workers. For the past 200 years, the royal road for a country or a sector to achieve successful economic development has been to use its low wage level to develop a comparative advantage and export industry in labor-intensive manufacturing. You thus borrow the middle-class of the global economic core to provide demand for the goods you manufacture and place them in global value chains. And so you can build up a community of engineering practice around which other processes of technology transfer can develop. By doing this, developing economy after developing economy—starting with the United States and continuing to Germany and most recently in China and Vietnam—have proved capable of importing necessary technologies and then nurturing the communities of engineering practice needed to raise productivity further, catching up at least partway to the global economic core.

But as Harvard’s Michael Kremer taught me fifteen years ago, it doesn’t look like there are going to be an awful lot of relatively low-wage, relatively low-skilled manufacturing jobs out there over the next 30 years. Will China and maybe Vietnam be the last countries for this kind of development? And if so, what alternatives do the structural changes driven by advancing technology open up, if any?

Other scholars to consider in thinking about this issue are: W. Arthur Lewis, the only Nobel Prize winner in economics from the island of St. Lucia. He wrote a book called The Evolution of the International Economic Order, laying out how this has worked. And Robert C. Allen wrote a book for Oxford University Press called Global Economic History: A Very Short Introduction. Most recently, Richard Baldwin has written a book called The Great Convergence: Information Technology and the New Globalization about the coming of the value chain world and its implications for global economic structure.

But even these three books don’t have a great deal to bear on the peculiar problems this provides for developing economies. I am planning a conference this fall at the Blum Center to get people together to talk about this question of the future of economic development.

Amartya Sen in Development as Freedom wrote: “Development consists of the removal of various types of unfreedoms that leave people with little choice and little opportunity of exercising their reasoned agency. The removal of substantial unfreedoms, it is argued here, is constitutive of development.” How would you define the unfreedoms that people in low-income regions and countries might experience in the coming decades due to advances in AI, automation, etc.?

The first unfreedom is obviously and simply: poverty.

I was reading 19th-century economist John Stuart Mill before I came here. Writing in 1871, Mills said: “It is questionable if all the mechanical inventions yet made have lightened the day’s toil of any human being.” In his day, he wrote, there was indeed higher productivity and there were a lot more machines. Together they had enabled a greater population to live the same life of drudgery and imprisonment; an increased number to make fortunes; and an increased number to achieve the comforts of the middle class. But they had not had any positive effects on working class standards of living. And in his description of working-class life, Mill used the word “imprisonment”.

Pause there. John Stuart Mill, founding utilitarian, founding libertarian, one of the people  most focused on “freedom” as the primary value, thought back in 1870 that the Industrial Revolution had failed. It has left the working class “imprisoned” because it had left them in poverty. “Imprisonment” is a very strong form of unfreedom: you are locked in a cage. Yet the working class John Stuart Mill saw around them had all the “negative freedom” that Sir Isaiah Berlin could have wanted.

But if John Stuart Mill sees freedom not as merely the absence of legal constraint or personal domination but as requiring enough wealth and social power to, as Sen puts it, “exercise reasoned agency,” who are we to disagree?

Lots of unfreedom could go away if only we could rearrange the process of economic development, so that the fruits of increased productivity would flow to the relatively poor in the form of income. Give people things to do that the outside world regards as valuable. But this also requires that you have to protect the property rights that the working classes have—or else rich and powerful people in your neighborhood will steal your things from you, and it does not matter much if they steal them “legally.”

Do you believe a Universal Basic Income is a feasible public policy to address growing inequality?

Milton Freedman, one of the founders of the Chicago School, was a strong believer in UBI, so it’s definitely out there. There are all kinds of worries about whether it is sociologically and politically unsupportable. There is a strong idea that people simply should never “get something for nothing.” I have never really understood this. We all get a good deal of something for nothing.

If you removed the society around me and all the gifts it has given to me—if you simply put me out in the Sierra foothills, naked, with my abilities to make tools with my own hands, I would starve to death in a month. We are able to be overwhelmingly productive today. But we are so only where we stand on the shoulders of giants, and use a great deal of stuff that has been given to us for free by those who came before us. To ignore this—it is to be born on third base and imagine that you hit a triple.

What about UBI within the foreign aid context, for example, the experiments with cash transfers?

The argument for cash transfers is that you want the people who have a strong sense of how they need resources to be able to spend their own money. The argument against cash transfers is that it’s relatively easy for local power brokers to take the cash away.

I believe delivering direct services, because you have economies of scale, has a great deal to be said for it. I have never understood the argument that service delivery or cash transfers harms people’s work ethic. People really do want to do useful and productive things with their lives overwhelmingly. Look, I had a rich grandfather. His wealth has been flowing to me to the tune of $20,000 per year since I was born until I turned 50. That’s a $20,000 UBI for me. Yet I do not see anyone wandering around saying this was a positively bad thing for me.

Do you use the term the “Fourth Industrial Revolution” to talk about the economic effects of AI, blockchain, nanotechnology, quantum computing, and biotechnology?

Well, it’s not “industrial.” There were two industrial revolutions. Coal and steam and cotton textiles comprised the first one. Then there were the new technologies of the 1880s and 1890s: internal combustion engines, oil, electricity, organic chemicals—that was the second. And I have never understood what the third was supposed to be.

ICT [information communication technology] is a post-industrial revolution. I just call it the ICT revolution, because as Alan Greenspan began saying in the 1990s, the most interesting thing is that the weight of what we are producing is folly. From 1700 to 1990, every year we made more and more stuff in terms of what is masses. And then in 1990, we began making stuff that has had less physical mass.

What does the discipline of economics bring to students taking Blum Center courses on poverty interventions?

Economics is good at getting the second and third order effects rights. For example, when something changes, people will start acting differently as their opportunities change—as the prices, both formal prices and informal prices, are transformed. But as they change what they do, that will affect the environment in which others can act, and what there opportunities are. Economics is very good at tracing those consequences through. And it does so in a way that gets you to not just qualitative but quantitative answers. That is a key analytic perspective—not the only valid one, but a key one.

What is your favorite period in economic history, given your interest in development issues?

I would say from 1870 to 1900, with the advent of: 1) the submarine telegraph cable; 2) the iron-hold, screw-propelled, ocean-going steamship; and 3) the industrial research lab and the arrival of machinery that could be deployed pretty much anywhere in the world.

These three changes made globalization and development on a large-scale possible. Before 1870, the most productive machines by and large did not work outside of England and New England in a way that would make them profitable to use. Before 1870, global communications were far from instantaneous. And before 1870, transportation costs were still relatively expensive enough to keep much of what was made in the periphery from being potentially valuable to the world’s industrial core. After 1870, none of these were true.

The world, however, greatly fumbled the opportunity. Since 1870, our failures of development have arisen from things we have done to ourselves. They have not been because of the absence of usable technologies, blockages to communication, or the tyranny of distance.

What is missing in the conversations today about international development—from economists, technologists, public health specialists?

It is the blind philosophers and the elephant problem. Economists miss the sociology. Sociology miss the economics and also the politics. Engineers miss the fact that the societal systems have to have the incentives for this stuff to actually be used in a way that’s worthwhile.

There are all kinds of ways in which things have gone horribly wrong. For example, think of 1650 in Poland, along the Vistula River. Holland was undergoing an economic boom. And so it was turning its grain fields from places where grain was grown to places where flowers were grown and where cows ate grass to produce milk to be turned into cheese. Suddenly, Holland needed a lot more wheat, which was easy to grow in Poland and, with better maritime technology, cheaply shipped to Amsterdam.

Was this a bonanza for the people of Poland? No. There work became more valuable, but they did not become higher paid. The nobles of Poland took the people and turned them into serfs. It was not a good time for Poland, even if it was a good time for “globalization,” in the sense of the rapid development of ways to grow more wheat faster in smaller spaces and then ship the wheat to places where it was very valuable.

Those are the kinds of things to look out for. Those are the kinds of things to fear.

What’s worked to take people out of poverty?

Land reform, nitrogen, and access to some place where you can sell your skills. What hasn’t taken people out of poverty is this kind of scenario: When the government of Mozambique prohibits the export of cashews to India, because it wants the products of the cashew trees of Mozambique funneled through four sets of South African entrepreneurs, each of whom runs one of the four cashew processing plants in Maputo and have a cartel agreement with respect to the price they will pay to cashew farmers.

What is the role of the university in all these complexities about economic development, whether locally or internationally?

To bring people up to speed on what the issues, opportunities, problems, and dilemmas are. To keep the conversation honest. To have a place where people can think and speak, without having to please powerful people by saying what they want to hear right now.

How do we create enduring prosperity rather than address just the symptoms of poverty?

This is a question that the Chandler Foundation (formerly known as the Cassia Foundation) has been grappling with over the years. On September 5, Leslie Lang Tsai, who serves as the assistant vice president and general counsel of the foundation, spoke at the Blum Center about the challenges of effective philanthropy and the road the Chandler Foundation has taken to achieve it.

As she addressed the packed room, Tsai, who earned a B.A. in Rhetoric and a B.S. in Business Administration from UC Berkeley, noted there are now more opportunities for Cal students to focus on poverty alleviation and social impact. When she graduated in May 2006, the Blum Center was just about to launch its Global Poverty & Practice minor and the Big Ideas student innovation contest. The landscape of poverty alleviation, particularly on the UC Berkeley campus, was shifting toward ideas about how to understand, build, and maintain effective programs, using a mix of history, social science, and technological innovation.   

Tsai started her talk with a thought experiment, asking the audience of largely undergraduate and graduate students: If you had one billion dollars, how would you use it to eliminate poverty and create inclusive prosperity?

Answers from the audience ranged from unconditional cash transfers to maternal health investments to comprehensive education programs, allowing Tsai to introduce the audience to the Chandler Foundation’s method for determining how to invest in effective organizations in the field. She recounted that Chandler Foundation Founder and Chairman Richard F. Chandler, who started his philanthropy in 1997, underwent “four seasons” of giving before deciding to apply a “Business House Investment Strategy” based on John D. Rockefeller’s idea that giving is investing.

Richard Chandler and his brother, Christopher Chandler, both successful investors, believed, per Andrew Carnegie’s maxim, “It is more difficult to give money away intelligently than to earn it in the first place.” Their first philanthropic venture, Geneva Global, became the first “philanthropic investment bank,” advising the donor community with the same level of advice they’d expect if they were making an investment.  

In subsequent years, Richard Chandler focused on operating social enterprises as well as supporting social justice leaders before he ultimately created the Chandler Foundation. Tsai said its grant-making program is based on three lessons learned from Richard Chandler’s prior social impact ventures: 1) address the root causes of poverty, not the symptoms; 2) “stay in our lane” as investors; and 3) have measurable impact and return on investment.

Tsai shared that the foundation’s model is to work collaboratively through partnerships. The Chandler Foundation is a founding donor of the Co-Impact collaborative, along with the Bill & Melinda Gates and Rockefeller Foundations, which aims to address global poverty through systems change solutions. The foundation’s approach also places a significant emphasis on encouraging all those involved to hew to the “values at the heart of property: humility, accountability, and integrity.”

Near the end of the program, a student from the Global Poverty & Practice minor asked Tsai how best to pursue a career in poverty alleviation. Tsai, who has worked in corporate law at Sullivan & Cromwell and in development at Microclinic International and the World Bank after internships at the United Nations, the African Development Bank, the Supreme Court of Rwanda, and the Special Court for Sierra Leone, shared that a typical career path in the social sector is not a straight line. She advised students to gain expertise and marketable skills in technical areas such as law, engineering, and business, or specific sector expertise in health or urban planning–and to not necessarily focus on how the nonprofit industry works.

Ultimately, she advised, “Develop marketable skills while following your passion and purpose.”

The video of Leslie Lang Tsai’s presentation about the Chandler Foundation can be viewed here.

By S. Shankar Sastry

Today, access to water, energy, health care, and financial services remain the greatest challenges to alleviation of extreme poverty, which affects nearly half the world’s population, more than 3 billion people. United Nations officials designed the 2000 Millennial Development Goals and the successor Sustainable Development Goals of 2015 to mobilize resources against the massive challenges. As such, the UN blueprints identify targets for progress in the four crucial areas of water, energy, health care, and wireless, along with the intertwining challenges of hunger, education, global warming, gender equity, environment, and social justice.

In many ways, the Millennial/Sustainable Development Goals are the most pressing problems of development. They are the challenges that must be of actionable focus for years to come. They are the wicked problems, as UC Berkeley Professor Horst Rittel coined them in 1973, “whose social complexity means that it has no determinable stopping point.”

Yet there are new and emerging technologies in our midst that are changing the 40-year dialogue about development interventions and disrupting the very idea of how intertwining problems can be “fixed.” These technologies are responsible for the many digital transformations that are revolutionizing the global economy. From banking and transportation to agriculture and health care, a multi-trillion information technology industry is in motion that is changing how human beings move, work, live, and think. This Information Age, this Third Industrial Revolution is leading over the next decade to an economic system in which more than 70 billion Internet of Things (IoT) sensors will be installed across all sectors to provide unprecedented volumes of data.

Of course, data is not water, energy, health care, or wireless communications access. Yet data can be inexpensively stored and processed, enabling the utilization of computer-intensive machine-learning algorithms that—if correctly directed—can bring down the cost of access to necessary goods and services. In addition, although artificial intelligence is still in its infancy, it is poised to make advances that will affect the development sector as much as the hospitality sector. Indeed, the trifecta of IoT, AI, and cloud computing offers a vision of digital transformation that will alter business models, services, and how every single person on the planet lives.

How might these digital transformations affect the poorest of the poor? How might they improve quality of life and access to goods and services? We at the Blum Center are focusing on how the next 10 years of digital transformation can be harnessed to provide new and sustainable solutions for extreme poverty alleviation. Here are some examples of digital transformations that we have invested in and tested to scale at the Center:

In Energy Access:

REPP Efforts to electrify rural communities in developing countries have been plagued by energy theft, unaffordable connection costs, intermittent supply, and poor maintenance. Despite ambitions of governments and donors to invest in rural electrification, decisions about how to extend electricity access to almost 1 billion people worldwide are being made in the absence of rigorous evidence. The Rural Electric Power Project (REPP) originally sought to address this problem by incorporating new technology, such as village-scale clean energy microgrids, as well as sustainable financing and distribution mechanisms to better serve the rural poor. REPP has been utilizing novel data collection and analysis tools to inform the redesign and refinement of the technology and rigorously measure impacts in the field. Researchers from the Technology and Infrastructure for Emerging Regions (TIER) group, the Center for Effective Global Action (CEGA), and the Energy Institute at the UC Berkeley Haas School of Business have been working with local government and industry partners to generate real-time user data (using “smart” meters) and to collect comprehensive household survey data before and after electricity deployment. Currently, in a partnership with Kenya’s Rural Electrification Authority, the researchers are studying the demand for and impacts of electrification in a large-scale, randomized controlled trial. By offering subsidies of varying amounts to “under grid” households—those located in close proximity to the national grid—the team is measuring people’s willingness to pay for power, and tracking what happens after they connect.

In Health Care Access:

CellScope. In developing regions, where health care infrastructure is limited, there is an urgent need for greater access to reliable diagnostic testing, particularly for infectious diseases. The objective of CellScope, invented by Blum Center Chief Technologist and Bioengineering Professor Dan Fletcher and his lab members, is to establish mobile digital microscopy as a platform for disease diagnosis that can be used by non-expert health workers to in remote settings. The mobile phone-based, easy-to-use platform can rapidly capture images blood, sputum, or other patient samples and wirelessly transmit the data to clinical centers, allowing the patient to be evaluated and treated at the point of care thanks to algorithms running on the phones, with data uploaded wirelessly (when connectivity is available) for epidemiological purposes and quality control monitoring. By using existing communication technology and infrastructure, CellScope moves a major step forward in affordably and innovatively taking clinical microscopy out of specialized laboratories and into field settings for disease screening, diagnoses, and treatment.

In Wireless Access:

Community Cellular Network. Today over one billion people worldwide live beyond the reach of cellular networks. Many live in sparsely populated rural regions, with weak power infrastructure—making it prohibitively expensive for most telecommunication companies to invest. Living outside the network means lack of access to important services like emergency communications, market price information, and job opportunities. To address this challenge, Computer Science Professor Eric Brewer and his lab members, developed the Community Cellular Network (CCN). The CCN is a complete “network in a box,” enabling remote communities to both own and operate their own cellular systems. Designed to be deployed by people with limited technical skills, CNN, which became Endaga under the leadership of Kurt Heimerl, costs less than one tenth the price of traditional cellular equipment, runs solely on solar or micro-hydro power, uses less than 50W average power draw, and can provide kilometers of coverage to rural communities. In 2015, Endaga joined forces with Facebook to scale Internet access to rural communities.

Many who follow these transformations in development are concerned about digital ethics, privacy, and fairness. We need to understand how AI (primarily machine learning and cloud computing) is being used to understand poverty and economic development in urbanization, population density, traffic demand, housing, crop yields, and food security, among other topics.

Questions of particular relevance to development include: Is it fair to be denied a program because the people you talk to on your cell phone make you look less creditworthy or less in need of a service? What rights do people have to privacy in an environment where satellites are photographing their homes, phones are tracking their locations and communications, and their moods are being analyzed on social media? And how much access to this type of data should development researchers have?

The fact is (per the economic concept of competitive equilibrium) if you give up more of your data, you may get lower prices. At the same time (per the Nash theory in economics) decisions about giving up data for individuals can sometimes be terrible for groups, causing users who have high privacy settings to “free-ride” at the expense of those with low privacy settings. Thus, if we want to optimize the utility of the common good around data sharing and AI in development, we may well need to institute societal side payments—means to induce recipients to take part in the transaction that are legitimate and corruption-free, and redress underinvestment in the common good.

This will take as much analysis, debate, and social justice action in development as in every other aspect of digital transformations. It is one of the Blum Center’s stakes in the ground for the 2018-2018 academic year and the years ahead at UC Berkeley.

Shankar Sastry is the Faculty Director of the Blum Center for Developing Economies. He is a Professor of Electrical Engineering and Computer Sciences, Bioengineering, and Mechanical Engineering.


By Veena Narashiman ’2020

Originally a portmanteau of the words hack and marathon, a hackathon typically occurs over a day or two, bringing together computer programmers and others to solve a puzzle or invent a creative solution. During these 24- to 48-hour periods, participants are encouraged to form groups and collaborate, completing the hackathon with a rough prototype or ideas that can be presented to judges for prize money. Over the years, the adrenaline rush that often drives these competitions have created some famous “hacks”: the messaging app GroupMe and the Facebook “Like” button were both conceived during hackathons.

Although hackathons may feel new, they are nearing their twentieth anniversary. The concept was born in June 1999, when UC Berkeley alumni John Gage challenged attendees of a Sun Microsystems event to write a multi-user Internet program in Java for the Palm V. Almost two decades later, hackathons have been organized to advance all manner of technologies in practically every sector. And increasingly, hackathons have been launched to solve societal challenges, such as natural disaster preparedness and government transparency.

But are “hackathons for good” really effective, given that rapid prototyping is rarely a fix for entrenched societal problems? For technologists like Luca Ibota, a former Apple employee who has been active in many hackathons for good, the most important aspect is “identifying the problem you have and the ideal outcome you want.” In fact, said Ibota, the key to a successful hackathon for good is “precisely defining a problem or challenge.”

Still, some Cal students are skeptical about hackathons for good. The most cynical argue that incorporating buzz words such as “social impact” and “corporate social responsibility” at hackathons is a smart public relations move for technology companies looking to improve their public standing. Other Cal students insist that incorporating social good goals in hackathons is a testament to Silicon Valley’s aim to think more holistically and ethically about technology’s effects.

For many, UC Berkeley hackathons that take on a social impact lens are seen as a reflecting a student culture that prioritizes hands-on learning and that seeks to solve grand challenges like climate change and food insecurity. For Swetha Prabhakaran, a UC Berkeley sophomore and computer science student, the 21st century requires companies, nonprofits, and individuals to make solutions to intractable problems a priority.

Either way, the number of UC Berkeley hackathons focused on social impact is on the rise. Causes have ranged from building prosthetics for people with disabilities to developing apps that enable students to source fair trade goods. Student-run organizations have championed these hackathons as a way to ethically fill consumer gaps.

In April 2018, a partnership between the Sutardja Dai Center for Entrepreneurship and the UC Regents Chancellor’s Association hosted Cal Innovates, a hackathon aimed to bridge the engineering and business disciplines. Prabhakaran, who organized the event, said attendance was high because engineering and business students have started to “soul search” for meaningful impact. “Berkeley students have a strong entrepreneurial spirit—you can see it everyday,” said Prabhakaran. “But conversations about using business to help others are happening on small scale. The hackathon is a way to help students do this on a bigger scale.”

The Cal Innovates hackathon presented no strict problem to solve. It allowed participants—of which 40 to 50 percent were engineering majors and 30 to 40 percent were from the Haas School of Business—to build and plan deployment of prototypes. During the competition, participants listened to speakers or pursued their project with the help of guides. Professionals from SkyDeck, Cal’s startup accelerator, helped students with presentations and judged the finals, while employees of GoDaddy and students from BlockChain at Berkeley helped participants with technical aspects of their designs. Finalists included a project for civil engineers in developing countries to create sustainable bridges.

Another example of a UC Berkeley hackathon geared toward positive social impact was EnableTech’s “Make-A-Thon.” Held in April 2018, it aimed to connect those building prosthetics with those who use them, per the club’s motto: “Build with them, not for them.” Spanning 48 hours, the event allowed participants, formed into groups of six people from different majors, to rank which of EnableTech’s active projects should be improved. Kyelo Torres, a rising senior in mechanical engineering and the event project leader, spoke of the hackathon’s purpose: “As students, we are taught only theories. The second we are asked to do something, we get lost. The idea of hackathons is to practice the real world aspect of things.”

Amy Dinh, programs manager of the Jacobs Institute for Design Management, said she believes the reason for the uptick in hackathons with a social good emphasis is simple: “People seek a challenge, and there’s nothing more challenging than the wicked problems of the world.” Yet she dissuades students from expecting implementable solutions post-hackathon, highlighting instead the importance of the iterative process. “The point of a hackathon is to get creative juices to flow,” she said. “It’s not realistic for the ideas to be polished; rather the point is to kickstart a new team or idea.”

By Tamara Straus

For the Pinoleville Pomo Nation of Ukiah, California, collaboration has not historically been a word used to describe interactions with white Americans. As late as 1950, native people were not permitted to walk on both sides of the street and signs in Ukiah’s storefront windows read, “No dogs or Indians allowed.”

Angela James, vice chair of the Tribal Council for the Pinoleville Pomo Nation, remembered this history was she was approached by David Edmunds, her tribe’s environmental director, about a possible collaboration with UC Berkeley. The goal was to co-design a sustainable housing project for the low-income families of her 300-person nation.

On the one hand, James, a mother of four, was eager to advance the education of young tribe members and teach them to live in two cultures. Yet her mind jangled with stories from her grandfather Smith Williams. He had told her about Ba-lay Ba-lin—the Bloody Run—an 1871 atrocity in which white settlers violently forced Native Americans off their land, turning the Eel River red with their blood. In 2007, when James first stepped onto the UC Berkeley campus to talk with Mechanical Engineering Professor Alice Agogino, now education director of the Blum Center and chair of the graduate group in Development Engineering, and graduate students Ryan Shelby and Yael Perez, she was aware that this was the place where Ishi, the so-called “last wild Indian,” became the research subject of anthropologist Alfred Kroeber. She also knew there was an ongoing dispute about the Hearst Museum’s return of 12,000 Native American remains to California tribes.

James’ warm-up to the UC Berkeley engineers was slow. She recounted that because Shelby is African American and Perez is foreign (Israeli), she felt they might be worthy of her community’s trust. She also wanted to believe that “science can cross cultural barriers,” and she observed from Agogino’s classroom that engineering was no longer “just a field for white males.”

At the same time, the interdisciplinary UC Berkeley group called CARES—Community Assessment of Renewable Energy and Sustainability—was seeking to tread new water in the field of development. “As we worked with the nation on the sustainable housing project, our understanding of development changed,” said Perez. “We realized technology, and technological ‘fixes,’ are not enough. We needed to start with what sustainability meant to the tribe. And they had a lot to say about sustainability, because of the way they view their connection to the Earth—resulting in unexpected design decisions around heating, water use, solar power, and the shape and functionality of their homes.”

This insight about collaboration led the CARES group to a development methodology called “co-design.” The term, which builds on human-centered design, user-centered design, design thinking, and participatory design, goes further in empowering stakeholders in the decision making and design process to recognize that users (or locals or recipients of development assistance) are key participants in their own economic, environmental, and sociopolitical advancement, with significant contributions to offer. In essence, CARES, a forerunner of UC Berkeley’s development engineering graduate program, embraced co-design to address the disconnect between the creation of technological innovations by engineers and the needs, preferences, and cultural views of the people who will use them.

Explains Agogino, “The 10-year collaboration with the Pinoleville Pomo Nation shows a number of things: It shows that development projects can and should be local, not just international. And it shows that development solutions can range from how we design to how we publish academic research. The journal articles that have come out of the PPN collaboration have notably been co-authored by PPN members.”

Since 2008, CARES has collaborated with the Pinoleville Pomo Nation on engineering, architecture, and educational projects that have tested the boundaries of development. Co-designed results have included sustainable housing, renewable energy power systems, water restoration and management projects, and most recently science, technology, engineering, art, and math (STEAM) workshops for middle and high school students and a K-12 maker space.

Like past collaborations, the recent educational one was the result of shared interests and available funding. Zhao Qui, project director of the Pomo Youth College and Career Success Project, explains that in October 2016 her organization received a Department of Education grant to fund new cultural and academic enrichment activities for native students; one area of concern was low access and achievement in math and science. At around the same time, the Blum Center received funding from the National Science Foundation to support development engineering students working on InFEWS (Innovations at the Nexus of Food, Energy, and Water Systems) for low-income communities facing extreme challenges. And the CARES team, energized by development engineering graduate students and Global Poverty & Practice (GPP) undergraduate students, was ready for a new collaboration.

The task for the co-design was to integrate native activities and sensibilities into STEM education. Says George Moore, a UC Berkeley mechanical and development engineering graduate student, who taught at the summer workshop, “It became clear in conversations with the PPN that it was hard to get the native students to apply themselves in the STEM disciplines. Institutionally, it just wasn’t structured for them. But these students got really engaged at the workshops and are really good at math and science.”

According to Moore—and other participating UC Berkeley students, including GPP students Dor Chavoinik, Grace Harrison, and Arielle Levin and Elena Duran, a PhD student in Graduate Group in Science and Mathematics Education—what works best is listening and not imposing views on what works in a STEM-based activities. Among the decisions were to teach engineering design through Pomo Pinoleville basket-making techniques and to engage students in 3D printing designs from local art and nature.

Qui says the workshops and maker space are generating excitement among the students to get into STEM fields. “We have a college career counselor coming to the classroom,” she notes. “The students have a sense these are high paying jobs. Yet for native people, we’re not just looking at the pay. We’re looking at how we can use the STEM program to serve our own community around solar power, rain catchment, and other sustainable and environmental solutions.”

For graduate student Pierce Gordon, the co-design approach is crucial for mechanical/development engineers like himself working in poor communities. Gordon says co-design is “de-colonizing,” as it simultaneously aware of the deep history of technological interventions and adamant that everyone be heard, understood, and acknowledged. Continues Gordon, “If we don’t do that, then we’re doing the very similar kind of harm that many people have done over the history of international development and interventionist work as a whole.”

Gordon, who is finishing his PhD dissertation, which includes case studies of co-design efforts in the United States and Botswana, says the first priority of development engineering work is not to get research publications, funding, or material for teaching classes, but to benefit marginalized communities. “It is to figure out what the community wants, because this research moves at the speed of trust. Once you build up that trust, you have the opportunity to build up to collaborations and research outcomes and beneficial activities that you didn’t even know could have existed.”

For Angela James, one very specific outcome of the 10-year collaboration is her children’s interest in STEM. “My daughter has been a participant in CARES since she was four. She’s 14 now. She’s very comfortable leaving Ukiah. She’s looking at a lot of different colleges. All her career interests are science-based. My son is right behind her and just the same.”

James, who was on the UC Berkeley campus on July 13, 2018 with a group of Native American high school students, says the days of cultural and educational isolation can end for her tribe and others in California. “My goal has been to open the minds of our youth and introduce them to college and science, and teach them how to build positive working relationships with people outside their immediate circle,” says James. “It is important that the university has the right individuals involved in a collaboration—people who are willing to advocate for the human approach, get to know the individuals, and ask about background and culture. An important part of this collaboration has been that our voice is finally being heard.”

Research about this collaboration was partially supported by the National Science Foundation’s Research Traineeship in Innovations at the Nexus in Food, Energy, and Water Systems (Award No. 1633740).

By Veena Narashiman

An injured soldier is rushed to a field hospital and is bleeding out. A surgeon needs to give the soldier meds to speed up her clotting. But too much or too little will kill her. The doctors rely on lab equipment to determine dosage; however, the large machine was never designed for field use. The surgeon is caught between an educated guess and blind dosing, putting the soldier’s life at risk.

This was the story that Jeffrey Lu and Johnathon Li heard from a U.S. Air Force vascular trauma surgeon. The two old friends, UC Davis graduate students in biomedical engineering and animal science, realized they had possibly stumbled upon a market gap for a mobile blood clotting monitoring device.

After conversations with UC Davis doctors, their hunch was confirmed. Not only did they learn that traumatic injuries which disrupt blood clotting are the second leading cause of preventable death in developed countries, they discovered that mobile blood clotting solution could had worldwide application—from the frontlines of the war in Syria to rural areas in Sub-Saharan Africa.

Lu and Li also learned that with current technologies, an injured soldier may not receive treatment for up to 24 hours; and in civilian hospitals, patient treatment can be delayed three hours. The technicians and surgeons they interviewed said they wanted a device they could use in the operating room, circumventing the time involved in sending samples to the lab. Surgeons especially complained that when they got back lab results, the information was often obsolete because the patient’s condition had changed from further bleeding out.

“Current [blood-clot testing] devices are like using microwaves to cook,” said Lu. “It works if you don’t move it, and occasionally they come out great, but more often than not you’re just going to be disappointed.”

Or as Dr. Joseph M. Galante, the trauma medical director at UC Davis Medical Center, put it: “Undiagnosed coagulopathy [bleeding disorder] in trauma patients is associated with greater transfusion requirements, longer intensive care unit and hospital stays, and greater incidence of multi-organ failure or death. Patients with uncorrected coagulopathy are eight times more likely to die within the first 24 hours following trauma.”

Lu and Li spent part of their graduate school years working on the project they dubbed Innovis Medical. The partners began to understand their competition, their possible business model, and the people they needed to cultivate to make the best possible medical device.

In October 2017, Lu and Li turned to the Blum Center’s Big Ideas student innovation contest, to further shape and fund their idea. Big Ideas is open to undergraduate and graduate students at all 10 UC campuses and had a contest category that fit their invention: Hardware for Good, made possible through the generous support of the Autodesk Foundation. The contest put them through a nine-month project incubation, mentoring, and application process that Lu and Li saw was crucial to their company’s development.

“In entrepreneurship, you’re not selling your idea, you’re selling your network,” said Li. “Big Ideas participants enter Berkeley’s well-oiled machine, and their biggest advantage is their network.”

By meeting new people and potential advisors, the Innovis Medical founders realized they needed to pivot their strategy. Lu and Li decided to prioritize the civilian market instead of battlefield situations and use more layman language to describe their product.

At the 2018 Big Ideas Pitch Day before winning a first place prize, Lu went into the specificities of the device:  “Our solution is a portable medical device that uses a solid state sensor to track an electrical property of blood known as bioimpedance as it clots. Our device produces graphs and data similar to the current state of the art device, but without the bulky sensor mechanical components. The sensor itself is a disposable cartridge with no mess to clean up, no chemicals to work with. With a solution designed specifically to mobility, blood clot tests are no longer restricted to laboratories but can be used in a battlefield, operating room and even the comfort of your own home.”

At the pitch, Lu further argued that tests during surgery, which take 30 minutes to receive back from the lab, could be performed in the operating room within four to 10 minutes. Post-surgery patients who previously needed to make a trip to the hospital every few weeks to have their blood thinner dosage checked, could run the tests themselves at home—much like diabetic patients who are able to track their own insulin levels.  

In January 2018, Lu and Li joined UC Davis’ Inventopia, a makerspace for startups, where they were able to witness the production of their device’s sensor. The next month, they attended Meet the Experts Night at UC Berkeley, whey they were connected to Rhonda Shrader, director of the Berkeley-Haas Entrepreneurship Program, who referred them to contacts throughout the Bay Area.

Innovis Medical estimates significant reach and cost savings. Its market could include an annual 672,000 U.S. military trauma cases, 15 million U.S. civilian cardiac surgeries, and 7 million disaster-related surgeries in the developing world. As for costs savings, Innovis estimates the 15 million annual civilian patients of cardiac surgery could save up to $7,000 per operation. In developing countries, Innovis believes its device could be crucial in setting where reliable energy and technicians may not be available.

Lu and Li recently expanded their business plans through the UC Berkeley Innovation Corps course and were accepted to the national I-Corps incubator for scaling university-based innovations run by the National Science Foundation.

The founders also have launched a collaboration with UC Davis Medical, where civilian and military surgeons are using the Innovis device to directly test human blood from cardiac patients alongside status quo devices. Lu said sensors are being deployed for clinical tests with the aim to iterate the device to address as wide a range of patients and blood types as possible. He and Li hope to get FDA approval by 2021.  

Blum Center Education Director Alice Agogino has been named winner of the Presidential Award for Excellence in Science, Mathematics and Engineering Mentoring, the government’s highest honor for mentors who have worked to expand talent in science, technology, engineering and mathematics (STEM).

The award was announced June 25 by the White House Office of Science and Technology Policy and the National Science Foundation. Agogino, the Roscoe and Elizabeth Hughes Professor of Mechanical Engineering at UC Berkeley, was one of 41 honorees to receive the award at a ceremony last week in Washington, D.C.

Professor Agogino has had a long and illustrious history of mentoring university students and junior faculty as well as engaging with local schools, museums and organizations to engage K-12 students in STEM topics. To support engineering students at UC Berkeley, she created a tiered mentoring network, in which senior doctoral students advise masters and undergraduate students. Over the years, she has been in high demand as a mentor by those who want to use their STEM educations for positive social impact. She also has built a reputation for designing courses that attract a high percentage of women and under-represented minorities.

At the Blum Center, Professor Agogino has been pivotal in creating the new field of Development Engineering, whose mission is to reframe development and the alleviation of poverty by educating engineering and social science students to create, test, apply and scale technologies for societal benefit. Development Engineering students, she has written, must learn “21st century skills”—interdisciplinary, team-based methods that are oriented to seeing problems from multiple viewpoints (quantitative, qualitative, ethnographic) and applying them through entrepreneurial pathways.

Professor Agogino is not new to awards. She is a member of the National Academy of Engineering and is the previous recipient of an ASME Ruth and Joel Spira Outstanding Design Educator Award “for tireless efforts in furthering engineering design education.” At UC Berkeley, she has received Chancellor Awards for Public Service, a Chancellor’s Award for Advancing Institutional Excellence and a Faculty Award for Excellence in Graduate Student Mentoring. She was elected a Fellow of the American Society of Mechanical Engineers, has won many best paper awards and has been honored with a National Science Foundation Distinguished Teaching Award and a AAAS Lifetime Mentor Award, the latter for increasing the number of women and African- and Hispanic-American doctorates in mechanical engineering.

Her work in decision-analytic approaches to engineering design led to a whole new field of research, and her research in mass customization became a patent-buster for licenses in database-driven Internet commerce. If that were not enough, Squishy Robotics, Inc., Professor Agogino’s startup company, recently was awarded a National Science Foundation Small Business Innovation Research grant to conduct research and development work on “Shape-Shifting Robots for Disaster Rescue, Monitoring and Education.”

Professor Agogino has explained that she was inspired to become a mentor due to her own experience at the University of New Mexico, where she was the only female mechanical engineering undergraduate student, and at UC Berkeley, where she became the first woman to receive tenure in her field. Professor Agogino uses a mentoring approach that she calls “designing for diversity.” By emphasizing the social impact of solving research problems, this strategy helps students feel connected to their work and motivated to persist in engineering.

By Veena Narashiman and Blum Center News

In 2013, the Blum Center and  the Center for Effective Global Action founded the Development Impact Lab, to launch the new field of Development Engineering and create a model for university-based poverty action labs. Since that time, the Development Impact Lab, with support from USAID, has tested over 135 innovations and engaged more than 500 students, 400 experts and 375 organizations, involving 16 universities in the United States, India and Uganda.

On June 4, key representatives from the network met at the Blum Center to discuss their five years of findings and outcomes. Temina Madon, executive director of the Center for Effective Global Action, summarized Development Engineering as enabling doctoral students from multiple disciplines to research and test poverty solutions as part of their dissertations. A panel entitled “Institutionalizing the Field of Development Engineering” included UC Berkeley Mechanical Engineering Professor Alice Agogino and Economics Professor Paul Gertler, who attested to the long need for such a PhD minor. Rachel Dzombak and Sophi Martin, who earned their PhDs at Cal and are serving as the Blum Center’s doctoral fellow and innovation director, respectively, also offered anecdotes about rising interest in Development Engineering. 

“Thanks to this new field, doctoral students considering international development now have a way to harness this aspect of their academic interests,” said Professor Agogino, who is chair of the Graduate Group in Development Engineering and Education Director of the Blum Center.

Professor Gertler gave an overview of the Development Engineering journal, an open access,  interdisciplinary publication that applies engineering and economic research to the problems of poverty. The two-year old journal, he explained, is giving scholars academic credit for novel research that previously had not been widely acknowledged or disseminated.

Katherine Dow, program manager of the Global Development Lab, said that the Development Impact Lab has helped USAID better understand emerging trends in science and technology for development and the role that university professors, researchers and students can play. She also said the UC Berkeley collaboration has helped bring quality data and data methodologies to government decision makers, allowing for a redefinition of problems.

Data gathering around energy reliability in Ghana was a focus of one session. Hana Freymiller and Jeffrey Garnett from the U.S. Government’s Millennium Development Corporation, gave an overview of its $535 million, five-year project in Ghana, which aims to decrease the country’s energy outages by 20 percent by 2021.  The Millennium Development Corporation is collaborating with the Development Impact Lab and UC Berkeley’s Lab11 to better understand where and when outages are happening in Ghana—using a mobile app called Gridwatch. GridWatch enables utility customers to automatically report outages through sensor technology on their cell phones. The data collected is more accurate in many cases than what the utility company can gather, and can show a variety of possible solutions for energy investment, energy savings, economic development, and improved quality of life.

“People are worried about the 1.1 billion people who don’t have access to electricity worldwide,” said UC Berkeley Business and Economics Professor Catherine Wolfram, a GridWatch project lead. “But what about those who don’t have reliable access? As urbanization trends move forward, it’s really important to understand reliability and measure how investment changes with reliability.”

The daylong conference also featured presentations by faculty and current and former PhD students associated with the Development Impact Lab.

UC Berkeley Bioengineering Professor Dan Fletcher summarized the progress of CellScope, an invention from his lab that adapts the camera of a mobile phone or tablet computer into a high-quality light microscope for disease detection in low-resource areas. Since 2008, Professor Fletcher has used CellScope to test more than 83,000 patients, analyzing the results in a dozen journal articles—and now is aiming to mass produce 10,000 CellScopes for use in rural areas in Africa. His insight was: “Don’t make technology for development as simple as possible; make it as automated as possible.”

Erin Kelly, a PhD candidate in Agricultural and Resource Economies at UC Berkeley presented a mobile phone application called SmartMatatu, designed to prevent the high incidence of traffic accidents among privately owned minibuses in Nairobi, Kenya. The application uses GPS and other mobile technologies along with affordable, off-the-shelf car sensor devices to collect and send location, ignition, route, distances, speed, acceleration and deceleration information, to show Matatu drivers when, where and how they are driving unsafely. According to a six-month survey of SmartMatatu users, the app has helped drivers raised their profits and reduce repair costs–demonstrating that visibility of data can influence driver behavior and productivity.

Danny Wilson, a Development Engineering alumnus, presented the outcome of his doctoral research: Geocene.com. With Development Impact Lab funding, Geocene has created hardware and apps for data logging and analysis. Wilson talked about findings from a survey of cookstoves users in Sudan in which people over-reported use of their indoor pollution-reducing stoves, making the survey findings unreliable. With Geocene, Wilson aims to create dashboards for monitoring cookstoves across many countries. The goal, he said, is to understand what are the best cookstoves for specific conditions, so people will actually use them. He noted that nearly two million deaths could be prevented annually by replacing cooking fires and inefficient, smoky stoves.

Susanna Berkouwer, a PhD candidate at the UC Berkeley Department of Agricultural and Resource Economics and the Haas School of Business’s Energy Institute, reported on the latest findings from the Development Impact Lab’s Rural Electric Power Project, which is utilizing novel data collection and analysis tools. She explained that Kenya is working on a last-mile connectivity project to power all households by 2020, and is collaborating with her group to better understand how energy access does (or doesn’t) lead to higher consumption, income, health and education. The results, she said, could empower both citizens and governments.

The other presentations included: Niall Keleher, a UC Berkeley School of Information PhD Candidate, presenting the results from Assistant Professor Joshua Blumenstock’s research applying machine learning to high-resolution satellite imagery to measure regional poverty in Africa; Chinmayee Subban presenting Berkeley Lab Water-Energy Resilience Research Institute’s progress on using charge-based salt water removal to clean brackish water; and Dana Hernandez, a Development Engineering student, summarizing UC Berkeley Civil and Environmental Engineering Professor Ashok Gadgil’s ongoing research on removing arsenic from groundwater.

“The Development Impact Lab has had a tremendous five years,” said Heather Lofthouse, the Blum Center’s director of special projects. “By partnering with USAID and other governmental and nongovernmental organizations, we have been able not only to generate new ideas—we have been able to implement real-world solutions.”

By Rachel Pizatella-Haswell, UC Berkeley Goldman School of Public Policy MPP ’18

Joshua Blumenstock is an Assistant Professor at the UC Berkeley School of Information, where he directs the Data-Intensive Development Lab, and a member of the Blum Center’s Development Engineering faculty. His research lies at the intersection of machine learning and development economics, and focuses on using novel data and methods to better understand the causes and consequences of global poverty. Blumenstock has a Ph.D. in Information Science and a M.A. in Economics from U.C. Berkeley, and Bachelor’s degrees in Computer Science and Physics from Wesleyan University.

What can remote sensing and geographic information system data and cell phone data tell us about a person living in poverty?

Blumenstock: We have partial answers to that question. The work that’s been done indicates we can estimate very basic things: population density, household average wealth, basic indices of relative socio-economic status. Of course, there are lots of different ways to measure poverty and inequality and welfare. People working in developing countries tend to like consumption because it seems to be most closely correlate to how someone is actually doing. There has been some work looking at whether you can estimate consumption and expenditures from remote data sources, and initial results are promising here too. Aside from measuring basic welfare, all sorts of work is being done to use these data to learn about migration, social network structure and the spread of disease, to give a few examples.

What can data tell us about poverty indicators such as the incidence or depth of poverty?

Blumenstock: What these models actually spit out are sub-regional estimates of welfare. We can define welfare however we want. In general, as long as you can measure it in the traditional way, you can use these non-traditional data and models to try to estimate it. However, depending on what you want to measure, and what data source you’re using – such as phone data or satellite data – your estimates may be more or less accurate. But once you have your estimate of the distribution of wealth, you can do all of the things you could do with traditional data. You can back-out the poverty incidence, Gini curves and other constructs you derive from the poverty distribution.

In what ways are these data sources limited in their ability to measure welfare or other things?

Blumenstock: I think we have to be careful because it is easy for people to get excited at the potential applications before really understanding the fundamental and practical limitations. Nonetheless, here are several margins where this could be a major improvement over the status quo. One is cost: it is a lot cheaper to collect cell phone data, for instance, than a nationally representative household survey, which costs tens of millions of dollars. Another is geographic resolution: budgets constrain the areas and number of people that you can survey, but satellites can quickly collect millions of images from a small region. Another is temporal resolution: again, because of the costs, you can only do a nationally representative survey every few years at best, but phone data gets updated every second and satellite data gets updated every day. So, if you can update your estimates of the things that you care about – the poverty incidence or the distribution of wealth – every day, that could be really useful. We can think about all of the applications: not just program targeting and impact evaluations but also program monitoring and disaster response. All of these things need up-to-date estimates of the distribution of welfare. Those are all of the reasons why I think people can be excited, including me, but we’re just at the very first baby steps of that long pipeline.

There are basically two canonical papers out there: one that I worked on and one that a Stanford group worked on. Using the most up-to-date data, what we show is that cell phone meta data can be used to estimate relative wealth very accurately. The group at Stanford shows that daytime satellite imagery can be used to do the same thing. They also look at consumption, and find similar results. However, both of those studies include a very small number of countries at one point in time. We have no idea yet if those models that you calibrate at one point in time can generalize into future points in time. To do a lot of the tantalizing applications, like monitoring and impact evaluations, the first step, which has not been done yet, is to show that these estimates can reliably allow for inference over time.

Poverty is heterogeneous across both space and time. Some of your work highlights the ability of machine learning to provide granular spatial assessments of poverty and assessments of poverty in real time. What are the implications of this for the delivery of poverty alleviation programs?

Blumenstock: I don’t think this is going to solve any of these age-old problems relating to the shallowness of quantitative estimates. There’s always going to be trade-offs between quantitative and qualitative research. There’s the famous quote that says, “Not everything that counts can be counted, and not everything that can be counted counts.” Here, it’s no different. There is a latent characteristic of people, which is welfare or well-being, and that’s what we want to measure. However, you can’t measure it directly. You can either embed yourself in a community and really get a sense for it, or, if you want to measure welfare at scale, you have to rely on these instruments that make observations about one dimension of things that we think are correlated with this fundamentally unobservable state. And what we’re doing is even one-step removed from that. We have these instruments that are already imperfect measures of that underlying state, and we want to try to replicate that using data that we get for free at true scale. At best, what we’re doing is trying to replicate those already imperfect instruments, which adds another layer of imperfection.

There certainly is nothing about what we’re doing that imposes homogeneity, though. We would never use a model that we fit on Rwanda and apply it to Kenya without knowing first how much we expect the model’s prediction to degrade by. Similarly, I would never expect a model that was fit in 2016 to be accurate in 2018. But that’s an empirical question, and one that we’re actively studying. Some of these are solvable problems, but I think there are these other unsolvable, philosophical questions like construct validity and if we’re measuring that thing that we care about. Those things are more fundamental.

Household income changes overtime due to income shocks throughout the course of a year. How do you view this as a mechanism to correct problems in real time? Could this inform programs to better smooth consumption and target across time as opposed to just one moment?

Blumenstock: I think there are some very compelling applications that look at inter-temporal consumption or changes in dynamics. For a lot of reasons, you might think that that’s a first order thing to target rather than a cross-sectional, stable measure of permanent income. In principle, this is exciting because with this line of research you can potentially get updated estimates at very high frequencies. Yet, that is a couple steps ahead of where we are now. In my mind, step one is seeing if data from a single point in time is accurate. We can sort of do that now. Step two is seeing if the estimates can remain accurate across different points in time. We haven’t quite gotten there, but we’re working on it. Step three is what you’re talking about: real-time estimates. I think those need to be done in that order. Unless we know the right way to generate dynamic estimates and, then, know the right way to layer those onto a real time streaming data set, real time estimates will be wrong. That won’t be for another few years.

You mentioned that you wouldn’t fit a model from one country to another country. What are the ways forward to potentially be able to generalize from one country to another using this data?

Blumenstock: Generalizability can mean a lot of different things. One is generalizing over space, like from one country to another or even within one country from one region to another. Another is generalizing over time. A third is generalizing from a population that you observe to a population that you don’t, even if it is in the same space at the same time.

Of the three, I think that generalizing from one country to another is the easiest. That is an empirical question. We can collect data from two countries, or 10 countries (I’m working on a project where we’re collecting data from 50 countries), and we can just see if we train the model in one country and apply it to another. Then, we need to determine if the degradation of the model’s estimates depend on things that we observe: whether the countries are on the same continent or how far apart they are; whether the ethnic composition of the two countries is similar; or if the distribution of wealth is similar or not. These are things that we can measure. So, we don’t want to just apply the estimates from one country to another, but rather, we want to have a sense for how to correct for translation errors, or at least know when and where such errors are likely to exist. We’ll hopefully have answers to some of these questions in the next few months.

We’re also actively working on this project to have a sense for the ability for phone- and satellite-based estimates to generalize over time.  But realistically, it will be a while until we have a conclusive answer.

The hardest one is generalizing from an observed to an unobserved population. That said, there are a lot of techniques from traditional econometrics that you might apply to this problem. If you know the process that governs whether someone is observable or not, then you can “reverse engineer” a statistical correction. For instance, if you only observe people from population A, you can only reliably estimate the distribution of wealth in population A. But, say you want to be able to estimate the wealth of population B, but they’re not visible in your data (because they don’t have phones, for instance). In this scenario, if you know something about how the distribution of wealth of population A relates to that of population B, you apply a transformation to the estimates of population A to get estimates of population B. These are not big data things or new data things. These are old problems with sample selection and construction, to which we have partial solutions.

What are some of the ethical concerns with using machine learning to track poverty that you’re confronting and how do you confront these issues, especially in consideration of the inherent vulnerability of those who your work is meant to serve?

Blumenstock: The thorniest ethical questions for me are more philosophical ethical questions: things like the legibility of populations and the possibility of misappropriation. Is it a good thing to make people easier to measure? What if an authoritarian regime takes the papers that I’m writing and uses them to weed out political dissenters? For these sort of questions, I try to look at the scale of negative use cases and positive use cases, and focus on problems where the positives outweigh the negatives.

Another important issue is privacy, in the sense that we often deal with data that people generate without a full understanding of how it can be used to draw inferences about them. Here again there is an ethical concern and a practical one. The practical one is easier to address: at least as far as our research is concerned, we do our work in a controlled research environment. We put in place rigid data protection procedures, like removing personally identifying information prior to conducting analysis, to ensure that, to the extent that we can, we are safeguarding the privacy of the people we study. But we can’t control the privacy practices of others, like industry or government. So, the ethical issues are bigger, and boil down to a similar calculus as I mentioned earlier – do we think the benefits outweigh the risks?

There’s an assertion that there’s tension between technocratic solutions and human-rights based solutions. Beyond the implications for poverty alleviation, in what ways does or could machine learning contribute to good governance or protection of human rights?

Blumenstock:  It could contribute in a lot of ways — both through the applications that have been developed in the last few years, as well as those that are on the horizon.

I can see why these “big data measurement” methods may seem more natural a fit for technocratic approaches. But bottom-up governance structures need data too. You need to know who your constituents are. A lot of the things that we’re measuring now are largely motivated by more of the holistic, softer things that have been off limits to technocratic fixes. For instance, we’re working on a project now that tries to quantify the extent to which violence disrupts the social fabric of places like Afghanistan — using phone data to observe the social fabric in ways that wouldn’t be possible with other methods. Technocrats are limited by what they can observe, and one of the things they have a hard time observing is community cohesion and fragmentation. If we can provide ways for people to more directly observe that then it can create a bridge between what technocrats are equipped to do and the more bottom up approaches to good governance.

World Development journal features the research of Evan Mills and the Blum-funded Lumina Project, which cultivates technologies and markets for affordable low-carbon lighting worldwide.

In this podcast, Blum Center affiliated faculty, Clair Brown, speaks about alternative ways of structuring an economy and measuring economic progress, based on the Buddhist values of sustainability, interconnectedness, capability and happiness. Click to listen to the podcast or learn about her book.