A Class for the Pandemic

When Rachel Dzombak and Vivek Rao began planning for the spring 2020 Development Engineering course “Innovation in Disaster Response,” part of their motivation was to get students to think about the use of technology during past disasters. But by early March, it was clear to Dzombak and Rao that the COVID-19 pandemic was increasing the relevancy of their class in ways no one could have predicted.

A Class for the Pandemic

When Rachel Dzombak and Vivek Rao began planning for the spring 2020 Development Engineering course “Innovation in Disaster Response,” part of their motivation was to get students to think about the use of technology during past disasters. But by early March, it was clear to Dzombak and Rao—who both earned PhDs in Engineering at Cal, have expertise in design and innovation, and lecture for the Blum Center and the Haas School of Business—that the COVID-19 pandemic was increasing the relevancy of their class in ways no one could have predicted.

For their 23 students—comprising even shares of graduates and undergraduates, technical and non-technical majors, and women and men—determining appropriate technological interventions to disaster-driven problems became visceral. And as the class moved online, connected by Google and Zoom instead of open studio space, the students observed how all manner of organizations were struggling to use technology to protect lives and livelihoods due to the fast-moving coronavirus.

Ethan Stobbe, a Master of Engineering student, recounted that the class started with different readings about drone technology. One reading was written for and by engineers whose view of drones was promotional and laudatory, and the other was written by and for government employees who warned about public policy problems presented by unmanned aerial vehicles.

“I realized there was this massive disconnect between the people who develop the technology and get excited about it and push it,” he said, “and the people who have to use technology to make life in a disaster zone more bearable. That’s the beauty of this class—to see both sides—and to understand how to bring technology that’s less than a decade old into a disaster response zone.”

Stobbe was assigned to the “cash disbursements” team with a fellow engineer and two lawyers. They included: Karen Olivia Jimeno, a Master of Development Practice and Fulbright student from the Philippines; Mozheng (Edward) Hu, a Master of Engineering student focused on product design from China; and Ifejesu Ogunleye, a Master of Development Practice student who trained in law at University of Manchester and the Nigerian Law School. As they conducted interviews about cash disbursement with representatives from FEMA, Give Directly, and other organizations, they were guided by Dzombak and Rao not just to focus on the mobile technology, but on “framing and reframing” their understanding of how to make cash disbursements more effective. 

Alex Diaz, Head of Crisis Response & Humanitarian Aid at Google.org, lectured to students on disaster prevention, response, and recovery, focusing on the roles of technology and governance.

The team’s first framing question was: How might we help streamline the disbursement of cash relief while maximizing its impact in disaster response? This prompted the students to question how the disbursement process works, why particular steps in the process are difficult, which organizations are the largest, and what existing standards govern the field. After conducting several interviews with practitioners, they learned that cash allocation can be enhanced through crowdsourced information and public accountability, but that targeting people is a challenge and enrollment and verification takes time. So they reframed their question to: How might we speed up the distribution of cash transfers by improving the enrollment of and verification process of disaster survivors?

The team’s final idea, which included a prototype website presented over Zoom in early May, was “biometric pre-registration” along with a policy guide to address legal concerns. The idea was to compel individuals in flood, hurricane, and other disaster zones to pre-register their biometric information on a website, in order to receive cash disbursements more easily in the event of a calamity. The point, argued the team, is to work around the problem of identification, as driver’s licenses, social security documents, and birth certificates often disintegrate in disasters. During their final presentation, the team acknowledged how seeing the rollout of the CARES Act, in which tax returns were used as a verification method, validated the need for solutions that enable quick access to cash for citizens.

Dzombak and Rao see the educational approach they offer to the cash disbursement and other teams as part of the emerging discipline of Development Engineering. “Development Engineering embraces complexity as a sub-discipline in itself,” explained Rao. “A lot of ways that design-based problem solving or technology-driven problem solving is taught—the problem isn’t engaged in a multi-dimensional way.”

Dzombak underscored that although the course teaches design methodologies, “The actual project is the focus and outcome of the class. The projects themselves demand that one builds technical and social fluencies and specifically how to move back and forth between the two to solve problems that matter.”

Dzombak feels strongly that STEM education needs more problem contextualization, more emphasis on ethics, and more rigor around collaboration and teamwork. She was drawn to Development Engineering during her PhD at UC Berkeley because she wants to see academic inventions tested and applied but also because she believes that well implemented technologies, devised in an interdisciplinary and collaborative way, can improve and even save lives.

Rao explained that there is a long orthodoxy in higher education that you must learn theory before exploring applied technologies or solutions—an orthodoxy that stems from the need for deep knowledge before tackling complex problems. “But there is also an urgency to many problems,” said Rao. “Students have a hunger for them and there are many ways to contribute to problems before you have a PhD in a specific field.”

Rao noted that the accessibility of technology is changing who gets to intervene in disasters and how. “The ability to manufacture a mechanical part would previously have required a high degree of fluency in several knowledge areas and toolkits,” he said. “Now, a rough prototype of that  product can be designed and built with a credit card and a few clicks. In many cases, the learning curve on technical tools has eased to the point where you can engage with tools and theory simultaneously and cater to students where they are.”

Dzombak noted that the augmented reality and data visualization sessions of their course would not have been possible four years ago when she and Rao were working on their doctorates. “Every student would have needed a background in programming and hardware in order to engage in that space. But given where toolkits are now, students were able to download software, do some reading, and then engage in a meaningful way.”

Since technologies will alway be advancing, Dzombak and Rao believe there is a growing space for people who are tech savvy but not tech specialized and can frame questions while leveraging the latest tools. “We’re trying to teach students how to learn how to learn in a very explicit way,” said Dzombak. “Because of the way jobs are shifting, people are going to be forced to get up to speed on new technologies and figure out how to use them to tackle problem areas.”

The student team that explored drone imagery is an example of this approach. They were excited to apply drone technology to fire mitigation in California. But after talking to fire chiefs, image processing researchers, and drone operators and designers, they surfaced several problem areas in which they did not have the expertise to make a contribution. For example, they knew that one of the challenges in using drone video footage during disasters is how best to parse the massive amount of data generated. And they also knew that drones suffer from flight mechanics and battery power issues during disasters, but those issues are best handled by drone manufacturers. Where could they make an impact?

One area where they found less activity is how to leverage public and private drone operation after the first hour of a disaster. The “Rapidash” prototype—developed by Master of Development Practice Student Aaron Scherf, Master of Engineering Student Wai Yan Nyein, Cognitive Science Student Meera Ramesh, and Data Science Student Jinsu Elhance—is an app that enables public and and private drone operators to collaborate during disasters by providing maps of high vulnerability areas and access by firefighters to this information. The idea is to get firefighters crucial information about the direction and density of a blaze as soon as possible and especially when public drones are too far away. 

Katie Wetstone, a Master of Development Practice student who was assigned to the “disinformation” team, said that this kind of idea formation has been a strength of the class. “We were given a structured way to process information after interviews and organize different insights,” she said. “This approach is different from other courses, in that we have more time to research and understand a problem space rather than jumping to a solution.”

Wetstone said it wasn’t until the last third of the class, after interviews with Alex Diaz at Google.org and Chris Worman at TechSoup, that her team homed in on the idea that disinformation is a “public sector problem in a private sector space.” They also realized that immediately after a disaster there is an “information vacuum period” when a lot of disinformation spreads, making people vulnerable to news that increases anxiety and bad decisions. 

“This whole problem is a balance between education, technology, and policy,” said Master of Development Practice Student Sadie Frank. “Until the policy mechanisms around enforcement and regulation of social media change, or until private social media companies make significant personnel investments, our best approach might be to teach people how to recognize and avoid disinformation.”

During the final projects showcase, the disinformation team presented “Compasio,” a downloadable device extension that filters potentially inaccurate information on social media through pre-verified accounts and geolocation. The software essentially warns users when information is suspect or unverified. 

Dzombak notes that “Innovation in Disaster Response” is not meant to jumpstart social enterprise ideas, such as new apps and web services, though it might. “The training is meant to prevent unintended consequences once students go into the workforce. That’s why we spent a lot of time on critical thinking, ethics and values, decision-making,  and teaming.”

Deniz Dogruer, an Engineering Education PhD Student and COO of Squishy Robotics, who served as the graduate student instructor for the course, noted that the range of disaster-related problem spaces students explored—drones, disinformation, evacuation, disaster documentation, and cash disbursement—made the course particularly complex to teach but also advantageous for development engineering training.

On Zoom: Innovation in Disaster Response Graduate Instructor Deniz Dogruer (upper left) and Course Developer-Lecturers Rachel Dzombak (upper right) and Vivek Rao (bottom).

Although the COVID-19 pandemic that forced the course online gave faculty and students a chance to consider the importance of technology during disasters, Dzombak said it’s been a “mixed bag.” 

“In some ways, it gives students an excellent way to connect with their learning. The disinformation team, for example, was inundated with so many examples of how their problem can manifest,” she said. “On the flip side, so many people think the future of education is purely online. But the intangibles that we’re trying to teach—collaboration, peer-to-peer learning, process iteration, emotional connections—are just drastically changed. I think the irony is that solving complex societal problems requires people collaboration as much if not more than advances in technology. We need to be present with each other, not just with the machine.” 

—Tamara Straus

Cruelest Month, COVID-19, and Fiat Lux

Around the UC Berkeley campus, there has been a plethora of COVID-19 responses that will help developing and developed countries alike.

Cruelest Month, COVID-19, and Fiat Lux

April is the cruellest month, breeding
Lilacs out of the dead land, mixing
Memory and desire, stirring
Dull roots with spring rain.

So began T. S. Eliot’s 1922 poem The Waste Land about madness and death, trauma and hope, and the confusing world of the early 20th century. A century later, we find ourselves in another cruel April, one witnessed and suffered by the whole world due to the coronavirus disease pandemic: COVID-19.

At the Blum Center, we like all centers and departments and schools have been shifting to online teaching, advising, and working—as well as closely following the spread of the disease to low-income countries and regions. As you know, the news is bad. The COVID-19 crisis threatens to disproportionately affect developing countries, not only as a health crisis but as a devastating social and economic crisis. 

For poor countries, the socioeconomic fallout from COVID-19 could take years to recover from, according to a United Nations Development Programme (UNDP) report released on March 30. The report warns that income losses are expected to exceed $220 billion in developing countries, and nearly half of all jobs in Africa could be lost:

“With an estimated 55 per cent of the global population having no access to social protection, these losses will reverberate across societies, impacting education, human rights and, in the most severe cases, basic food security and nutrition. Under-resourced hospitals and fragile health systems are likely to be overwhelmed. This may be further exacerbated by a spike in cases, as up to 75 per cent of people in least developed countries lack access to soap and water.”

But there is room for hope and more for action. As Berkeley Economics Professor Edward Miguel points out in a recent Cal news article, Africa has certain strengths for combatting COVID-19. Unlike much of Europe, the median age of many African countries is young: 20 years old. That could mean the proportion of people who die could be much lower in African countries. That might also be true for India, where the median age is 26.8. Miguel, who is faculty director of the Center for Effective Global Action, also notes two other strengths: Even though Africa is rapidly urbanizing, a large share of the population still lives in rural areas, where social distancing is more possible.

He continues: “Another strength is the regional experience in sub-Saharan Africa dealing with Ebola in the last five or six years. There was infrastructure put in place to screen people, to contain an epidemic. I know Ebola and COVID-19 are quite different, but that capacity building may help now. And Africa has 30 years of dealing with the HIV/AIDS epidemic. Partially due to local initiatives, partially due to global aid initiatives, African health systems are much stronger than they were 20 years ago, or 15 years ago.”

Still, there is much to fear and prepare for. Multilateral agencies, international foundations, and all manner of aid organizations focused on poor countries are moving funds and resources toward saving lives. A UNDP-led COVID-19 Rapid Response Facility has been launched with an initial $20 million; however, UNDP anticipates a minimum $500 million need to support 100 countries. The International Monetary Fund and World Bank have urged debt relief to poorer countries hit by the coronavirus pandemic, with bilateral creditors playing a major role.

“Many countries will need debt relief. This is the only way they can concentrate any new resources on fighting the pandemic and its economic and social consequences,” said World Bank President David Malpass at a March 26 meeting. Malpass reported that the bank has emergency operations under way in 60 countries and its board is considering the first 25 projects valued at nearly $2 billion under a $14 billion fast-track facility to help fund immediate healthcare needs. Meanwhile, the State Department and the U.S. Agency for International Development have pledged $274 million in health and humanitarian assistance. And Bill Gates is spending billions to set up factories that will make the seven most promising coronavirus vaccines. 

Around the UC Berkeley campus, there has been a plethora of COVID-19 responses that will help developing and developed countries alike. The first target of a new AI research consortium, the C3.ai Digital Transformation Institute (of which I am co-director), is research that addresses the application of AI and machine learning to mitigate the spread of COVID-19. Bioengineering Professor and Blum Center Chief Technologist Dan Fletcher and his lab members have come up with a way to adapt the fluorescence microscopy function of their mobile phone microscope, the CellScope, to assist in rapid testing. Fletcher and his colleagues have been working with virology expert Melanie Ott of the Gladstone Institute and CRISPR pioneer Jennifer Doudna, among others, to provide the rapid remote detection portion of the team’s CRISPR-based COVID-19 RNA detection method. Dr. Bertram Lubin, the Blum Center’s and College of Engineering’s senior advisor in health, has been working with a coalition of UC Berkeley engineers led by Mechanical Engineering Professor Grace O’Connell, emergency room doctors, and critical care pulmonologists to turn sleep apnea machines into ventilators. And Development and Mechanical Engineering Student Paige Balcom is in Uganda (where there are 55 ICU beds with oxygen for a population of nearly 43 million people), using her social enterprise Takataka Plastics to manufacture face shields for doctors and staff in the town of Gulu.

In this issue of the Blum Center’s Innovation Chronicle, we salute these and others working stop the spread of COVID-19 and educating the next generation of Berkeley changemakers. Fiat Lux!

Shankar Sastry is Faculty Director of the Blum Center for Developing Economies and Siebel Professor of Electrical Engineering and Computer Sciences, Bio-engineering and Mechanical Engineering at UC Berkeley.

 

Development Engineering Scholar Woojin Jung Finds Significant Discrepancies in Global Poverty Measures

Development Engineering Scholar Woojin Jung Finds Significant Discrepancies in Global Poverty Measures

Woojin Jung, an assistant professor in the Rutgers School of Social Work, credits her interdisciplinary education in social welfare, public policy, and development engineering for her award-winning research. In December, she was honored with the 2020 Society for Social Work and Research Outstanding Social Work Doctoral Dissertation Award for Combating Poverty Through Aid: A Critical Analysis of Alternative Models, which she wrote at UC Berkeley to fulfill her PhD in social work and development engineering. To find out more about Jung’s poverty measurement research and her contributions to development engineering, the Blum Center conducted the following interview.

Rutgers School of Social Work. Photo by John O’Boyle

Your dissertation examines the discrepancies between different global poverty measures and brings that analysis to bear on identifying the salient dimensions of poverty in developing countries. What were your most surprising or meaningful takeaways from this analysis?

One surprising finding is that the discrepancies between the two approaches to poverty were larger than I thought. For instance, in Cambodia in 2010, only 10 percent of the population was poor by a $1.90 poverty measure, but almost half of the population was living in poverty by multidimensional measure. In development agencies, when it comes to the usage of indicators, income measures dominate but this study shows that each measure requires attention. How to incorporate multiple measures is another issue. Policymakers and research communities can juxtapose various measures one by one, taking a dashboard approach, but I want to take a systemic account of discrepancies. It was interesting to me that exceptions and mismatches between measures are not always bad but may serve as interesting sources of information and have the potential to be used as a policy instrument.

The most unexpected finding was that some evidence of the match between needs and policy intervention, which I would call the diagnosis and prescription match. My study finds that the “capability poor” countries receive marginally higher social sector aid relative to economic sector aid.[1] Social sector aid aiming to address capability poverty has skyrocketed since the beginning of the 2000s, significantly outpacing the economic and production aid. The result of the analysis tells us that higher rate of social sector aid is not uniform but more in countries where poverty is more multidimensional. Further research can expand this discussion by analyzing whether the considerable policy shift favoring the social sector was in response to the growing rate of “capability poor” countries to “income poor countries” or in response to the large magnitude of capability poverty as relative to income poverty. As for the individual country, more attention can be paid to outliers lacking the diagnosis and treatment match[2]

Given what you know about discrepancies between measures of international poverty and advances in technology to better measure poverty, how can the development community better distribute aid in, say, Myanmar, where you focus some of your paper?  

I would say that development communities should be more clear and consistent about the definition and concepts of poverty and policy responses to address poverty. Rhetorically, the development community calls for tackling “poverty.” However, in terms of aid targeting, they equate the meaning of poverty with low gross national income. Strictly speaking, poverty and low gross national income inform needs from different angles. The poverty rate exclusively focuses on those falling below the poverty line and reflects the distribution of income (and dimensions of other wellbeing). However, average national income, which is a measure of central tendency, takes account of everyone’s income, and the super-rich can move the mean upward. In my previous study, I found out that aid per capita per country is explained by GNI per capita and population, but poverty rate does not have any significant explanatory power, or even if it does, it is in the negative direction (the poorer, the less aid). The ways economic growth and national income translate into poverty reduction differs by country; both income and poverty should be taken together. For instance, among countries with a similar average income per capita, should not those with a large proportion of poor be receiving more aid?

I also think that development communities should take advantage of the advancement of technology to measure poverty. We can validate and test the performance of new poverty measures through supervised learning, triangulate alternative measures, and use them to impute missing data. I found that the areas with the highest needs often have the least certain data, spatially and timely irrelevant. When serving these areas, even if the development community uses their best intentions, it is left with ad-hoc decisions to pick beneficiary communities. When the World Bank and Korea International Cooperation Agency started their community-centered development (CCD) projects in Myanmar in 2012-2013, the country didn’t have any reliable income and consumption data to identify the most impoverished townships or villages. The country’s first DHS data became available in 2015 and 2016, but proxy poverty measures such as the wealth index[3] are available in only 441 village clusters. Using geospatial interpolation techniques or poverty prediction techniques using satellite imagery, development communities can better pinpoint where the poor are and fill the development gaps using global social welfare program—development aid.

Your study concludes with a call for social work research and practice to return to the basics, and to begin by considering client needs. Why are you compelled to make this call?

Actually, I am speaking to the broad field of social science, including social welfare/social work and development engineering. I was compelled to make this call because a particular way of generating evidence may have obscured broader lessons. The knowledge continuum of a development project is composed of need assessment, implementation, evaluation, and policy uptake. Each piece of evidence can contribute to creating a holistic sense of impact. There will be a cost involved in putting too much emphasis on one of the continuums (e.g., outcome evaluation), a specific sector (e.g., health), or scope (micro approach). For instance, rigorous experimental studies can tease out socio-economic impacts of interventions but are less likely to recover quantities that are useful for policy.

Similarly, too much emphasis on outcomes can result in disproportionate aid allocation to sectors with easy-to-measure outcomes, such as health, HIV/AIDS prevention, while stifling innovations with hard-to-reach populations. With the promise of the big data revolution, questions also arise over the value added—other than confirming what’s already been known—in the international development context. Many development projects have failed because they did not simply pass the scrutiny of the very first test: Does the intervention take precedence over all competing resources for individuals and communities in extreme deprivation? Is providing a laptop for a child really a priority for children suffering from lack of water or food and in a village without electricity?

The sub-field of social welfare/social work is heavily leaning towards health science while the sub-field dedicated to anti-poverty policies has been losing its ground, particularly in the U.S. Still, I am not quite convinced why studies covering individual health outcomes such as patients experiencing depression or sleeplessness are more likely to be funded than inquiries about poverty, inequality, or structural impediments to finding decent work, which might affect billions of people and many other social problems. Part of the reason would be the substantial funding streams exclusively earmarked to the health sector with concrete indicators for success. Science that advances health is important to both the rich and the poor, but science that reduces poverty would be only an issue for the poor. I think such an imbalance in social welfare and in social science as a whole can be partly remedied by going back to basics, starting from client and user needs.

Tell us about your effort to combine fine-grained spatial techniques with satellite imagery to assess aid allocation in data-sparse communities in Myanmar. What did that involve, and what did you discover?

My efforts focused on creating poverty variables, combining spatial analysis and remote sensing methods. They involve the entire process of data science techniques—atomized data collection, the representation of non-traditional data, downstream machine learning tasks, and data visualization. Like in many other countries, Myanmar does not have poverty data at a small community level where aid projects are taking place. This would make it difficult to say whether aid-receiving communities are poorer than non-aid receiving communities or whether aid volume is explained by the degree of wealth. I used spatial interpolation techniques to overlay the gridded wealth field onto the georeferenced aid project locations, so that we can estimate the level of poverty in project villages as compared to non-project villages. The fine-grained spatial analysis also allows measurement of poverty at a small scale such as a 5 km by 5 km square grid depending on the resolution of the images, and it does not depend on administrative boundaries. What I also found interesting is that there are multiple ways of measuring poverty or needs broadly so that we can link needs and interventions. One of those is a distance to conflict areas from project villages, a measure of need relevant to fragile and conflict-prone countries. Beyond spatial interpolation, I also use nontraditional data sources such as daytime and nighttime satellite images. For instance, annual average nighttime luminosity across Myanmar was extracted from raster/image files and was trained to predict poverty using a convolutional neural network.

Through this new approach, I discovered mixed evidence in needs-based targeting. Community centered development (CCD) in Myanmar disproportionately flows to better-off communities, as indicated by a lower share of vulnerable populations per township and areas that shine brighter. However, unlike the literature that argues that aid favors the richest, my study suggests that a need-based allocation is also in place in Myanmar, at least for community-centered development, an aid instrument known for its emphasis on participation and inclusion. The previous studies used aggregated poverty measures at the state level, which is the highest administrative level, across African countries. Within villages of similar levels of population and electrification, aid goes to areas with low assets. The analytic tool I developed also helped me answer other questions. I found that the donor’s ideology shapes the design of aid projects design and project design matters in targeting. One CCD project concentrates on poorer regions, while the other project supports villages close to conflict zones.

Why did you choose to get a designated emphasis in development engineering? What did the field bring to your dissertation and how might it shape your academic career?

With a policy analyst background in development agencies, I wanted to continue work on international development and was about to start a concurrent MA in economics while earning a PhD. At that time, I also discovered the development engineering program and sought advice from Dr. Clair Brown to weigh in. I like what the program is aiming for—that is, addressing poverty by emphasizing human-centered design, adapting technology to local needs, and scaling up interventions. So I decided to take a route to development engineering.

I took core development engineering courses and was connected with innovative projects and their research teams, such as the Darfur Cook Stove project. That inspired me a lot, so for the last chapter of my dissertation, I wanted to survey “technology-informed data-intensive projects” (e.g., Development Impact Lab projects supported by the Blum Center) and interview principal investigators. However, after the discussion with the Blum Center, I realized that there is no centralized reservoir/data warehouse to collect such data. Due to this obstacle in doing a study of other studies, I thought, “Why don’t I get involved in data-savvy research?” and I ended up doing such research. The rigorous core and elective course of development engineering paved my way toward building data fluency and programming skills.

As I acknowledged in my dissertation, being part of the development engineering group has expanded my area of interest to the application of technology for social good. I really benefited from the marriage between STEM and social science education. For instance, I drew my aid occurrence and density outcome variable from spatial differences in African elephant densities. The development engineering program helped me select rigorous data science and impact evaluation courses to promote my analytic skills. It put me in touch with faculty members from various disciplines. The guidance and mentorship from my advisor, Dr. Brown, as well as Dr. Agogino and Dr. Levin, have been strong. Dr. Brown has been nourishing my scholarship in every way from the formulation of the research question to coaching for a job interview, to following up with article submission. The NSF INFEWS fellowship was also a tremendous financial support to pursue my dissertation.

The data science training and my interdisciplinary background with social welfare, public policy, and development dngineering will profoundly shape my academic career. I believe my unique contribution to the field is showing how to harness technology and data to identify the needs of the most impoverished in the world—from the eyes of social work, as well as for its direct work experience with clients.

—Tamara Straus


[1] Particularly low policy score (CPIA) countries receive more assistance to the civil service and governance subsector, which was a sub-sector that led to the increase in aid to the social sector.

[2] For instance, Zimbabwe in 2016 received a higher ratio of social sector aid (USD 151) despite its income poverty status. In contrast, Sudan in 2010 received a lower rate of social sector aid (USD 6.77) despite its capability poor status.

[3] Although the wealth index cannot be used directly to construct benchmark measures of poverty, these asset-based measures are capable of capturing a household’s long-term economic welfare in poor regions lacking consumption, expenditure and price data.

Why We Are Expanding the Field of Development Engineering

Why We Are Expanding the Field of Development Engineering

By Shankar Sastry

This winter, the Blum Center was among the many groups in academia and development to celebrate the recipients of the Nobel Prize in Economics. Professors Abhijit Banerjee and Esther Duflo of MIT and Michael Kremer of Harvard were lauded for their innovative use of randomized control trials and behavioral economics to evaluate the effectiveness of global poverty interventions—and for a body of scholarship that has transformed the field of development economics.

Stated the Royal Swedish Academy of Sciences: “This year’s Laureates have introduced a new approach to obtaining reliable answers about the best ways to fight global poverty. In brief, it involves dividing this issue into smaller, more manageable, questions—for example, the most effective interventions for improving educational outcomes or child health. They have shown that these smaller, more precise, questions are often best answered via carefully designed experiments among the people who are most affected.”

One of Banerjee, Duflo, and Kremer’s innovations—strengthened by other leading development economists like UC Berkeley’s Edward Miguel—is to emphasize the importance of field work and the contribution of teams. Previously, development economists worked largely in isolation; today, their studies often include dozens or even hundreds of people representing government, nonprofits, civic organizations, and private firms. This approach leads to greater transparency of both the data collected and the methodology used, as well as a richer inquiry into which poverty reduction programs and policies should be studied and whether or how they should grow.

At the Blum Center, we are studying how advances in development economics are part of a new and emerging field, which we call “global problem solving” and “development engineering.” This field is responsive  to the UN Sustainable Development Goals and to the fact that, in many cases, we have the scientific and technological tools to meet the United Nations’ 17 goals but not the financial will or transformative tools for changing people’s behavior to achieve them. Development engineering builds on what development economics has revealed—which poverty interventions are succeeding—and then modifies or scales or re-invents them for implementation elsewhere.

In this way, development engineering is both deeply indebted to development economics as well as a transdisciplinary field for our time. Its rigor is in understanding complex societal challenges—such as the need to build earthquake and typhoon-resistant homes around the globe—and then devising the technological, cultural, financial, policy tools, and work force development to implement these problem solutions.

Elizabeth Hausler, who received her PhD in civil and environmental engineering from Cal, and went on to found Build Change to empower people to live and learn in safer homes and schools, is an exemplary development engineer. When she visited the Blum Center recently, she said her organization’s greatest challenge is not in seismic technologies but in all that surrounds resilient construction in developing nations: community buy-in, policy frameworks, government advocacy, financial product availability and affordability, and ensuring local construction workers are well trained.

Hausler called her efforts “Money, Technology, People” or “The Financial, The Technical, and the Social,” describing a kind of holy trinity of development engineering demands. Another way to describe development engineering is that it enables iterative problem identification and solution formulation propelled by interdisciplinary teams. In essence, we are advocating a transdisciplinary approach that combines the insights-oriented rigor of development economics with the solutions-oriented rigor of engineering. We also aim to integrate business, natural resources, public health, and social sciences into development engineering in order to appropriately and ethically create, implement, and scale new technologies to benefit people living in resource-deprived regions.

Over the next year, the Blum Center will take steps toward realizing the promises of development engineering by partnering with the College of Engineering and the Haas School of Business to hire two tenure track professors. One will be an assistant professor whose focus area may include: engineering better health, the nexus of food, energy and water systems, accessible low-cost energy technologies, the digital transformation of societal systems, climate change mitigation, or sustainable design and communities. Applicants will be hired 50 percent into the Blum Center and 50 percent into a home department in Bioengineering, Civil & Environmental Engineering, Electrical Engineering & Computer Sciences, Industrial Engineering & Operations Research, Materials Science & Engineering, Mechanical Engineering, or Nuclear Engineering.

The second hire will be an assistant, associate, or full professor in Entrepreneurship in Developing Economies who will split his or her time between the Blum Center and the Haas School and whose research topics may include productivity, innovation, small and medium-sized enterprises, financing for entrepreneurial activities, start-ups, venture capital funding, incubators, and policies to promote new businesses.

These professors will help us realize the promises of development engineering and be leaders, with their future students, in the achieving the UN Sustainable Development Goals.

Shankar Sastry is Faculty Director of the Blum Center for Developing Economies and NEC Distinguished Professor of Electrical Engineering and Computer Sciences at UC Berkeley.

Empowering Women of Color in the Medical & Technology Field

Empowering Women of Color in the Medical & Technology Field

Although Maria Artunduaga, a Colombian-born translational physician and entrepreneur, says that racial and gender bias has played a major role in shaping her career, she doesn’t view it as an obstacle. Instead, she views such experiences as motivation to close the gender and racial gap, particularly in Silicon Valley.

Echolocation Technology that Empowers the Blind

Echolocation Technology that Empowers the Blind

Darryl Diptee used to think of himself as a “closet innovator.”

During his time as an officer for the U.S. Navy, Diptee remembers being told to “color inside the lines and innovate on your own time.” After coming to UC Berkeley in 2018 to pursue a Ph.D. in Education, Diptee found himself in an environment that required the opposite.

What It Means To Be First Generation LatinX in Medical School: An Interview with Leilani Gutierrez-Palominos and Karla Tlatelpa

The Blum Center reached out to Karla Tlatelpa and Leilani Gutierrez-Palominos to ask how the Global Poverty & Practice minor helped shape their understanding of and participation in the medical field.

What It Means To Be First Generation LatinX in Medical School: An Interview with Leilani Gutierrez-Palominos and Karla Tlatelpa

Karla Tlatelpa and Leilani Gutierrez-Palominos, UC Berkeley graduates who majored in Molecular and Cell Biology and minored in Global Poverty & Practice, have recently been admitted to the David Geffen School of Medicine at UCLA. They are attending UCLA’s Program in Medical Education-Leadership and Advocacy (PRIME-LA), which enables students to focus on underserved communities. Tlatelpa and Gutierrez-Palominos are both first generation college Latinx women who have defied odds and pushed through barriers to get to where they are now. The Blum Center reached out to Tlatelpa and Gutierrez-Palominos to ask how the Global Poverty & Practice minor helped shape their understanding of and participation in the medical field.

What inspired you to join the Global Poverty & Practice minor?

Leilani Gutierrez-Palominos: I wanted to apply a critical social lens to my understanding of poverty and inequality. I have experienced poverty on a downstream level, but I wanted to learn what upstream factors caused the poverty I had witnessed. My existence in this country, as a previously undocumented immigrant, is inherently political. Thus, I am personally invested in advocacy efforts regarding underserved communities. My clinical and personal experiences have shown me patients’ desire to feel represented and understood, both through language and culture. In addition to having my background drive my passion for addressing inequalities, minoring in GPP provided me with the historical, political, and economic knowledge necessary to analyze and address systemic forces contributing to poverty.

Karla Tlatelpa: Growing up, my family experienced many injustices that, at the time, I thought were only happening to us. As I grew older and learned more about the systems in which we live, I began to understand that our circumstances were not isolated and were part of systemic problems that other families like mine were experiencing. We were a low-income family of undocumented immigrants, so my parents worked two to three  jobs at a time to keep us economically afloat. From the ages of 7 to 15, I worked 12-hour days with my grandma on weekends selling candy at the Oakland Coliseum flea market to help contribute to our food budget, especially since being undocumented meant we did not have access to social services like SNAP. With limited access to health care due to a lack of health insurance, my family’s health problems would sometimes go unattended. As I entered UC Berkeley, I wanted to gain a framework that would help me understand the disparities families like mine experience as a result of limited economic and social rights. On orientation day, I came across a student tabling for the Global Poverty & Practice minor and was immediately hooked!

How has the GPP minor changed your perspective on the field of medicine, if at all?

Gutierrez-Palominos: The GPP minor has made me more socially aware and fostered my sense of seeking to serve underserved populations. The minor has allowed me to delve deeper into wanting to understand upstream social determinants of health, which encouraged me to apply to the PRIME program at UCLA. I will be weaving an additional Master of Public Health year into my four years of medical education.

Tlatelpa: GPP helped me understand the role I will have as a physician beyond the clinical setting. I’ve always known that physicians are highly respected members of society, but GPP highlighted the extent of my privilege as a future physician. After GPP, my drive to study medicine shifted from a desire to help individuals in my community to also include a sense of responsibility to use the power and influence that being a MD provides to push for positive social change.

What lessons from GPP will you carry forward into your medical education and career?

Gutierrez-Palominos: Through the GPP minor, I considered the economical, social, and political dimensions involved around engaging in poverty work—which is relevant to my aspiration of providing care in low-income areas as a doctor. The GPP minor focuses on processes, such as the process of grappling with newfound concepts, which helped to further develop my critical thinking skills. Knowing that poverty doesn’t have a simple solution, I remained humble when engaging in poverty alleviation work since I always had to consider further implications, possibilities, and ways to improve. I became more conscientious of the decisions I made in ethical consumption, my support for certain organizations, and evaluating the effectiveness of certain methods/approaches when serving impoverished communities. Lessons of humility and critical thinking is what I will carry forward.

Tlatelpa: One of the greatest lessons GPP taught me was to always ensure I include the community’s voice in decision making that will affect them directly. As a medical student and eventually a physician, I will be regarded as an expert in many situations. However, I will take the teachings from GPP and my practice experience and remind myself and my colleagues that community members are the experts of their own lived experience and should always be included in the decision making process.

What’s the most important thing people should know about you as a Latina entering the world of medicine?

Gutierrez-Palominos: My clinical and personal experiences have shown me patients’ desire to feel represented and understood, both through language and culture. Underrepresentation causes low-income Latino communities to mistrust the medical field and lack mentors they can seek for guidance. Thus, this encourages me to gain more representation for my community and underserved communities like the ones I come from. There are few  Latinas in medicine; at UCLA medical school I am not only representing myself, but a greater community—both the village it took to continuously support me on this journey and those who will come after me.

Tlatelpa: There are few Latinx in medicine; this field is certainly not representative of the general population. This meant that when my family had health insurance, we did not usually have medical providers who shared our language or culture. Being a Latina in medicine means that I will have the unique opportunity of improving health outcomes in the Latinx community and relate to my patients in the way my family would have liked to with our own physicians.

What do you hope to accomplish for yourself, your family, your community, or the great world in becoming a doctor?

Gutierrez-Palominos: I hope to have the agency to help in situations where a medical professional is desperately needed. For example, experiencing death and disease in my own family that could have been prevented had there been a doctor. I want to be an advocate for my community and give back to low-income areas like the ones I come from. Due to my background, my ultimate goal is to work in under-resourced global communities involving poor migrants.

Tlatelpa: In the future, I see myself working as a primary care physician in under-resourced, largely Latinx communities. I also see myself working at the policy level to increase access to healthcare for everyone, including undocumented and socioeconomically disadvantaged folks. As part of the Program in Medical Education-Leadership & Advocacy (PRIME-LA) at UCLA, I will take time off from medical school to pursue a Master’s degree in public policy. Through this additional training, I hope to gain the tools necessary to advocate effectively for my patients’ economic and social rights and to carry out policy work that may institutionalize protection for under-resourced communities to access care and other vital social services. As a physician, my voice will carry more weight and increase the impact I could have at the policy level to create changes that will positively affect people beyond those I can reach during individual consultations.

—Dalia Elkhalifa 

Fletcher Lab’s Mobile Phone-based Microscope for Neglected Tropical Diseases Receives Gates Foundation Support

The Bill & Melinda Gates Foundation awarded a grant to Berkeley in July 2019 to support the scaled-up production of the LoaScope, a mobile phone-based microscope developed by Blum Center Chief Technologist Daniel Fletcher and researchers in his bioengineering laboratory, to enable mapping of Loa loa prevalence and intensity in Central and West Africa.

Fletcher Lab’s Mobile Phone-based Microscope for Neglected Tropical Diseases Receives Gates Foundation Support

The Bill & Melinda Gates Foundation has awarded a $1.9 million grant to Berkeley to support the scaled-up production of the LoaScope, a mobile phone-based microscope developed by Blum Center Chief Technologist Daniel Fletcher and researchers in his bioengineering laboratory, to enable mapping of Loa loa prevalence and intensity in Central and West Africa. The LoaScope uses video from the mobile phone-based microscope to automatically detect and quantify infection by parasitic worms in a drop of blood. 

Loa loa, commonly referred to as African eye worm, is passed on to humans through the repeated bites of deer flies in West and Central Africa rainforests. Knowing whether someone has a Loa loa infection and the intensity of that infection is critical for mass drug administration efforts to eliminate onchocerciasis (river blindness) and lymphatic filariasis (elephantiasis). There may be more than 29 million people who are at risk of getting loaisis in affected areas of Central and West Africa, according to the Centers for Disease Control and Prevention.

The Fletcher Lab’s original device was developed with support from the Blum Center, USAID, KLA-Tencor, and the Gates Foundation to enable safe treatment of River Blindness with the potent anti-helminth drug ivermectin in regions co-endemic with Loa loa. The new project will update 30-year-old maps of Loa loa infections in partnership with the Task Force for Global Health. Fletcher, who is UC Berkeley’s Purnendu Chatterjee Chair in Engineering Biological Systems, said the mapping is necessary to identify regions where mass drug administration for River Blindness can be carried out safely and where precautions due to Loa loa co-infection may be necessary. 

The LoaScope uses video from the mobile phone-based microscope to automatically detect and quantify infection by parasitic worms in a drop of blood. 

Among the LoaScope’s proof of impact is a November 2017 New England Journal of Medicine paper co-authored by Professor Fletcher and an international team of researchers describing how the device was used to successfully treat more than 15,000 patients with ivermectin without the severe adverse events that had previously halted treatment. 

“This is not just a step forward for efforts to eliminate river blindness,” Professor Fletcher told Berkeley News in a November 2017 article, “but a demonstration that mobile microscopy — based on a mobile phone — can safely and effectively expand access to healthcare. This work sets the stage for expanding the use of mobile microscopy to improve diagnosis and treatment of other diseases, both in low-resource areas and eventually back in the U.S.”

The Role of Data Science and Machine Learning to Combat Human Trafficking

The Role of Data Science and Machine Learning to Combat Human Trafficking

The International Labour Organization estimates that there are 40.3 million victims of human trafficking globally. With the rapid adoption of social media platforms, human traffickers have the potential to target more vulnerable children. Yet artificial intelligence and machine learning also have the potential to thwart more predators and protect potential victims.

On April 26, the Anti-Trafficking Coalition at Berkeley, a Blum Center IdeaLab, gathered researchers and advocates from academia, industry, and the nonprofit sector to discuss how AI can help prevent child exploitation and combat human trafficking. The panelists included: Bob Rogers, expert in residence for AI at the UCSF Center for Digital Health Innovation; Lisa Thee, vice president of Bark.us, a child monitoring app; and Roger Martin, former Chief IP Strategist of Qualcomm and co-founder and CEO of the charity platform Enduragive.

Martin explained that preventing initial online communications between vulnerable children and suspected traffickers is a significant intervention. “Since 2015, the number one recruiting tactic into the sex trade happens online,” he said. “But there was a huge gap in using technology in prevention.” Predators were deciding whom to approach by looking at public profiles online and gauging vulnerability. If these vulnerabilities were modeled, Martin said, machine learning could be coded to detect which children were most likely to be approached.    

Once a child goes missing, time is of the essence. In 2016, the National Center for Missing and Exploited Children employed 25 analysts receiving and disbursing about 8 million reports to law enforcement. Cases determined as “urgent” were automatically dispersed to a government agency, while others went to a 30 day backlog. Machine learning was introduced as a key part of the pipeline in 2017, automating the IP addresses and cell phone information of victims and predators. Since then, case backlog is down to 24 hours, and the time saved has allowed analysts to focus more deeply on specific cases.

When creating data sets to be fed to algorithms to prevent human trafficking, concerns about diversity and inclusion are life and death issues. As Thee of Bark.us explained, “Traditional facial recognition tools are good at identifying those who are white, adult, and male—which is almost the opposite of human trafficking victims. Pairing the grainy pictures of missing children with actual faces was our initial challenge.”

Finding technology companies to partner with the panelists’ initiatives presented significant challenges. “Storytelling has significant power,” Rogers said. “Press about how Intel can use its AI technology to save lives is powerful. But you have to be comfortable with rejection. Funding is always going to be a issue here—You have to be ready for a marathon and not a sprint.”

The panelists underscored that AI and machine learning are proving to be extremely helpful tools for this important human rights work. They also noted that the potential for student involvement is great, as this generation of university students are increasingly fluent in computer science, which can be put toward protecting vulnerable children around the world.

“Young people growing up online are in the midst of one of the largest social experiments in history,” said Thee. “This is labor intensive work, but in many ways you can work to save yourselves and your peers.”

—Veena Narashiman ’2020

“Imagining the Future Helps Us Engineer Toward that Future”: A Q&A with Will Tarpeh

“Imagining the Future Helps Us Engineer Toward that Future”: A Q&A with Will Tarpeh

When Will Tarpeh was an undergraduate at Stanford University, he didn’t know if it was possible to be a research engineer who works in the developing world. His global interests started in high school, when he learned that more than 2 billion people lack access to adequate sanitation. And they expanded throughout college, as he studied chemical engineering and African studies and interned at Sarar Transformación, a Mexican nonprofit focused on sanitation. “That’s when I got interested in ecological sanitation,” he said, “which is just the idea of using waste as fertilizer.”

Tarpeh, now an assistant professor in chemical engineering at Stanford, says his professional turning point happened at UC Berkeley in 2013, the year the Development Engineering program started. The Blum Center sat down with Tarpeh to learn more about his views of Development Engineering and how his research combines electrochemical engineering, global sanitation, and resource recovery.

How did Development Engineering shape your academic work in global sanitation?

It was extreme serendipity. Development Engineering started the year I got to Berkeley and made a lot of things possible. It gave me a formal structure—having a chapter in my dissertation that was explicitly about Development Engineering and about my sanitation work in Kenya. If it weren’t there and if I hadn’t gone to Berkeley, I might not have explored this part of my academic identity in as much detail. Now it’s such a crucial part, I can’t imagine being an academic without it.

What else drew you to Cal?

I wanted to work with Professor Kara Nelson, because she has a process engineering focus for achieving sanitation goals. She had a Gates Foundation grant that was part of their Grand Challenges exploration, and she and a post-doc were working on the idea of using ammonia from urine to disinfect feces. I tagged along and went to the Gates Foundation’s Reinvent the Toilet Expo, which was my dream at that time. I got to see all these cool toilets, and realized there was a large community of academic researchers who shared my interests.

How did your own research develop?

My first year in graduate school I reviewed journal papers and focused on unanswered questions. That’s when we landed on urine and recovering nitrogen. We chose urine because there were lots of motivations for separating out urine and feces. And from a chemical engineering perspective, we thought nitrogen from urine could be useful because nitrogen fertilizers are central to modern society—they’ve helped feed a growing population. We focused on what we could borrow from other subfields, such as the extraction of nitrogen from wastewater in the U.S., and also on what we could dream up on our own to address sanitation access.

How do you see your academic contributions?

My first paper as a PhD student compared materials that adsorb or concentrate nitrogen in urine. We compared four different adsorbents. Then we took the work to the field and published it in the Development Engineering journal—which meant characterizing the technology in lab, bringing it to the field, and in between looking at the operating and design parameters to show the trajectory as a contribution. Another contribution is in electrochemical nitrogen recovery. Electrochemistry and wastewater treatment have met in earnest over the past decade or so. I’ve been part of the first group of people to apply electrochemistry to urine and to extract nitrogen in a new way we call electrochemical stripping. It’s set some records in terms of nitrogen recovery efficiency and resulting energy efficiency.

You said in a previous interview that “a lot of the solutions to the world’s most pressing problems are in the minds of children who are simply preoccupied with survival.” Why are children a place to understand the world’s grand challenges?

Grand Challenges are really interesting because they are descriptive in nature. Through them, academics, UN representatives, and others try to describe a reality that millions of people experience. But I think the expertise really lies in the communities who experience the problems. We as scientists can try to lend our technical expertise in other communities—but the people who live in those communities are the real experts. That’s how I approach my work. This comes in part from growing up in a low-income household in the U.S., and knowing that resource-constrained communities have valuable skills and life experiences to solve their own problems.

How new is the field of Development Engineering?

 It’s not new in some ways. People have been doing this kind of engineering for as long as there’s been inequality. What’s new is that we’re studying how we do it and thinking about better ways to do it. Ten years ago, it was news to people that you need to engage the community when you design for it. It really was. We would learn about implementation failures all the time—and be surprised that engineers didn’t remember to ask people about their sanitation needs and, as a result, the new toilets got turned into closets because they had roofs. Now, I see the frequency with which that kind of thing is reported going down, which tells me there’s value in the Development Engineering enterprise. It formalizes things in a way that engineers who don’t focus on development can appreciate.

How important is field work to Development Engineering?

It’s a crucial site of learning. Going back and forth into the field has been extremely valuable to my research. Maybe the traditional model of humanitarian engineering was: you develop something in the lab about a problem in a developing community; you say, I have an answer for that; you characterize it in the lab; and you go out and say, here it is. But then you realize you were designing for constraints that didn’t reflect reality in the community. Development Engineering is about iterating. Over the course of my PhD, I went to Kenya and worked with Sanergy. That’s when I realized they were collecting urine but not yet creating value from it. Then I tinkered in the lab on the urine research, and spent the next four years going back and forth to see what worked and made adjustments, which allowed for the rigorous study we expect in academic communities.

 Is being a Development Engineer a liability in academia?

I don’t think it is the liability it was five or ten years ago. It’s attractive now to do Development Engineering because of the huge impact you can have. Another part of this is students are demanding training to try to solve development problems. I have engineering students who say global sanitation really gets them moving and motivated. From a disciplinary perspective, Development Engineering is one of the ways we stay relevant to our students and to the Grand Challenges that people are facing around the world.

Are you seeing more academic engineers like yourself who do applied research in developing countries?

I do feel there’s a generation of professors tying loose ends together and thinking about ways to leverage skill sets that are no longer within one discipline. Alice Agogino always talked about the wicked problems that refuse to be classified in one silo and that demand multiple approaches. Many professors now have multiple skill sets and are oriented toward solving wicked problems. I feel I’m part of this, combining electrochemical engineering, global sanitation, and resource recovery.

Do you think it’s significant that most of your mentors have been women?

Yes, and that was a recent epiphany. After Berkeley, I did a post-doc at University of Michigan, where I also was advised by two women—Nancy Love and Krista Wigginton. Female professors have impacted me, particularly by seeing the extra obstacles they have to go through and the strategies they use to succeed. Being supportively mentored by advisors who are different than me has prepared me to support students from diverse backgrounds in my own career.

How do you advocate for STEM inclusion and equality now that you’re a professor?

I recommend students and colleagues for awards, formally by writing recommendation letters and informally by suggesting people for collaborations and so on. Also, being a black male, I try to serve as a role model for students. At Stanford, I give lunch talks with minority or under-represented students. It doesn’t take a lot of time and it could be a high impact intervention for one of them. I also work to design impactful programs. Kara [Nelson] and I were involved in the Graduate Pathways Symposium at Berkeley for underrepresented minorities to apply to grad school. I also make sure when I work in Kenya, I give author credit to the local researchers on my academic papers.

 When will we achieve global sanitation?

There are some estimates that low and middle-income countries are not going to fully address the problem by 2050. One argument is that we won’t get there because of the barriers to creating centralized wastewater treatment facilities. But there are other options, namely resource efficiency. A paper I’m working on argues that if we take resource recovery one step further and bake sustainability into every process we do, we can minimize the inputs for everything we produce. The paper encapsulates the idea of the circular economy, of resource recovery. Of course, being a urine researcher, I believe separating urine has a role to play in that. I believe imagining the future helps us engineer toward that future.

—Tamara Straus

The Future of Collaboration in the Future of Work

The Future of Collaboration in the Future of Work

By Rachel Dzombak

At the 2018 Autodesk University conference, a weeklong event bringing together representatives from the building, design, manufacturing, and construction industries, the skillsets required for the future workforce were a heavy focus. In her keynote speech, Beth Comstock, the former CEO of GE, discussed how multinational companies are reorganizing around digital information flows, asserting, “We can’t control change, we can’t predict the future, but we can be more adaptable.”

Throughout the conference, others asked: How do we build an adaptable workforce? How are educational needs shifting in response to emergent industry changes? What are the initial steps that we need to take to prepare for the transition?

These critical questions are being asked not just by industry leaders but by faculty and senior administrators at universities. The conversation at UC Berkeley is near constant, especially in engineering and business. Students and faculty alike want to know: How will companies operate? How will industries evolve? And how should socio-political systems best adapt to workforce changes?

There are pessimists and optimists. Among the optimists is UC Berkeley Robotics Professor Ken Goldberg, who argues that forecasts of mass unemployment are unfounded. He believes new jobs will replace old ones and even imagines, echoing Maynard Keynes, that automation will lead to elimination of mundane tasks, giving people time to be more creative.

A technology-infused world that abets humans must be a goal. We may even be on the brink of a golden age of intelligent collaboration—enabling new inventions and ways of thinking that come from the melding of disciplines, cultures, and fields. As Fei-Fei Li, a Stanford University computer science professor and former chief scientist at Google, points out, bringing technology to bear on societal issues will “require insights derived from fields beyond computer science, which means programmers will have to learn to collaborate more often with experts in other domains.” In other words, workers, especially those in the cutting-edge fields, will be compelled to integrate computation with linguistics, behavioral science with physics, economic development with history, and so on.

Historically, universities provided access to knowledge and skillsets that was hard to reach otherwise. Knowledge was held by faculty experts who achieved mastery in narrow subjects, and delivered material to students via lectures. With the rise of the Internet, content is now available at an unprecedented level. Students are learning to prove fluid dynamics proofs through YouTube, skipping economics class in favor of learning through Khan Academy, and asking Google or Wikipedia “How do I design a gray-water system?”

If students are then learning traditional material through other forums, what is the value of the university today? And what do students need to learn that cannot be taught online? The World Economic Forum cites the top six skills needed in 2020 as: 1) complex problem solving, 2) critical thinking, 3) creativity, 4) people management, 5) coordinating with others, and 6) emotional intelligence.

In this first article on the future of work, I want to underscore that three of the top six skills on this list—and many others—focus on collaboration. This is unsurprising, as work increasingly happens in teams regardless of industry. However, few (if any of us) have ever been explicitly taught how to work in teams. We learn through sports and project work, but team-based experiences often lead to frustration (“oh, I’m stuck doing all the work again”), confusion (“we’re all on different pages”), or conflict (“it’s really hard to work with people who are so different from me”).

Teaching students to collaborate across diverse teams will be a key priority of universities in the coming years. Speaking on cultivating the next generation of students, Ruth Simmons, former president of Brown University and current president of Prairie View A&M University, commented in a recent New York Times article about the role of teaching students to collaborate. She said, “If we’re doing what we should be doing, we are acclimating students to an environment in which they have to learn to work with others who are very different from themselves. And that seems to me to be the first requirement of leadership. To actually learn to work with people in a respectful and inclusive way is inordinately important.”

At Berkeley, Professor Sara Beckman and I developed a toolkit called “Teaming by Design” for teaching students how to collaborate in teams. We provide tools and research grounded in human-centered design, organizational behavior, and systems engineering to educate on building self-awareness, working collaboratively with others, and growing capacity to achieve innovative outcomes.

In the toolkit, we outline four phases: Team Formation, Team Launch, Team Check-in, and Team Celebration. Within each phase, we give exercises teams can conduct to improve their dynamics and research to ground the importance of the phase as well as raise consciousness of common issues. We additionally provide guidance on what work should be done in teams. Too often in school, team work is confused with group work. Students quickly divide the work among themselves and meet only to staple the elements together.

A team, by definition, is a collection of people who are committed to a common purpose, whose interdependence requires coordinated effort, and who hold themselves mutually accountable for results. While in some Berkeley classes, teams are comprised of a mix of different students from the same majors (e.g., a mechanical engineer and civil engineer working on the design of a sensor), other teams cross the spectrum—bringing together students from business, art, history, and dance to address, for example, homelessness. Both experiences represent deep learning opportunities for students to become exposed to different ways of thinking and doing.

Our work aims to create change on several levels. First, it is a resource for faculty who may be unfamiliar with how to coach teams. Despite the changes coming to education, faculty (particularly at research universities) are still largely hired for expertise in a narrow field. A fluid dynamics professor who wants students to work in teams within her class may be great at coaching on mathematical modeling issues yet far less equipped at structuring projects that require interdependence or coaching on the socio-emotional challenges that come up within project teams—such as issues of mutual accountability, trust, and conflicts stemming from varied personalities. We work with faculty in business, engineering, art practice, and biology to teach them how to collect feedback and how to debrief the feedback with students, so that it becomes a learning mechanism and not only a tool for grading.

During the Autodesk University conference, advanced machines, XR headsets, and 3D digital models were prominently on display. But even more prominent were the opportunities that technology could enable. For example, advanced lighting systems that provide Internet, mood, music, and safety features—in addition to light—could lead cities to rethink public services. The role of the lighting designer will shift from thinking about delivering light to imagining ways people might navigate their environment. This new frame increases the importance of knowing how to draw out insights from residents and collaborating with relevant stakeholders. Advancing technology forces individuals and organizations to rethink the systems in which they are working, and who they are working with. The more diverse the collaboration, the higher chance for creative problem solving.

We need to start ensuring that students are equipped with the ability to collaborate across untraditional boundaries, because collaboration will be critical for their success in the rapidly evolving workplace.

Rachel Dzombak is a Research Fellow at the Blum Center for Developing Economies. She researches and teaches design, innovation, and system thinking.

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