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Designing Algorithms for Social Good

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DESIGNING ALGORITHMS FOR SOCIAL GOOD A Dissertation Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Rediet Tesfaye Abebe December 2019 c 2019 Rediet Tesfaye Abebe ALL RIGHTS RESERVED DESIGNING ALGORITHMS FOR SOCIAL GOOD Rediet Tesfaye Abebe, Ph.D. Cornell University 2019 Algorithmic and artificial intelligence techniques show immense potential to deepen our understanding of socioeconomic inequality and inform interven- tions designed to improve access to opportunity. Interventions aimed at histor- ically underserved communities are made particularly challenging by the fact that disadvantage and inequality are multifaceted, notoriously difficult to mea- sure, and reinforced by feedback loops in underlying structures. While great strides have been made in these areas – from assigning seats in public schools to poverty mapping – there remain many domains with major opportunities for further contributions and the prospect that we may be able to develop unified frameworks for applying computational insights to improve societal welfare. In this thesis, we develop algorithmic and computational techniques to ad- dress these issues through two types of interventions: one in the form of allo- cating scarce societal resources and the other in the form of improving access to information. We examine the ways in which techniques from algorithms, discrete optimization, mechanism design, and network and computational sci- ences can combat different forms of disadvantage, including susceptibility to income shocks, social segregation, and disparities in access to health informa- tion. We highlight opportunities for computing to play a role in fundamental social change. We close with a discussion on open questions in an emerging research area – Mechanism Design for Social Good (MD4SG) – around the use of algorithms, optimization, and mechanism design to address. BIOGRAPHICAL SKETCH Rediet Abebe is a computer science researcher, broadly working in the areas of algorithms and artificial intelligence with a focus on their applications to eq- uity and social good concerns. As part of this research agenda, she co-founded the Mechanism Design for Social Good (MD4SG) research initiative as a Ph.D. stu- dent at Cornell University. After graduating from Cornell, she will continue her tenure as a Junior Fellow at Harvard University, Society of Fellows. Abebe is an alumna of Harvard University (M.S. in applied mathematics, 2015), University of Cambridge (M.A. in mathematics, 2014), Harvard College (B.A. in mathematics, 2013), as well as the International Community School of Addis Ababa and Nazareth School. To foster inclusion and representation in her field, Abebe co-founded the Black in AI network as a graduate student. Her work is deeply informed by her upbringing in Addis Ababa, Ethiopia. iii For my mother and the motherland. iv ACKNOWLEDGEMENTS I knew I wanted to be an academic at a young age and I did not think that it would be possible for me to become any more excited about the prospect of being a researcher, mentor, and teacher than when I started graduate school. I feel immense gratitude to Jon Kleinberg for proving me wrong and showing me new ways to be excited about this career from my very first visit to Cornell. Thank you for your guidance, mentorship, and friendship, and for teaching me the value of a well-placed em dash – I could not be more grateful. I have been lucky to have a secondary advisor in David Parkes who, in addi- tion to getting me started on this research path, helped me as I transitioned from mathematics to computer science, from Harvard to Cornell then back again. Your generous support and teaching through the years has helped me achieve this milestone; thank you very much. I have learned an incredible amount from Bobby Kleinberg, who, in addition to being the ultimate test of my most challenging math problems, has been an unrelentless cheerleader for me over the years. Thank you for everything you have taught me and for believing in me since the first moment we met. I am deeply grateful, also, for Michael Macy, for welcoming me into your lab, always asking questions that I would not have thought of, and the most timely boosts in confidence. I am also thankful to my committee member, Kil- ian Weinberger, for your guidance and support, despite my refusal to do deep learning. Maybe someday, Kilian. I have benefited greatly from being a member of the theory of computa- tion group, the AI, Policy, and Practice group, and the Center for the Study of Inequality. I would especially like to thank Karen Levy and Kim Weeden for be- ing incredible collaborators, mentors, and friends. Many of the ideas presented v in this thesis have their origin in presentations I attended in one of these initia- tives or discussions in Kim Weeden’s social stratification class. Thank you for everything. I have also benefited from working with each of my collaborators on the work presented in this thesis: Lada Adamic, Solon Barocas, Richard Cole, Vasilis Gkatzelis, Jason Hartline, Shawndra Hill, Jon Kleinberg, Karen Levy, Nicole Im- morlica, Brendan Lucier, H. Andrew Schwartz, Peter M. Small, Manish Ragha- van, David Robinson, Jennifer Wortman Vaughan, Matt Weinberg. Thank you all. Two of the chapters in this thesis started as a result of research internships at Microsoft Research, where I was mentored by Nicole Immorlica, Brendan Lucier, and Jennifer Wortman Vaughan. Thank you for providing these oppor- tunities for me to grow as a researcher. My research has been enriched by the many people I have had the plea- sure of working with through MD4SG. Many thanks to Kira Goldner for your incredible insight and vision in building the foundation over the years, Irene Lo for taking the group to a whole new level, and Ana-Andreea Stoica for ef- fortlessly jumping in and showing us creative ways to expand our purpose. I have learned a lot and been inspired by each of you. I am grateful for Fran- cisco Marmolejo, Bryan Wilder, Zoe¨ Hitzig, Sara Kingsley, Faidra Monachou, Moses Namara, Manish Raghavan, Swathi, Sadagopan, Sam Taggart, and many others for leading groups within MD4SG and additionally my collaborators Ke- hinde Aruleba, Basiliyos Betru, Lenore Cowen, Rachel Cummings, Sanmay Das, Ezra Gross, Cynthia Habomania, Sera Linardi, Dina Machuve, Alvaro Monge, Daniel Nkemelu, Ezinne Nwankwo, George Obaido, Sekou Remy, Mwiza Sim- beye, and many others. I would also like to thank many members of the Cornell CIS community. vi Thank you to David Bindel, Eva´ Tardos, and Hakim Weatherspoon for your aca- demic and personal mentorship of me and other students, and especially those of us from underrepresented groups. Thank you to my collaborator and friend Austin Benson for your inspiring creativity and unending support. Thank you to Rebecca Stewart, Yl Guanchez, Vanessa Maley, and Coralia Torees for all of your support and patience with the unending stream of tasks for Black in AI and MD4SG, among many other things. I am very grateful for you all. And many thanks to numerous other Cornell CIS faculty, staff, and students, who made my time at Cornell all the more better. Thank you to everyone on Cornell’s West Campus, and especially to Er- ica Ostermann and Julia Thom-Levy for the community you created in Bethe House, which was my home for the majority of my graduate studies at Cornell. Part of the work presented in this thesis was completed during my first semester at the Harvard Society of Fellows. I would like to thank Kelly Katz, Ana Novak, and Diana Morse for your support during my transition into the Society, Sarah Derbew and Mireille Kamariza for all that you do to create com- munity, and the Senior Fellows for this wonderful gift of time. I credit much of the encouragement and sense of belonging I have felt as a graduate student to the Black in AI community, which continues to be one of the greatest sources of joy for me. Many thanks to Esube Bekele, Sarah Brown, Moustapha Cisse, Hassan Kane, Sanmi Koyejo, Daniel Nkemelu, Ezinne Nwankwo, Lyne Tchapmi, Judy Wawira, and especially to Timnit Gebru and Devin Guillory for all your work building this community and your support and friendship. My academic career and transition into computer science was instigated and facilitated by summers I spent working with Laszl´ o´ Babai and Peter May, who vii continue to be two of my most-trusted mentors and friends. Thank you both for taking me under your wing and encouraging me to be a researcher, despite never having a formal obligation in my training. I am also grateful for Imre Leader and Felix Fischer for supervising my re- search and studies during my time at the University of Cambridge, to Barbara Grosz, Radhika Nagpal, and David Parkes for getting me excited about AI dur- ing my year at Harvard SEAS, and to Michael Hopkins, Richard Stanley, and Victor Reiner for getting me started on research as an undergraduate student. Growing up I benefited from being a member of many communities in Ethiopia, including the International Community School of Addis Ababa and Nazareth School, of which I am a proud alumna. And, last, I am grateful for my families, God-given, assigned, and chosen: thank you to the Neale Parises: to Carly, Jasmine, Tallulah, and Leo for wel- coming me as one of the sisters from the first day and to Bridget and Matteo for opening up your home and your heart – your friendship means the world to me. To Fiona Wood and Diana Cai: thank you for being the kindest, wisest, and most generous friends I could have asked for. Thank you to David Miller for your boundless support, always knowing when to affirm and when to chal- lenge me, and, of course, thank you for typing.
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