Algorithmic Monoculture and Social Welfare
Jon Kleinberg and Manish RaghavanTo appear in Proceedings of the National Academy of Sciences
Manish Raghavan
I'm a final-year PhD candidate in the Computer Science department at Cornell University, where I have the great fortune of being advised by Jon Kleinberg. I'm supported by an NSF GRFP award and a Microsoft Research PhD Fellowship. I received my B.S. in Electrical Engineering and Computer Science from UC Berkeley in May 2016. My primary interests lie in the application of computational techniques to domains of social concern, including algorithmic fairness and behavioral economics, with a particular focus on the use of algorithmic tools in the hiring pipeline. I'm also a member of Cornell's Artificial Intelligence, Policy, and Practice initiative and the Mechanism Design for Social Good working group on Bias, Discrimination, and Fairness. In my spare time, I play for Cornell's Mundial FC club soccer team.
Research
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness
Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K. Patro, Manish Raghavan, Ana-Andreea Stoica, and Stratis TsirtisThe Fourth ACM Conference on Fairness, Accountability, and Transparency (FAccT 2021)
Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices
Manish Raghavan, Solon Barocas, Jon Kleinberg, and Karen LevyThe Third ACM Conference on Fairness, Accountability, and Transparency (FAT* 2020) [video]
Press: MIT Technology Review, Fortune, Fortune (video), TechTarget, The Globe and Mail, HR Technologist, Cornell ChronicleRoles for Computing in Social Change
Rediet Abebe, Solon Barocas, Jon Kleinberg, Karen Levy, Manish Raghavan, and David G. RobinsonThe Third ACM Conference on Fairness, Accountability, and Transparency (FAT* 2020) [video of Karen's presentation]
The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons
Solon Barocas, Andrew D. Selbst, and Manish RaghavanThe Third ACM Conference on Fairness, Accountability, and Transparency (FAT* 2020) [video of Solon's presentation]
How Do Classifiers Induce Agents To Invest Effort Strategically?
Jon Kleinberg and Manish RaghavanThe 20th ACM Conference on Economics and Computation (EC 2019) [video]
Also appeared as:Designing Evaluation Rules that are Robust to Strategic Behavior at the AAAI-20 Sister Conference Track.
How Do Classifiers Induce Agents to Invest Effort Strategically? in ACM Transactions on Economics and Computation, October 2020.
Algorithmic Classification and Strategic Effort in SIGecom Exchanges, November 2020.
Hiring Under Uncertainty
Manish Raghavan, Manish Purohit, and Sreenivas GollapudiThirty-sixth International Conference on Machine Learning (ICML 2019)
The Externalities of Exploration and How Data Diversity Helps Exploitation
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, and Zhiwei Steven WuConference on Learning Theory 2018 (COLT 2018) [video]
For a version focused on the technical results, see Greedy Algorithm almost Dominates in Smoothed Contextual Bandits.Mapping the Invocation Structure of Online Political Interaction
Manish Raghavan, Ashton Anderson, and Jon KleinbergThe Web Conference 2018 (WWW 2018)
Selection Problems in the Presence of Implicit Bias
Jon Kleinberg and Manish RaghavanThe 9th Innovations in Theoretical Computer Science Conference (ITCS 2018) [video]
On Fairness and Calibration
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q. WeinbergerThe Thirty-First Annual Conference on Neural Information Processing Systems (NIPS 2017)
Planning with Multiple Biases
Jon Kleinberg, Sigal Oren, and Manish RaghavanThe 18th ACM Conference on Economics and Computation (EC 2017) [video]
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon Kleinberg, Sendhil Mullainathan, and Manish RaghavanThe 8th Innovations in Theoretical Computer Science Conference (ITCS 2017) [video]
Press: Washington Post, ProPublica, Harvard Business ReviewPlanning Problems for Sophisticated Agents with Present Bias
Jon Kleinberg, Sigal Oren, and Manish RaghavanThe 17th ACM Conference on Economics and Computation (EC 2016)
Deduplicating a Places Database
Nilesh Dalvi, Marian Olteanu, Manish Raghavan, and Philip BohannonThe 23rd International World Wide Web Conference (WWW 2014)
Other Writing
Testimony on New York City Int. No. 1894
Manish Raghavan2020. See the bill here
Challenges for mitigating bias in algorithmic hiring
Manish Raghavan and Solon BarocasThe Brookings Institution, 2019