Daniel L. Chen

Camille Terrier, Daniel L. Chen, and Matthias Sutter, “COVID-19 within families amplifies the prosociality gap between adolescents of high and low socioeconomic status”, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, n. 46 (e2110891118), 2021.

Sandeep Bhupatiraju, and Daniel L. Chen, “The Process of Machine Learning for the Courts of India”, National Law School of India Review, vol. 33, n. 2, 2021.

Yu Cao, Elliott Ash, and Daniel L. Chen, “Automated fact-value distinction in court opinions”, European Journal of Law and Economics, vol. 50, December 2020, pp. 451–467.

Daniel L. Chen, “Gender Violence and the Price of Virginity: Theory and Evidence of Incomplete Marriage Contracts”, Journal of Religion and Demography, vol. 7, n. 2, October 2020, pp. 190–221.

Boris Babic, Daniel L. Chen, Theodoros Evgeniou, and Anne-Laure Fayard, “A Better Way to Onboard AI”, Harvard Business Review, vol. 98, n. 4, August 2020, pp. 56–65.

Eric Reinhart, and Daniel L. Chen, “Incarceration And Its Disseminations: COVID-19 Pandemic Lessons From Chicago’s Cook County Jail”, Health Affairs, vol. 39, n. 8, August 2020, pp. 1412–1418.

Boris Babic, Daniel L. Chen, Theodoros Evgeniou, and Anne-Laure Fayard, “A Better Way to Onboard AI”, Harvard Business Review, August 2020.

Daniel L. Chen, Vardges Levonyan, S.Eric Reinhart, and Glen Taksler, “Mandatory Disclosure: Theory and Evidence from Industry-Physician Relationships”, Journal of Legal Studies, vol. 48, n. 2, June 2019, pp. 409–440.

Daniel L. Chen, “Judicial Analytics and the Great Transformation of American Law”, Artificial Intelligence and the Law, vol. 27, n. 1, March 2019, pp. 15–42.

Daniel L. Chen, “Law and Literature: Theory and Evidence on Empathy and Guile”, Review of Law and Economics, vol. 15, n. 1, March 2019.

Daniel L. Chen, and Elliott Ash, “Case Vectors: Spatial Representations of the Law Using Document Embeddings”, Law as Data, vol. 11, 2019.

Daniel L. Chen, “Machine Learning and the Rule of Law”, 2019in Law as Data: Computation, Text, and the Future of Legal Analysis, Michael Livermore, and Daniel Rockmore (eds.), Santa Fe Institute Press, 2019.

Daniel L. Chen, Yosh Halberstam, Manoj Kumar, and Alan Yu, “Attorney Voice and the U.S. Supreme Court”, 2019in Law as Data: Computation, Text, and the Future of Legal Analysis, Michael Livermore, and Daniel Rockmore (eds.), Santa Fe Institute Press, 2019.

Daniel L. Chen, Charlotte Cavaillé, and Karine Van Der Straeten, “A Decision-Theoretic Approach to Understanding Survey Response: Likert vs. Quadratic Voting for Attitudinal Research”, The University of Chicago Law Review, vol. 22, n. Online, 2019.

Daniel L. Chen, “Intermediated Social Preferences: Altruism in an Algorithmic Era”, in Advances in Economics of Religion, Jean-Paul Carvalho, Sriya Iyer, and Jared Rubin (eds.), Palgrave Macmillan, series “International Economic Association Series”, vol. 158, 2019, pp. 119–138.

Daniel L. Chen, “Tastes for Desert and Placation: A Reference Point-Dependent Model of Social Preferences”, Research in Experimental Economics, 2018.

Daniel L. Chen, Jacob Phillips, and Alan Yu, “Non-Segmental Conditioning of Sibilant Variation in American English”, in Proceedings of the 9th International Conference on Speech Prosody, 2018.

Daniel L. Chen, Adithya Parthasarathy, and Shivam Verma, “The Genealogy of Ideology: Identifying Persuasive Memes and Predicting Agreement in the U.S. Courts of Appeals”, in Proceedings of the ACM Conference on AI and the Law, 2018, forthcoming.

Ramya Vunikili, Hitesh Ochani, Divisha Jaiswal, Richa Deshmukh, Daniel L. Chen, and Elliott Ash, “Analysis of Vocal Implicit Bias in SCOTUS Decisions Through Predictive Modelling”, in Proceedings of Experimental Linguistics, 2018.

Daniel L. Chen, Matt Dunn, Levent Sagun, and Hale Sirin, “Early Predictability of Asylum Court Decisions”, in Proceedings of the ACM Conference on AI and the Law, 2018.