As a research fellow at Princeton University's Center for Information Technology Policy and Center for Statistics and Machine Learning, I use qualitative, quantitative, and computational techniques to understand the intersection of emerging technologies, such as artificial intelligence
and blockchain, and the cultural, organizational, and financial influences that shape ethical practices within these industries.
In addition to my research, I have also led ethical development workshops for startup founders and business professionals. These workshops focus on operationalizing values in technology development,
offering practical strategies to ensure ethical considerations are at the forefront of innovation.
Prior to joining Princeton, I worked as an Assistant Professor of Psychology at Bard College and as a data scientist for e-commerce technology companies, where I developed machine learning systems for providing product recommendations.
I have published academic articles and book chapters on psychology, neuroscience, machine learning, and human-computer interaction
Download my CV.
Publications on Technology
An up-to-date record of my academic publications is available on
Google Scholar
Conference Proceedings
Papakyriakopoulos, O., Engelmann, S., & Winecoff, A.. (2023) Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit . In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems.
Winecoff, A., & Watkins, E. A. (2022). Artificial concepts of artificial intelligence: Institutional compliance and resistance in AI startups
In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society.
Winecoff, A., Brasoveanu, F., Casavant, B., Washabaugh, P., & Graham, M. (2019).
Users in the loop: A psychologically-informed approach to similar item retrieval. In Proceedings of the 13th ACM Conference on Recommender Systems, (pp. 52-59).
Workshop Papers & Presentations
Lenhard, J., & Winecoff, A. (2022, forthcoming). What web3 calls thinking - from democratisation to inequality in blockchain ideologies. Presentation at Anthropology, AI, and the Future of Human Society.
Winecoff, A., Sun, M., Lucherini, E., & Narayanan, A. (2021). Simulation as experiment: An empirical critique of simulation research on recommender systems
Paper presented at the SimuRec Workshop at the 15th ACM Conference on Recommender Systems.
Papakyriakopoulos, O., Watkins, E. A., Winecoff, A., Jaźwińska, K., & Chattopadhyay, T. (2021). Qualitative analysis for human centered AI.
Paper presented at the Human-Centered AI Workshop at the Conference on Neural Information Processing Systems (NeurIPS).
Sherman, J., Shukla, C., Textor, R., Zhang, S., & Winecoff, A. (2019). Assessing fashion recommendations: A multifaceted offline evaluation approach.
Paper presented at the FashionXRecSys Workshop at the 13th ACM Conference on Recommender Systems.
Preprints
Winecoff, A., & Lenhard, J. (2023, submitted). Techno-utopians, scammers, and bullshitters: The promise and peril of Web3 and blockchain technologies according to operators and venture capital investors .
arXiv preprint arXiv:2307.10222
Lucherini, E., Sun, M., ,Winecoff, A., & Narayanan, A. (2021). T-RECS: A simulation tool to study the societal impact of recommender systems.
arXiv preprint arXiv:2107.08959.
Khaziev, R., Casavant, B., Washabaugh, P., Winecoff, A., & Graham, M. (2019). Recommendation or discrimination?: Quantifying distribution parity in information retrieval systems.
arXiv preprint arXiv:1909.06429.
Publications on Psychology & Neuroscience
Journal Articles
Sweitzer, M. M., Watson, K. K., Erwin, S. R., Winecoff, A., Datta, N., Huettel, S., Platt, M. & Zucker, N. L. (2018). Neurobiology of social reward valuation in adults with a history of anorexia nervosa.
PloS One, 13(12), e0205085.
King, A., Kaighobadi, F., & Winecoff, A. (2016). Brief report: A health belief model approach to men’s assessment of a novel long-acting contraceptive.
Cogent Medicine, 3(1), 1250320.
Winecoff, A., Ngo, L., Moskovich, A., Merwin, R., & Zucker, N. (2015). The functional significance of shyness in anorexia nervosa.
European Eating Disorders Review, 23(4), 327-332.
Winecoff, A., Clithero, J. A., Carter, R. M., Bergman, S. R., Wang, L., & Huettel, S. A. (2013). Ventromedial prefrontal cortex encodes emotional value.
Journal of Neuroscience,33(27), 11032-11039.
Winecoff, A., LaBar, K. S., Madden, D. J., Cabeza, R., & Huettel, S. A. (2011). Cognitive and neural contributors to emotion regulation in aging.
Social Cognitive and Affective Neuroscience. 6(2), 165-176.
Chang, S. W., Winecoff, A., & Platt, M. L. (2011). Vicarious reinforcement in rhesus macaques (Macaca mulatta).
Frontiers in Neuroscience, 5, 27.
O'Dhaniel, A., Detwiler, J. M., Winecoff, A., Dobbins, I., & Huettel, S. A. (2011). Infrequent, task-irrelevant monetary gains and losses engage dorsolateral and ventrolateral prefrontal cortex.
Brain Research, 1395, 53-61.
Book Chapters
Winecoff, A. , & Huettel, S. A. (2017). Cognitive control and neuroeconomics. In Egner, T. (Ed.) The Wiley Handbook of Cognitive Control, (pp. 408-421)
Jacques, P. L. S., Winecoff, A., & Cabeza, R. (2013). Emotion and aging. In Armony, J., & Vuilleumier, P. (Eds.), The Cambridge Handbook of Human Affective Neuroscience, (pp. 635-661)
Today's Machine Learning Needs Yesterday's Social Science
(2022, April, 19). Talk at the Center for Information Technology Policy, Princeton University.
Jespersen, Ryan (Host). (2021, September, 22). UN calls for AI Moratorium. [
YouTube podcast episode]. In Real Talk Ryan Jespersen. Interview starts at 1:36.
Winecoff, A. (2022, June 16). Dcentral vs. Consensus: Are Institutions Frens or Enemies of Crypto? Freedom to Tinker.
Winecoff, A. (2022, March 4). Will Web3 Follow in the Footsteps of the AI Hype Cycle? Freedom to Tinker.
Winecoff, A. (2020, June 18). Ok Karens, We Need to Speak to the Manager … About Equity. Medium.
Winecoff, A. (2019, October 13). Getting Started in Machine Learning & Data Science: A Guide for Social Scientists. Towards Data Science.
Winecoff, A. (2019, September 11). I’m the Best Data Scientist You’d Never Hire. Medium.