Sina Fazelpour

According to our database, Sina Fazelpour authored at least 14 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Aspirational Affordances of AI.

Sina Fazelpour, Meica Magnani

CoRR, April, 2025

Should you use LLMs to simulate opinions? Quality checks for early-stage deliberation.

Terrence Neumann, Maria De-Arteaga, Sina Fazelpour

CoRR, April, 2025

The Value of Disagreement in AI Design, Evaluation, and Alignment.

Sina Fazelpour, Will Fleisher

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

2024

Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina.

Yuan Gao, Dokyun Lee, Gordon Burtch, Sina Fazelpour

CoRR, 2024

Authenticity and exclusion: social media recommendation algorithms and the dynamics of belonging in professional networks.

Nil-Jana Akpinar, Sina Fazelpour

CoRR, 2024

Disciplining deliberation: a sociotechnical perspective on machine learning trade-offs.

Sina Fazelpour

CoRR, 2024

Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation.

Terrence Neumann, Sooyong Lee, Maria De-Arteaga, Sina Fazelpour, Matthew Lease

CoRR, 2024

2022

Diversity in sociotechnical machine learning systems.

Sina Fazelpour, Maria De-Arteaga

Big Data Soc., January, 2022

Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms.

Terrence Neumann, Maria De-Arteaga, Sina Fazelpour

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Homophily and Incentive Effects in Use of Algorithms.

Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary C. Lipton, David Danks

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Diversity and homophily in social networks.

Sina Fazelpour, Hannah Rubin

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021

Information elaboration and epistemic effects of diversity.

Daniel Steel, Sina Fazelpour, Bianca Crewe, Kinley Gillette

Synth., 2021

Fair Machine Learning Under Partial Compliance.

Jessica Dai, Sina Fazelpour, Zachary C. Lipton

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Algorithmic Fairness from a Non-ideal Perspective.

Sina Fazelpour, Zachary C. Lipton

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020