Výsledky vyhledávání - "Kingsley, Sara"

Report

Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work together to Surface Algorithmic Harms?

Autor: Li, Rena, Kingsley, Sara, Fan, Chelsea, Sinha, Proteeti, Wai, Nora, Lee, Jaimie, Shen, Hong, Eslami, Motahhare, Hong, Jason

Recent years have witnessed an interesting phenomenon in which users come together to interrogate potentially harmful algorithmic behaviors they encounter in their everyday lives. Researchers have started to develop theoretical and empirical understa

Externí odkaz: http://arxiv.org/abs/2304.02134

Zobrazit plný text záznamu

Report

A Cognitive Science perspective for learning how to design meaningful user experiences and human-centered technology

Autor: Kingsley, Sara

This paper reviews literature in cognitive science, human-computer interaction (HCI) and natural-language processing (NLP) to consider how analogical reasoning (AR) could help inform the design of communication and learning technologies, as well as o

Externí odkaz: http://arxiv.org/abs/2106.07553

Zobrazit plný text záznamu

Report

Narratives and Counternarratives on Data Sharing in Africa

Autor: Abebe, Rediet, Aruleba, Kehinde, Birhane, Abeba, Kingsley, Sara, Obaido, George, Remy, Sekou L., Sadagopan, Swathi

As machine learning and data science applications grow ever more prevalent, there is an increased focus on data sharing and open data initiatives, particularly in the context of the African continent. Many argue that data sharing can support research

Externí odkaz: http://arxiv.org/abs/2103.01168

Zobrazit plný text záznamu

Report

Auditing Digital Platforms for Discrimination in Economic Opportunity Advertising

Autor: Kingsley, Sara, Wang, Clara, Mikhalenko, Alex, Sinha, Proteeti, Kulkarni, Chinmay

Digital platforms, including social networks, are major sources of economic information. Evidence suggests that digital platforms display different socioeconomic opportunities to demographic groups. Our work addresses this issue by presenting a metho

Externí odkaz: http://arxiv.org/abs/2008.09656

Zobrazit plný text záznamu

Report

SECure: A Social and Environmental Certificate for AI Systems

Autor: Gupta, Abhishek, Lanteigne, Camylle, Kingsley, Sara

In a world increasingly dominated by AI applications, an understudied aspect is the carbon and social footprint of these power-hungry algorithms that require copious computation and a trove of data for training and prediction. While profitable in the

Externí odkaz: http://arxiv.org/abs/2006.06217

Zobrazit plný text záznamu