Zobrazeno 1 - 10
of 4 184
pro vyhledávání: '"Vincent, Nicholas"'
The rapid scaling of AI has spurred a growing emphasis on ethical considerations in both development and practice. This has led to the formulation of increasingly sophisticated model auditing and reporting requirements, as well as governance framewor
Externí odkaz:
http://arxiv.org/abs/2409.19104
We propose a framework for measuring attentional agency - the ability to allocate one's attention according to personal desires, goals, and intentions - on digital platforms. Platforms extend people's limited powers of attention by extrapolating thei
Externí odkaz:
http://arxiv.org/abs/2405.14614
Systemic property dispossession from minority groups has often been carried out in the name of technological progress. In this paper, we identify evidence that the current paradigm of large language models (LLMs) likely continues this long history. E
Externí odkaz:
http://arxiv.org/abs/2403.13073
Can governments build AI? In this paper, we describe an ongoing effort to develop ``public AI'' -- publicly accessible AI models funded, provisioned, and governed by governments or other public bodies. Public AI presents both an alternative and a com
Externí odkaz:
http://arxiv.org/abs/2311.11350
Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (e.g. behavior logs, user-gener
Externí odkaz:
http://arxiv.org/abs/2305.13238
Autor:
Abhari, Rod, Villa-Turek, Esteban, Vincent, Nicholas, Dambanemuya, Henry, Horvát, Emőke-Ágnes
Retracted scientific articles about COVID-19 vaccines have proliferated false claims about vaccination harms and discouraged vaccine acceptance. Our study analyzed the topical content of 4,876 English-language tweets about retracted COVID-19 vaccine
Externí odkaz:
http://arxiv.org/abs/2303.16302
Retracted research discussed on social media can spread misinformation. Yet we lack an understanding of how retracted articles are mentioned by academic and non-academic users. This is especially relevant on Twitter due to the platform's prominent ro
Externí odkaz:
http://arxiv.org/abs/2203.04228
Autor:
Bandy, Jack, Vincent, Nicholas
Recent literature has underscored the importance of dataset documentation work for machine learning, and part of this work involves addressing "documentation debt" for datasets that have been used widely but documented sparsely. This paper aims to he
Externí odkaz:
http://arxiv.org/abs/2105.05241
Many powerful computing technologies rely on implicit and explicit data contributions from the public. This dependency suggests a potential source of leverage for the public in its relationship with technology companies: by reducing, stopping, redire
Externí odkaz:
http://arxiv.org/abs/2012.09995
Autor:
Contractor, Danish, McDuff, Daniel, Haines, Julia, Lee, Jenny, Hines, Christopher, Hecht, Brent, Vincent, Nicholas, Li, Hanlin
With the growing reliance on artificial intelligence (AI) for many different applications, the sharing of code, data, and models is important to ensure the replicability and democratization of scientific knowledge. Many high-profile academic publishi
Externí odkaz:
http://arxiv.org/abs/2011.03116