paper-with-me

홈 › Papers

Private Accountability in the Age of Artificial Intelligence

2026-01-14 · Sonia Katyal arxiv

In this Article, I explore the impending conflict between the protection of civil rights and artificial intelligence (AI). While both areas of law have amassed rich and well-developed areas of scholarly work and doctrinal support, a growing body of scholars are interrogating the intersection between them. This Article argues that the issues surrounding algorithmic accountability demonstrate a deeper, more structural tension within a new generation of disputes regarding law and technology. As I argue, the true promise of AI does not lie in the information we reveal to one another, but rather in the questions it raises about the interaction of technology, property, and civil rights. For this reason, I argue that we are looking in the wrong place if we look only to the state to address issues of algorithmic accountability. Instead, we must turn to other ways to ensure more transparency and accountability that stem from private industry, rather than public regulation. The issue of algorithmic bias represents a crucial new world of civil rights concerns, one that is distinct in nature from the ones that preceded it. Since we are in a world where the activities of private corporations, rather than the state, are raising concerns about privacy, due process, and discrimination, we must focus on the role of private corporations in addressing the issue. Towards this end, I discuss a variety of tools to help eliminate the opacity of AI, including codes of conduct, impact statements, and whistleblower protection, which I argue carries the potential to encourage greater endogeneity in civil rights enforcement. Ultimately, by examining the relationship between private industry and civil rights, we can perhaps develop a new generation of forms of accountability in the process.

📄 PDF Abstract BibTeX arXiv:2601.17013

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: What can they learn from each other?

2024-07-07 · Jakob Mokander, Prathm Juneja, David Watson, Luciano Floridi

On the whole, the U.S. Algorithmic Accountability Act of 2022 (US AAA) is a pragmatic approach to balancing the benefits and risks of automated decision systems. Yet there is still room for improvement. This commentary h…

Accountability of Generative AI: Exploring a Precautionary Approach for "Artificially Created Nature"

2025-05-12 · Yuri Nakao

The rapid development of generative artificial intelligence (AI) technologies raises concerns about the accountability of sociotechnical systems. Current generative AI systems rely on complex mechanisms that make it diff…

Prioritizing Policies for Furthering Responsible Artificial Intelligence in the United States

2022-11-30 · Emily Hadley

Several policy options exist, or have been proposed, to further responsible artificial intelligence (AI) development and deployment. Institutions, including U.S. government agencies, states, professional societies, and p…

Ethics

Human-Centered Artificial Intelligence and Machine Learning

2019-01-31 · Mark O. Riedl

Humans are increasingly coming into contact with artificial intelligence and machine learning systems. Human-centered artificial intelligence is a perspective on AI and ML that algorithms must be designed with awareness …

BIG-bench Machine LearningFairness

Man and Machine: Questions of Risk, Trust and Accountability in Today's AI Technology

2013-07-26 · Piyush Ahuja

Artificial Intelligence began as a field probing some of the most fundamental questions of science - the nature of intelligence and the design of intelligent artifacts. But it has grown into a discipline that is deeply e…