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Full-Text Articles in Law
Reconsidering The Public Square, Helen L. Norton
Regulating The Risks Of Ai, Margot E. Kaminski
Regulating The Risks Of Ai, Margot E. Kaminski
Publications
Companies and governments now use Artificial Intelligence (“AI”) in a wide range of settings. But using AI leads to well-known risks that arguably present challenges for a traditional liability model. It is thus unsurprising that lawmakers in both the United States and the European Union (“EU”) have turned to the tools of risk regulation in governing AI systems.
This Article describes the growing convergence around risk regulation in AI governance. It then addresses the question: what does it mean to use risk regulation to govern AI systems? The primary contribution of this Article is to offer an analytic framework for …
Toward Stronger Data Protection Laws, Margot E. Kaminski
Toward Stronger Data Protection Laws, Margot E. Kaminski
Publications
No abstract provided.
Naïve Realism, Cognitive Bias, And The Benefits And Risks Of Ai, Harry Surden
Naïve Realism, Cognitive Bias, And The Benefits And Risks Of Ai, Harry Surden
Publications
In this short piece I comment on Orly Lobel's book on artificial intelligence (AI) and society "The Equality Machine." Here, I reflect on the complex topic of aI and its impact on society, and the importance of acknowledging both its positive and negative aspects. More broadly, I discuss the various cognitive biases, such as naïve realism, epistemic bubbles, negativity bias, extremity bias, and the availability heuristic, that influence individuals' perceptions of AI, often leading to polarized viewpoints. Technology can both exacerbate and ameliorate these biases, and I commend Lobel's balanced approach to AI analysis as an example to emulate.
Although …
Humans In The Loop, Rebecca Crootof, Margot E. Kaminski, W. Nicholson Price Ii
Humans In The Loop, Rebecca Crootof, Margot E. Kaminski, W. Nicholson Price Ii
Publications
From lethal drones to cancer diagnostics, humans are increasingly working with complex and artificially intelligent algorithms to make decisions which affect human lives, raising questions about how best to regulate these "human-in-the-loop" systems. We make four contributions to the discourse.
First, contrary to the popular narrative, law is already profoundly and often problematically involved in governing human-in-the-loop systems: it regularly affects whether humans are retained in or removed from the loop. Second, we identify "the MABA-MABA trap," which occurs when policymakers attempt to address concerns about algorithmic incapacities by inserting a human into a decision-making process. Regardless of whether the …