Optimizing large language models (LLMs) for downstream use cases often involves the
customization of pre-trained LLMs through further fine-tuning. Meta's open release of Llama …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

The introduction of autonomous vehicles (AVs) has led to a shift in liability from driver to AV.
This paper is a systematic review of the literature on liability with AVs. Articles were selected …

Artificially intelligent algorithms are being integrated into decisionmaking processes at mind-
boggling speed and scale. 1 Governments use artificial intelligence (" Al") for law …

Scholars and advocates have proposed algorithmic impact assessments (" AIAs") as a
regulatory strategy for addressing and correcting algorithmic harms. An AIA-based …

This paper shows that the law, in subtle ways, may set hitherto unrecognized incentives for
the adoption of explainable machine learning applications. In doing so, we make two novel …

Optimism about the explosive potential of artificial intelligence (AI) to transform medicine is
tempered by worry about what it may mean for the clinicians being “augmented.” One …

Mitigating Racial Bias in Machine Learning Page 1 92 journal of law, medicine & ethics The
Journal of Law, Medicine & Ethics, 50 (2022): 92-100. © 2022 The Author(s) DOI: https://doi.org/10.1017/jme.2022.13 …

Facial Recognition and the Fourth Amendment Page 1 Article Facial Recognition and the
Fourth Amendment Andrew Guthrie Fergusont Introduction …

The employment of AI systems presents challenges for liability rules. This paper identifies
these challenges and evaluates how liability rules should be adapted in response. The …