Three Laws Blog: Law and Artificial Intelligence

King, Aggarwal, Taddeo, and Floridi on AI Crime

Thomas King, Nikita Aggarwal, Mariarosaria Taddeo, and Luciano Floridi, all of the Oxford Internet Institute, University of Oxford, have published Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.

Artificial Intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, which we term AI-Crime (AIC). We already know that AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing law enforcement and policy-makers with a synthesis of the current problems, and a possible solution space.

Download the article from SSRN at the link.

Chung and Zink on the Liability of Artificial Intelligence In Medicine @leopardist

Jason Chung and Amanda Zink, both of New York University, are publishing Hey Watson, Can I Sue You for Malpractice? Examining the Liability of Artificial Intelligence in Medicine in the Asia-Pacific Journal of Health Law, Policy, and Ethics. Here is the abstract.

Currently, three South Korean medical institutions – Gachon University Gil Medical Center, Pusan National University Hospital and Konyang University Hospital - have implemented IBM’s Watson for Oncology artificial intelligence (AI) system. As IBM touts the Watson for Oncology AI’s to “[i]dentify, evaluate and compare treatment options” by understanding the longitudinal medical record and applying its training to each unique patient, questions regarding the status and liability of these AI machines have arisen. Given its ability to interpret data and present treatment options (along with relevant justifications), AI represents an interim step between a diagnostic tool and colleague in medical settings. Using philosophical and legal concepts, this article explores whether AI’s ability to adapt and learn means that it has the capacity to reason and whether this means that AI should be considered a legal person. Through this exploration, the authors conclude that medical AI such as Watson for Oncology should be given a unique legal status akin to personhood to reflect its current and potential role in the medical decision-making process. They analogize the role of IBM’s AI to those of medical residents and argue that liability for wrongful diagnoses should be generally based on a medical malpractice basis rather than through products liability or vicarious liability. Finally, they differentiate medical AI from AI used in other products, such as self-driving cars.

Download the article from SSRN at the link.

Chandra on Liability Issues in Relation to Autonomous AI Systems @bucerius_law

Abhiuday Chandra, Bucerius Law School, has published Liability Issues in Relation to Autonomous AI Systems. Here is the abstract.

This paper explores issues relating to two fundamental questions, how mitigate the risks associated with a constant expansion in autonomy of artificial intelligence (AI) and how to make people liable for their AI creations. The aim of this paper is to only highlight issues fundamental to the constituents of the legal regulatory structure for autonomous AI systems at following levels: (i) desirable attributes of AI, (ii) legal approach and principles to determine liability, and (iii) contractual arrangement governing relationship between developers and users of AI.

Download the article from SSRN at the link.