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42 Cardozo Arts & Ent. L.J. 391 (2024)
Lost in Translation: The Limits of Explainability in AI

handle is hein.journals/caelj42 and id is 415 raw text is: LOST IN TRANSLATION: THE LIMITS OF EXPLAINABILITY IN AI • HOFIT WASSERMAN-ROZEN,* RAN GILAD-BACHRACH,** AND NIVA ELKIN-KOREN* ABSTRACT As artificial intelligence becomes more prevalent, regulators are in- creasingly turning to legal measures, like a right to explanation, to protect against potential risks raised by AI systems. However, are eX- plainable AI (XAI) tools-the artificial intelligence tools that provide such explanations-up for the task? This paper critically examines XAI's potential to facilitate the right to explanation by applying the prism of explanation's role in law to dif- ferent stakeholders. Inspecting the underlying functions of reason-giving reveals different objectives for each of the stakeholders involved. From the perspective of a decision-subject, reason-giving facilitates due pro- cess and acknowledges human agency. From a decision-maker's per- spective, reason-giving contributes to improving the quality of the deci- sions themselves. From an ecosystem perspective, reason-giving may strengthen the authority of the decision-making system toward different stakeholders by promoting accountability and legitimacy and by provid- ing better guidance. Applying this analytical framework to XAI's gener- ated explanations reveals that XAI fails to fulfilll the underlying objec- tives of the right to explanationfrom the perspective of both the decision- subject and the decision-maker. In contrast, XAI is found to be extremely well-suited to fulfill the underlying functions of reason-giving from an ecosystem's perspective, namely, strengthening the authority of the deci- sion-making system. However, lacking all other virtues, this isolated * Permission is hereby granted for noncommercial reproduction of this Article in whole or in part for education or research purposes, including the making of multiple copies for classroom use, subject only to the condition that the name of the author, a complete citation, and this copyright notice and grant of permission be included in all copies. * PhD Candidate, Zvi Meitar Center for Advanced Legal Studies, Buchman Faculty of Law, Tel- Aviv University; Research Fellow, Chief Justice Meir Shamgar Center for Digital Law and Inno- vation at Tel Aviv University. ** Professor, Tel-Aviv University Bio-Medical Engineering Department and Safra Center for Bio- Informatics. ** Professor, Tel-Aviv University Faculty of Law; Faculty Associate, Berkman Klein Center at Harvard University. This research was supported by the Israel Science Foundation (Grant No. 1437/22). 391

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