Lawyers are from Mars, data scientists are from Venus: promoting responsible AI on Earth

Hofit Wasserman-Rozen and Karni Chagal-Feferkorn

Chapter Chapter 9 in Research Handbook on the Law of Artificial Intelligence, 2025, pp 177-193 from Edward Elgar Publishing

Abstract: This chapter explores the critical need for collaboration between lawyers and data scientists in the era of Artificial Intelligence (AI). It asserts that while AI holds immense promise, it also presents significant legal and ethical challenges. Effective communication and teamwork between these two disciplines are essential to responsibly harness AI and mitigate its risks. The chapter starts by outlining potential dangers of AI, including biased decision-making, lack of transparency, and privacy threats. It highlights concerns about “black-box” AI systems, where opaque internal workings make it difficult to understand decision-making processes. It then describes how, in response, the concept of Responsible AI has emerged, emphasizing the ethical development and deployment of AI systems to uphold human rights, fairness, and transparency. The chapter touches on various international regulations and policy frameworks promoting Responsible AI but argues that traditional top-down regulation is insufficient for AI’s complexities. Instead, the chapter stresses the importance of collaboration between lawyers and data scientists. Lawyers bring expertise in legal and ethical frameworks, while data scientists understand AI’s technical intricacies. It acknowledges inherent challenges, such as lawyers’ tendency to think in nuanced legal terms, while data scientists deal with the concrete realities of code; or the ever-evolving nature of AI that complicates the establishment of fixed rules. Using the regulatory requirement of “transparency and explainability” in AI as a case study, the chapter illustrates how lawyers see “explanation” as justifying decisions in a legal sense, while data scientists approach explainability through Explainable AI (XAI) techniques, aiming to create simplified representations of complex algorithms. The chapter emphasizes the need for both perspectives to achieve meaningful transparency and demonstrates why collaboration between lawyers and data scientists is necessary in that context. The chapter concludes with preliminary thoughts on how to create and strengthen the bridge between both disciplines, in order to ensure that AI is developed, deployed and used in a responsible manner.

Keywords: Black box; Data science; Explanation; Responsible AI; Transparency; Artificial intelligence (search for similar items in EconPapers)
Date: 2025
ISBN: 9781035316489
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