The recent explosion of generative and non-generative AI has sparked broad public debate on ethical applications of the new technology, the potential for harm and abuse, and bias. Writing for The Regulatory Review, Janaina Rodrigues Valle Gomes LLM’23 examines recommendations for addressing bias in AI development from three experts, including Rangita de Silva de Alwis, Senior Adjunct Professor of Global Leadership, Member-Elect to the UN Convention on the Elimination of Discrimination against Women (CEDAW), and Treaty Body Expert Committee (2023-2026).
De Silva De Alwis is a globally recognized international women’s rights expert as well as Associate Dean of International Affairs at the University of Pennsylvania Carey Law School, where she teaches several pathbreaking courses such as “International Women’s Rights; Women, Law, and Leadership” and the “Policy Lab on AI and Bias. De Silva de Alwis also directs the Global Institute for Human Rights.
From The Regulatory Review:
The public conversation has increasingly focused on bias in artificial intelligence (AI) systems that can be traced to poorly representative datasets and the unconscious biases of programmers. In a recent paper, three experts propose a two-pronged approach—with both direct and indirect policy interventions—that aim to ensure that AI systems achieve equity.
These experts—Rangita de Silva de Alwis, a professor at the University of Pennsylvania Carey Law School, Amani Michelle Carter Coutinho, a lawyer at Kirkland & Ellis, and Govind Nagubandi, an independent data scientist—argue both for direct and indirect interventions to encourage changes in the design of machine learning as well as at the development stages of business models using AI technology.
As for direct intervention, de Silva de Alwis, Coutinho, and Nagubandi argue for the recognition of a fifth category of intellectual property rights alongside patents, copyright, trademark, and trade secrets. This new category would grant ownership interests in an algorithm to the extent it is developed lawfully, without implicit bias. The parameter for this evaluation would be the United Nations (UN) human rights treaties, especially the Guiding Principles on Business and Human Rights 2011—known as the Ruggie Principles.
Based on the norms of the UN human rights treaties, ownership of an algorithm would require that it possess six characteristics.
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Launched in 2009 and operating under the guidance of Cary Coglianese, Edward B. Shils Professor of Law and Professor of Political Science, The Review is edited by students at Penn Carey Law. It is part of the overarching teaching, research, and outreach mission of the Penn Program on Regulation (PPR), which draws together more than 60 faculty from across the University of Pennsylvania.