Lessons learned from AI ethics principles for future actions
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OPINION PAPER
Lessons learned from AI ethics principles for future actions Merve Hickok1 Received: 29 August 2020 / Accepted: 2 September 2020 © Springer Nature Switzerland AG 2020
Abstract As the use of artificial intelligence (AI) systems became significantly more prevalent in recent years, the concerns on how these systems collect, use and process big data also increased. To address these concerns and advocate for ethical and responsible development and implementation of AI, non-governmental organizations (NGOs), research centers, private companies, and governmental agencies published more than 100 AI ethics principles and guidelines. This first wave was followed by a series of suggested frameworks, tools, and checklists that attempt a technical fix to issues brought up in the high-level principles. Principles are important to create a common understanding for priorities and are the groundwork for future governance and opportunities for innovation. However, a review of these documents based on their country of origin and funding entities shows that private companies from US-West axis dominate the conversation. Several cases surfaced in the meantime which demonstrate biased algorithms and their impact on individuals and society. The field of AI ethics is urgently calling for tangible action to move from high-level abstractions and conceptual arguments towards applying ethics in practice and creating accountability mechanisms. However, lessons must be learned from the shortcomings of AI ethics principles to ensure the future investments, collaborations, standards, codes or legislation reflect the diversity of voices and incorporate the experiences of those who are already impacted by the biased algorithms. Keywords Artificial intelligence · AI and ethics · Applied ethics · Governance · Social justice · Diversity
1 Introduction In the last few years advances in the capabilities of AI coupled with big data brought into focus the opportunities and risks of AI. These developments in response created a spike in the publication of AI ethics principles and guidelines from civil society organizations, research centers, private companies and governmental agencies as these parties made their commitments public, and positioned themselves on what they think are the most important values to embed in the development and implementation of AI products. Principles and guidelines are intentionally provided as high-level, abstract documents as the application of them is case, time and context sensitive. They need to be applicable across multiple areas. These high-profile value statements in AI contribute to the formation of a moral background as they make the connection between values, ethics, and technologies explicit [1]. Principles are also treated as the * Merve Hickok [email protected] 1
AIethicist.org, Ann Arbor, MI, USA
guides on how the policymakers and professionals should prioritize and structure future legislation, standards, governance models, and investment. Soft and hard governance models,
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