Abstract
The rapid spread of artificial intelligence (AI) systems has precipitated a rise in ethical and human rights-based frameworks intended to guide the development and use of these technologies. Despite the proliferation of these principles, there has been little scholarly focus on understanding these efforts either individually or as contextualized within an expanding universe of principles with discernible trends. To that end, this white paper and its associated data visualization compare the contents of thirty-six prominent AI principles documents side-by-side. This effort uncovered a growing consensus around eight key thematic trends: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values. Underlying this “normative core,” our analysis examined the forty-seven individual principles that make up the themes, detailing notable similarities and differences in interpretation found across the documents. In sharing these observations, it is our hope that policymakers, advocates, scholars, and others working to maximize the benefits and minimize the harms of AI will be better positioned to build on existing efforts and to push the fractured, global conversation on the future of AI toward consensus.
Highlights
Alongside the rapid development of artificial intelligence (AI) technology, we have witnessed a proliferation of “principles” documents aimed at providing normative guidance regarding AI-based systems
65 Mission assigned by the French Prime Minister (n 8) p. 113; Amnesty International, Access (n 56) p. 9; UNI Global Union, ‘Top 10 Principles for Ethical Artificial Intelligence’ (2017) p. 6 ; IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems (n 5) pp. 29-30 (See Principle 6); Standard Administration of China and Triolo (n 24) (See Principle 3.3.1.); German Federal Ministry of Education and Research, the Federal Ministry for Economic Affairs and Energy, and the Federal Ministry of Labour and Social Affairs (n 10) p. 16; Japanese Cabinet Office, Council for Science, Technology and Innovation (n 20) p. 10 (See Principle 4.1.6.)
The Toronto Declaration calls upon developers to submit “systems that have a significant risk of resulting in human rights abuses to independent third-party audits.”91 The T20 report on the future of work and education focuses instead on breadth of input, highlighting the need for training data and features to “be
Summary
Alongside the rapid development of artificial intelligence (AI) technology, we have witnessed a proliferation of “principles” documents aimed at providing normative guidance regarding AI-based systems. Our desire for a way to compare these documents – and the individual principles they contain – side by side, to assess them and identify trends, and to uncover the hidden momentum in a fractured, global conversation around the future of AI, resulted in this white paper and the associated data visualization. It is our hope that the Principled Artificial Intelligence project will be of use to policymakers, advocates, scholars, and others working on the frontlines to capture the benefits and reduce the harms of AI technology as it continues to be developed and deployed around the globe
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