{"id":563,"date":"2020-05-03T18:18:00","date_gmt":"2020-05-03T18:18:00","guid":{"rendered":"http:\/\/sigai.acm.org\/aimatters\/blog\/?p=563"},"modified":"2020-05-03T18:18:00","modified_gmt":"2020-05-03T18:18:00","slug":"policy-and-ai-ethics","status":"publish","type":"post","link":"https:\/\/sigai.acm.org\/main\/2020\/05\/03\/policy-and-ai-ethics\/","title":{"rendered":"Policy and AI Ethics"},"content":{"rendered":"\n<p><strong>The Alan Turing Institute Public Policy Programme<\/strong><\/p>\n\n\n\n<p>Among the complexities of public policy making, the new\nworld of AI and data science requires careful consideration of ethics and\nsafety in addressing complex and far-reaching challenges in the public domain. Data\nand AI systems lead to opportunities that can produce both good and bad\noutcomes. Ethical and safe systems require intentional processes and designs\nfor organizations responsible for providing public services and creating public\npolicies. An increasing amount of research focuses on developing comprehensive\nguidelines and techniques for industry and government groups to make sure they\nconsider the range of issues in AI ethics and safety in their work. An\nexcellent example is the Public Policy Programme at The Alan Turing Institute\nunder the direction of Dr. David Leslie [1]. Their work complements and supplements\nthe Data Ethics Framework [2], which is a practical tool for use in any project\ninitiation phase. Data Ethics and AI Ethics regularly overlap.<\/p>\n\n\n\n<p>The Public Policy Programme describes AI Ethics as \u201ca set of\nvalues, principles, and techniques that employ widely accepted standards of\nright and wrong to guide moral conduct in the development and use of AI\ntechnologies. These values, principles, and techniques are intended both to\nmotivate morally acceptable practices and to prescribe the basic duties and\nobligations necessary to produce ethical, fair, and safe AI applications. The\nfield of AI ethics has largely emerged as a response to the range of individual\nand societal harms that the misuse, abuse, poor design, or negative unintended\nconsequences of AI systems may cause.\u201d<\/p>\n\n\n\n<p>They cite the following as some of the most consequential potential harms:<\/p>\n\n\n\n<ul><li>Bias and Discrimination<\/li><li>Denial of Individual Autonomy, Recourse, and Rights<\/li><li>Non-transparent, Unexplainable, or Unjustifiable Outcomes<\/li><li>Invasions of Privacy<\/li><li>Isolation and Disintegration of Social Connection<\/li><li>Unreliable, Unsafe, or Poor-Quality Outcomes<\/li><\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p>The Ethical Platform for the Responsible Delivery of an AI Project,\nstrives to enable the \u201cethical design and deployment of AI systems using a\nmultidisciplinary team effort. It demands the active cooperation of all team\nmembers both in maintaining a deeply ingrained culture of responsibility and in\nexecuting a governance architecture that adopts ethically sound practices at\nevery point in the innovation and implementation lifecycle.\u201d The goal is to\n\u201cunite an in-built culture of responsible innovation with a governance\narchitecture that brings the values and principles of ethical, fair, and safe\nAI to life.\u201d<\/p>\n\n\n\n<p>[1] Leslie, D. (2019). Understanding artificial intelligence\nethics and safety: A guide for the responsible design and implementation of AI\nsystems in the public sector. The Alan Turing Institute. <a href=\"https:\/\/doi.org\/10.5281\/zenodo.3240529\">https:\/\/doi.org\/10.5281\/zenodo.3240529<\/a><\/p>\n\n\n\n<p>[2] Data Ethics Framework (2018). <a href=\"https:\/\/www.gov.uk\/government\/publications\/data-ethics-framework\/data-ethics-framework\">https:\/\/www.gov.uk\/government\/publications\/data-ethics-framework\/data-ethics-framework<\/a>.<\/p>\n\n\n\n<p><strong>Principled Artificial Intelligence<\/strong><\/p>\n\n\n\n<p>In January, 2020,\nthe Berkman Klein Center released a <a href=\"https:\/\/cyber.harvard.edu\/publication\/2020\/principled-ai\">report<\/a> by Jessica Fjeld and Adam Nagy \u201cMapping Consensus in Ethical and\nRights-Based Approaches to Principles for AI\u201d, which summarizes contents of 36\ndocuments on AI principles.<\/p>\n\n\n\n<p>This work acknowledges the surge in frameworks based on ethical and human rights to guide the development and use of AI technologies. &nbsp;The authors focus on understanding ethics efforts in terms of eight key thematic trends: &nbsp;<\/p>\n\n\n\n<ul><li>Privacy<\/li><li>Accountability<\/li><li>Safety &amp; security<\/li><li>Transparency &amp; explainability<\/li><li>Fairness &amp; non-discrimination<\/li><li>Human control of technology<\/li><li>Professional responsibility<\/li><li>Promotion of human values<\/li><\/ul>\n\n\n\n<p>They report \u201cour 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.\u201d<br><\/p>\n\n\n\n<p><strong>Human-Centered AI<\/strong><\/p>\n\n\n\n<p>Prof. Ben Shneiderman recently presented his extensive work \u201cHuman-Centered AI: Trusted, Reliable &amp; Safe\u201d at the University of Arizona\u2019s <a href=\"https:\/\/cra.org\/ccc\/events\/assured-autonomy-workshop-2\/\">NSF Workshop<\/a> on \u201cAssured Autonomy\u201d. \u00a0His research emphasizes human autonomy as opposed to the popular notion of autonomous machines. His Open Access paper quickly drew 3200+ downloads. The ideas are now available in the <a href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/10447318.2020.1741118\"><strong>International Journal of Human\u2013Computer Interaction.<\/strong><\/a> The abstract is as follows: \u201cWell-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe &amp; Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.\u201d <\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Alan Turing Institute Public Policy Programme Among the complexities of public policy making, the new world of AI and data science requires careful consideration of ethics and safety in addressing complex and far-reaching challenges in the public domain. Data and AI systems lead to opportunities that can produce both good and bad outcomes. Ethical [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"categories":[12],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Policy and AI Ethics - ACM SIGAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sigai.acm.org\/main\/2020\/05\/03\/policy-and-ai-ethics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Policy and AI Ethics - ACM SIGAI\" \/>\n<meta property=\"og:description\" content=\"The Alan Turing Institute Public Policy Programme Among the complexities of public policy making, the new world of AI and data science requires careful consideration of ethics and safety in addressing complex and far-reaching challenges in the public domain. 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