{"id":65359,"date":"2018-12-07T18:13:39","date_gmt":"2018-12-07T23:13:39","guid":{"rendered":"http:\/\/danielschristian.com\/learning-ecosystems\/?p=65359"},"modified":"2018-12-07T18:33:53","modified_gmt":"2018-12-07T23:33:53","slug":"ai-now-report-2018-10-recommendations-for-ai-ai-now-institute","status":"publish","type":"post","link":"https:\/\/danielschristian.com\/learning-ecosystems\/2018\/12\/07\/ai-now-report-2018-10-recommendations-for-ai-ai-now-institute\/","title":{"rendered":"AI Now Report 2018: 10 Recommendations for AI [AI Now Institute]"},"content":{"rendered":"

AI Now Report 2018 | December 2018 <\/strong><\/a>\u00a0— from\u00a0ainowinstitute.org<\/p>\n

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
\nKate Crawford , AI Now Institute, New York University, Microsoft Research
\nRoel Dobbe , AI Now Institute, New York University
\nGenevieve Fried , AI Now Institute, New York University
\nElizabeth Kaziunas , AI Now Institute, New York University
\nVaroon Mathur , AI Now Institute, New York University
\nSarah Myers West , AI Now Institute, New York University
\nRashida Richardson , AI Now Institute, New York University
\nJason Schultz , AI Now Institute, New York University School of Law
\nOscar Schwartz , AI Now Institute, New York University<\/p>\n

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)<\/p>\n

Excerpt (emphasis DSC):<\/span><\/em><\/p>\n

Building on our\u00a02016<\/strong><\/a>\u00a0and\u00a02017<\/strong><\/a>\u00a0reports, the\u00a0AI Now 2018 Report<\/strong><\/a>\u00a0contends with this central problem, and provides 10 practical recommendations\u00a0<\/strong>that can help create accountability frameworks capable of governing these powerful technologies.<\/p>\n

    \n
  1. Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.<\/li>\n
  2. Facial recognition and affect recognition need stringent regulation to protect the public interest.<\/li>\n
  3. The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.<\/li>\n
  4. AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.<\/li>\n
  5. Technology companies should provide protections for conscientious objectors, employee organizing, and ethical whistleblowers.<\/li>\n
  6. \u00a0Consumer protection agencies should apply \u201ctruth-in-advertising\u201d laws to AI products and services.<\/li>\n
  7. Technology companies must go beyond the \u201cpipeline model\u201d and commit to addressing the practices of exclusion and discrimination in their workplaces.<\/li>\n
  8. Fairness, accountability, and transparency in AI require a detailed account of the \u201cfull stack supply chain.\u201d<\/li>\n
  9. More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.<\/li>\n
  10. University AI programs should expand beyond computer science and engineering disciplines.<\/strong> <\/span>AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.<\/span><\/li>\n<\/ol>\n

     <\/p>\n

    Also see:<\/em><\/span><\/p>\n

    After a Year of Tech Scandals, Our 10 Recommendations for AI<\/strong><\/a>\u00a0— from\u00a0medium.com by the\u00a0AI Now Institute
    \nLet\u2019s begin with better regulation, protecting workers, and applying \u201ctruth in advertising\u201d rules to AI<\/em><\/p>\n

     <\/p>\n

    Also see:<\/em><\/span><\/p>\n

    \"\"<\/a><\/p>\n

    Excerpt:<\/em><\/p>\n

    As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we\u2019ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We\u2019ve learned more and tested new ideas. Based on this work, we believe it\u2019s important to move beyond study and discussion. The time for action has arrived.<\/p>\n

    We believe it\u2019s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.<\/p>\n

    In particular, we don\u2019t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.<\/p>\n

     <\/p>\n

    From DSC:<\/span><\/em>
    \nThis is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them!\u00a0<\/strong><\/span><\/p>\n

    The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.<\/strong><\/span><\/p><\/blockquote>\n

     <\/p>\n

     <\/p>\n","protected":false},"excerpt":{"rendered":"

    AI Now Report 2018 | December 2018 \u00a0— from\u00a0ainowinstitute.org Meredith Whittaker , AI Now Institute, New York University, Google Open Research Kate Crawford , AI Now Institute, New York University, Microsoft Research Roel Dobbe , AI Now Institute, New York University Genevieve Fried , AI Now Institute, New York University Elizabeth Kaziunas , AI Now […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[113,556,139,356,817,387,174,86,115,302,45,112,210,403,816,37,35,63,3,391,547,419,180,482,55,825,285,511,216,353,44,309,204,480,293,212,40,460,454,195,206,321,214,367,11,299],"tags":[],"class_list":["post-65359","post","type-post","status-publish","format-standard","hentry","category-21st-century","category-amazon","category-apple","category-artificial-intelligence-agents-llms-and-related","category-bots","category-business","category-career-development","category-change","category-colleges","category-community-colleges","category-computer-science","category-corporate-business-world","category-emerging-technologies","category-ethics","category-facebook","category-future","category-game-changing-environment","category-google","category-higher-education","category-human-computer-interaction-hci","category-ibm","category-ideas-teaching","category-innovation","category-intelligent-systems","category-internet","category-law-schools","category-legislation-legislatures","category-machine-to-machine-communications","category-microsoft","category-moralsvalues","category-pace-of-change","category-platforms","category-programming","category-society","category-sociology","category-surviving","category-technologies-for-your-home","category-technology-general","category-the-downsides-of-technology","category-tools","category-trends","category-united-states","category-universities","category-vendors","category-vision-possibilities","category-workplace"],"_links":{"self":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/65359","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/comments?post=65359"}],"version-history":[{"count":10,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/65359\/revisions"}],"predecessor-version":[{"id":65370,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/65359\/revisions\/65370"}],"wp:attachment":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/media?parent=65359"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/categories?post=65359"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/tags?post=65359"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}