We put a stop to the A Level grading algorithm! Last accessed 25 October 2021. Home Office says it will abandon its racist visa algorithm - after we sued them. Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.
David Freeman Engstrom and Daniel E Ho.Independent auditors are struggling to hold AI companies accountable. Layers of bias: A unified approach for understanding problems with risk assessment. Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook, and Julie Ciccolini.Journal of applied corporate finance 24, 2 (2012), 65-71. The need for sector-specific materiality and sustainability reporting standards. Robert G Eccles, Michael P Krzus, Jean Rogers, and George Serafeim.Towards intellectual freedom in an AI Ethics Global Community. Christoph Ebell, Ricardo Baeza-Yates, Richard Benjamins, Hengjin Cai, Mark Coeckelbergh, Tania Duarte, Merve Hickok, Aurelie Jacquet, Angela Kim, Joris Krijger, et al.Improving the confectionery industry supply chain through second party audits. Ilija Djekic, Sladjana Dragojlovic, Zoran Miloradovic, Snezana Miljkovic-Zivanovic, Marija Savic, and Vesna Kekic.Double Standards in Social Media Content Moderation. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, and Daniel E Ho.Introducing Twitter's first algorithmic bias bounty challenge. In Conference on Fairness, Accountability and Transparency. A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. Alexandra Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, and Rhema Vaithianathan.Therapeutic innovation & regulatory science 52, 1 (2018), 62-69. A comparative study of medical device regulations: US, Europe, Canada, and Taiwan. Yi-Jung Chen, Chi-Ming Chiou, Yu-Wen Huang, Pei-Weng Tu, Yung-Chuan Lee, and Chia-Hung Chien.In Conference on fairness, accountability and transparency. Gender shades: Intersectional accuracy disparities in commercial gender classification. Facebook shut down German research on Instagram algorithm, researchers say. Esg investing: Practices, progress and challenges. Strengthening the financial reporting system: can audit committees deliver? International journal of auditing 14, 2 (2010), 174-210. Organic Certification of Farms and Businesses Producing Agricultural Products., 8 pages. Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner.Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1-30. Discrimination through optimization: How Facebook's Ad delivery can lead to biased outcomes. Muhammad Ali, Piotr Sapiezynski, Miranda Bogen, Aleksandra Korolova, Alan Mislove, and Aaron Rieke.We conclude that the turn toward audits alone is unlikely to achieve actual algorithmic accountability, and sustained focus on institutional design will be required for meaningful third party involvement. Finally, we survey the evidence base around these design components and spell out the implications for algorithmic auditing. Second, we survey audit systems across domains - e.g., financial, environmental, and health regulation - and show that the institutional design of such audits are far from monolithic. First, we discuss the challenges of third party oversight in the current AI landscape.
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Our paper synthesizes lessons from other fields on how to craft effective systems of external oversight for algorithmic deployments. But existing algorithmic accountability policy approaches have neglected the lessons from non-algorithmic domains: notably, the importance of third parties. Much attention has focused on algorithmic audits and impact assessments to hold developers and users of algorithmic systems accountable.
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