Synthetic Intelligence Forum is excited to convene a presentation about the AI Accountability Framework issued by the US Government Accountability Office (GAO) with Taka Ariga, the Chief Data Scientist and Director of Innovation Lab at the US GAO.

Title: US Government Accountability Office AI Accountability Framework

Abstract: This presentation will outline the AI accountability framework, issued by the US Government Accountability Office (GAO), to ensure responsible, equitable, traceable, reliable, and governable AI. This framework is organized around four components that address governance, data, performance, and monitoring. GAO described practices for Federal agencies and other entities that are considering, selecting, and implementing AI for each of these principles.

The work for the framework was conducted from February 2020 to June 2021, in accordance with all sections of GAO’s Quality Assurance (QA) Framework. This QA framework required that GAO plan and perform engagement to obtain adequate and relevant evidence to meet objectives and surface any deficiencies in the work. The GAO used input from government, industry and nonprofit experts to develop a framework on the responsible use of AI technology. Auditors, third-party examiners and other interested parties are encouraged use the framework to answer questions as well as adopt procedures to support the responsible use of AI.

Biography: Taka Ariga is GAO’s first Chief Data Scientist and Director of the Innovation Lab. As an integral part of the Science, Technology Assessment, and Analytics team, he will help GAO develop and implement advanced analytical capabilities for its auditing practices. Prior to joining GAO, he held executive positions at Deloitte, Ernst & Young, and Booz Allen Hamilton, where he worked with audit, compliance, legal, and regulated entities.

Profiles of the host and presenter:
• Vik Pant, PhD – https://www.linkedin.com/in/vikpant
• Taka Ariga – https://www.linkedin.com/in/jeremieharris/

Web resources pertaining to US GAO AI Governance Framework:
• Website – https://www.gao.gov/products/gao-21-519sp
• Report – https://www.gao.gov/assets/gao-21-519sp.pdf

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