Advancing Artificial Intelligence and Machine Learning in the U.S. Government Through Improved Public Competitions

• URL: http://arxiv.org/abs/2112.01275v1
• Date: Mon, 29 Nov 2021 16:35:38 GMT
• Title: Advancing Artificial Intelligence and Machine Learning in the U.S. Government Through Improved Public Competitions
• Authors: Ezekiel J. Maier
• Abstract summary: In the last two years, the U.S. government has emphasized the importance of accelerating artificial intelligence (AI) and machine learning (ML) The U.S. government can benefit from public artificial intelligence and machine learning challenges through the development of novel algorithms and participation in experiential training. Herein we identify common issues and recommend approaches to increase the effectiveness of challenges.
• Score: 2.741266294612776
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In the last two years, the U.S. government has emphasized the importance of accelerating artificial intelligence (AI) and machine learning (ML) within the government and across the nation. In particular, the National Artificial Intelligence Initiative Act of 2020, which became law on January 1, 2021, provides for a coordinated program across the entire federal government to accelerate AI research and application. The U.S. government can benefit from public artificial intelligence and machine learning challenges through the development of novel algorithms and participation in experiential training. Although the public, private, and non-profit sectors have a history of leveraging crowdsourcing initiatives to generate novel solutions to difficult problems and engage stakeholders, interest in public competitions has waned in recent years as a result of at least three major factors: (1) a lack of high-quality, high-impact data; (2) a narrow engagement focus on specialized groups; and (3) insufficient operationalization of challenge results. Herein we identify common issues and recommend approaches to increase the effectiveness of challenges. To address these barriers, enabling the use of public competitions for accelerating AI and ML practice, the U.S. government must leverage methods that protect sensitive data while enabling modelling, enable easier participation, empower deployment of validated models, and incentivize engagement from broad sections of the population.

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