America's Next 'Stop Model!': Algorithmic Disgorgement
SSRN Electronic Journal
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
This Article explores the emergence of model deletion–the compelled destruction or dispossession of certain data, algorithms, models, and associated work products created or shaped by illegal means--as a remedy, right, and requirement for artificial intelligence and machine learning systems. Part I examines model deletion's emergence as a consumer protection remedy and conception as a positive right and regulatory requirement. Part II considers the constellation of Federal and State actors who might seek model deletion to address particular AI and ML harms and violations of law, including Federal and State enforcement agencies and legislative bodies. Part III underscores the need to legislate broader privacy and data protection regulation to bolster the effectiveness of model deletion. Part IV reflects on the challenges of model deletion, including the scope and enforcement of model deletion orders and logistical issues for companies undergoing model deletion. Part V envisions two speculative case studies for model deletion: Clearview and Securus.
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