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Stephen Lynch

U.S. representative from Massachusetts

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Portrait source: US House of Representatives, Public domain

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While financial institutions, financial technology companies, and government agencies are already utilizing artificial intelligence to facilitate the detection of financial crime, risk analysis, personalized customer services, consumer lending, and other critical functions, the evolving application of A.I.

Exact quote, beginning

Stephen Lynch

U.S. representative from Massachusetts

In a 2024 House press release, Stephen Lynch called for robust federal oversight and adaptive regulation of AI in financial services to identify risks to consumers.

U.S. Representative for Massachusetts's 8th Congressional District and Ranking Member of the Subcommittee on Digital Assets, Financial Technology and InclusionPublished January 12, 2024 · date of remarks not establishedRep. Lynch Named Lead

SourceArchived
Context and checks

Surrounding words

“As Ranking Member of the Subcommittee on Digital Assets, Financial Technology and Inclusion, I am proud to serve as the lead Democrat on the new bipartisan Working Group on Artificial Intelligence,” said Congressman Lynch. “While financial institutions, financial technology companies, and government agencies are already utilizing artificial intelligence to facilitate the detection of financial crime, risk analysis, personalized customer services, consumer lending, and other critical functions, the evolving application of A.I. technologies must be paralleled by robust federal oversight and a regulatory framework that is adaptive to innovation and equipped to identify potential risks to American consumers. Following the recent determination by the Financial Stability Oversight Council identifying A.I.

What this quote does not say

  • The statement is an office-hosted quotation rather than a signed authored document or recording.
  • Its risk framing is narrower than existential risk and focuses on consumers and financial stability.

How this was checked

  • Quote matched character-for-character against the captured page.

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