Employer-side witnesses urge national standard and internal governance over blanket bans
Loading...
Summary
Employer-side counsel and labor-law practitioners told the House panel that existing technology-neutral laws and robust internal governance can address many AI risks, warning that rushed state laws and agency overreach can create confusion for businesses.
Employer-side witnesses told the House subcommittee that measured, clear federal standards combined with strong internal governance are the best responses to workplace AI.
Bradford Kelly, a shareholder at Littler Mendelson, said the United States already has ‘‘a well established technology-neutral legal framework’’ that can address most AI misconduct and cautioned against a ‘‘rapid rush to enact new laws.’’ Kelly criticized a 2022 National Labor Relations Board general counsel memo, saying it introduced a ‘‘presumption’’ that many AI tools are unlawful and lacked clear definitions or stakeholder input.
David Walton, a partner at Fisher Phillips who founded his firm’s AI practice, described governance practices he said employers are using: cross-functional teams involving IT, HR and legal; bias-audit testing; human-in-the-loop requirements for major decisions; and training and reporting mechanisms. ‘‘These governance frameworks work,’’ Walton said, arguing that documented internal controls can reduce risk without blanket prohibitions.
Both witnesses criticized hastily drafted state measures, citing the Colorado AI Act and New York City rules as examples that created uncertainty. They recommended Congress consider a national standard to streamline compliance and avoid a patchwork of conflicting rules.
Opposing witnesses and some members countered that concrete harms already exist and agency enforcement is needed; the hearing reflected the partisan and substantive tension between precautionary regulation and avoiding undue restrictions on innovation.
No bills were passed at the hearing; members indicated continued interest in legislative and oversight responses.

