To enact section 4113.90 of the Revised Code regarding the use of automated employment decision tools.
HB 828 would add a new section to the Ohio Revised Code regulating the use of automated employment decision tools in hiring and other employment decisions. The bill defines these tools broadly to include systems based on machine learning, statistical modeling, data analytics, or artificial intelligence that produce a score, classification, or recommendation used to support or replace human discretion in employment determinations.
Under the bill, employers, employment agencies, and personnel placement services could not rely solely on an automated tool when making decisions about hiring, promotion, retention, discipline, dismissal, or contract renewal. Any use of such a tool would have to be reviewed for accuracy by a human reviewer. The bill also requires advance written notice to workers or applicants at least ten days before the tool is used, including information about the tool’s criteria, the data inputs and sources, and the employer’s data-retention policy. It further gives workers and prospective workers the right to request an alternative assessment that does not use an automated tool, which the employer must then use.
The bill would create new statutory duties for Ohio employers, employment agencies, and personnel placement services that use AI or other automated decision systems in employment decisions. It would establish notice, disclosure, human-review, and alternative-assessment requirements, and would likely affect hiring and personnel practices, vendor compliance, and internal recordkeeping policies. The measure would also give workers and applicants a procedural right to avoid automated evaluation if they request an alternative process.
Because HB 828 was only introduced and has no recorded votes or committee testimony in the provided materials, there is no formal legislative record of support or opposition to gauge sentiment. The bill’s sponsors and cosponsors suggest interest in increasing oversight of AI-driven employment practices, and the overall framing indicates a consumer- and worker-protection approach. At the same time, the absence of hearing records means there is no documented committee debate yet on the bill’s merits or drawbacks.
The main likely point of contention is the bill’s restriction on automated hiring and employment tools, especially the requirement that a human reviewer verify outputs and that workers be allowed to opt for an alternative assessment. Employers and staffing firms may view these requirements as burdensome, costly, or difficult to implement, particularly where AI tools are integrated into large-scale recruiting systems. Supporters are likely to argue that the bill is needed to prevent overreliance on opaque algorithms, reduce bias, and ensure transparency and human accountability in employment decisions.