While the intention behind House Bill 4388 is a worthy attempt to reinforce a parent’s role in keeping kids safe online, the bill suffers from constitutional concerns and privacy risks that must be addressed before it becomes law. As other states have learned, through the passage of nearly identical legislation, the outcome of leaving these constitutional concerns and privacy risks unaddressed is wasted taxpayer dollars in attorneys’ fees without forward progress.  

The fact of the matter is that laws mandating age verification for social media platforms cut through the core of the First Amendment right to access speech and speak anonymously. Age verification laws also create unnecessary privacy risks by requiring online account holders and users to disclose personal information before accessing social media.  

All of this has held true across the states that passed bills that were nearly identical to HB 4388, and for the reasons outlined below, we urge this legislature to oppose this bill.  

HB 4388 is fraught with constitutional concerns 

The exact methods a social media company must use to comply with HB 4388’s age verification mandate is a mystery — the only hint provided by the bill as to the procedures and mechanisms for verifying age is that the attorney general (AG) must recommend more than just the use of a valid government-issued ID. This does not mean a government-issued ID is off the table; it just means it cannot be the only recommendation. While one should never speculate as to the recommendations that could be offered by the Michigan AG, when this bill was passed in Utah, the proposed alternative methods of privacy-invasive age verification included biometric facial scans, bank information requests, social security numbers, and more.

The same ambiguous delegation of authority is relied on for setting rules for confirming a parent is, indeed, the parent of a minor account user. Same for “retaining, protecting, and securely disposing” this information. As the Supreme Court has made clear, it is rare for such a burden on the First Amendment to survive legal scrutiny.

Other states that passed HB 4388 have not been successful in court 

Not even Utah follows this approach, despite being the first state in the country to pass a near-identical bill in 2023. In fact, exactly one month after the first complaint was filed in a lawsuit over Senate Bill 152, alleging that the bill violated the First Amendment, the AG requested that the court reschedule hearings due to the legislature completely rewriting the law and pushing back the effective date. The new law that followed, Utah Senate Bill 194, was enjoined for violating the First Amendment.

Other states that have passed nearly identical laws as HB 4388 have either lost in court, been forced to delay effective dates, or are now awaiting hearings. This includes Arkansas (permanent injunction), Georgia (preliminarily enjoined), Louisiana (pending judgment, effective date delayed), and Tennessee (pending judgment), with Nebraska likely to be added to that list within the year.

Similar, though not identical, bills have found the same to be true. This includes California’s Senate Bill 976, which was blocked by the district court and the Ninth Circuit on appeal. Another similar bill, Mississippi’s House Bill 1126, was also struck down by the courts. The list goes on, including Texas, Ohio, and Maryland.

HB 4388 ignores clear privacy risks inherent in age verification 

As has been fleshed out over time, “commercially available methods” involve handing over sensitive information like a government ID, biometric facial scan data, social security numbers, banking information, and more. This information, and the process used to gather and collect it, has not only led to privacy risks but also painted a target on the backs of companies collecting it, resulting in significant data breaches that could have been prevented had these laws not been in place.

Thank you for the opportunity to submit this written testimony, and we welcome the opportunity to advise the legislature on this subject in the future.  

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The Technology Policy Project at Reason Foundation has provided pro bono consulting to public officials and stakeholders to help them design and implement technology policy reforms around the regulation of artificial intelligence (AI) and other emerging technologies, digital free speech, data security and privacy, child online safety, and tech industry competition policy. Our team brings practical, market-oriented strategies to help foster innovation, competition, and consumer choice through technology policies that work.  

We submit this written testimony on House Bill 392 as an interested party.   

HB 392 is similar to other state legislation in that it creates a “Right to Compute.” This right to compute is a critical affirmative right for innovators, as it requires a state legislature to carefully weigh the compliance burdens of proposed, potentially heavy-handed legislation and affords innovators a right of redress when such burdens are imposed.   

The bill is an excellent first start, but two areas for improvement currently limit its intended effect. These problems revolve around the bill’s definition of  “compelling governmental interests.” As written, the bill would still allow for a state agency or political subdivision to impose burdens on innovators in two key areas.  

First, the bill makes AI-generated content the basis of a “compelling governmental interest” for further regulation or legislation, but does not specify the actor creating such content. Leaving this definition vague opens the door for laws that would punish an AI company rather than the person using an AI model with nefarious intent—an onerous legislative proposal that would be impossible to comply with. Such a law was proposed in California, and because of its unreasonable burdens on AI companies, Gov. Gavin Newsom vetoed the bill. These types of bills are not one-off bad ideas. Though well-intentioned, they fly in the face of the core intent of HB 392: to unburden innovators from impossible compliance demands so as to allow the U.S. to develop next-generation technologies that compete with the rest of the world.   

Second, aside from the public process of approving new construction on a data center, carving out exceptions for laws and local ordinances that undermine data centers under the veil of “public nuisance” law would ignore the possibility that hostile localities would create ordinances after the fact to hike up energy rates and extract revenue from data centers once they’re built. The U.S. needs more—not less—data center capacity, which is contemplated in Right to Compute legislation passed elsewhere.   

Thank you for the opportunity to submit this written testimony, and we welcome the opportunity to advise the legislature on this subject in the future.  

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On behalf of Reason Foundation, we respectfully submit these comments in response to the Office of Science and Technology Policy’s (OSTP’s) request for information on “Regulatory Reform on Artificial Intelligence.”

Reason Foundation is a national 501(c)(3) public policy research and education organization with expertise across a range of policy areas, including technology and communications policy.

There are numerous activities, innovations, and deployments currently inhibited, delayed, or constrained by federal statute, regulation, or policy. For this reason, we recommend a formal audit or review to identify areas of regulatory conflict with innovation—including the effect of state laws where federal regulation is silent. However, we offer the following specific examples in response to Question (i) for OSTP’s review:

1. Legacy NEPA Rules and Expansion Create Major Delays in Energy Production
2. Regulatory Barriers Limit the Expansion of Automated Track Inspection

Legacy NEPA rules and expansion create major delays in energy production

In order to maintain global technological superiority, the United States must focus squarely on reforms that increase energy capacity through streamlined permitting reforms in order to facilitate the development of artificial intelligence (AI) across industries. As of now, multi-year permitting delays are the status quo in any energy project. These delays set back the construction of new power plants, but also lead to the downstream effects of a restricted energy grid. As the United States competes with foreign adversaries for dominance in AI, energy capacity will either be a force multiplier in the country’s success or lead to failure on the global stage.

Congress passed the National Environmental Policy Act (NEPA) in 1969, directing federal agencies to evaluate the environmental impact of their decision-making prior to a major federal action. As part of this directive, agencies were required to produce an Environmental Impact Statement (EIS) when a federal action would significantly alter the environment, which is to include a comprehensive analysis of environmental effects, alternatives to the proposed action, and proposed mitigation measures (42 U.S.C. § 4332).

For federal actions that would impose smaller effects on the environment or where the size of the effect is uncertain, agencies must complete an Environmental Assessment (EA). An EA is a shorter-form document that aims to determine whether a proposed federal action warrants a full EIS or if the effects are small enough to render a Finding of No Significant Impact (FONSI). These mandated reviews were meant to inform both decision-makers and the public of potential significant environmental impacts and potential mitigations, but have evolved into increasingly lengthy and complex processes. Further, despite their extensive documentation, these reviews generate a substantial amount of litigation. As a result, the environmental review process that was designed to increase public transparency increasingly serves to delay and add costs to worthy projects.

For instance, the Nuclear Regulatory Commission (NRC) promulgated licensing rules that incorporate NEPA’s environmental review framework into nuclear power project approvals (10 C.F.R. Part 51). These NRC licensing processes have traditionally entailed lengthy reviews and administrative hurdles, delaying and often derailing reliable energy projects that could support AI infrastructure. Similarly, power grid interconnection regulations governed by the Federal Energy Regulatory Commission (FERC) under 16 U.S.C. § 824a et. seq. impose restrictive control over how new loads such as AI data centers connect to the grid. Lengthy wait times and cost allocation disputes in FERC’s interconnection queues compound delays to reliable, scalable power delivery essential to AI model performance.

The Supreme Court’s decision in Seven County Infrastructure Coalition v. Eagle County curtailed this expansion of agency review. Moreover, recent reforms, such as the expansion of categorical exclusions, recent executive orders on permit streamlining, and the U.S. Court of Appeals for the D.C. Circuit’s Marin Audubon Society ruling, may remove some of the chokepoints.

However, legacy NEPA implementation and statutes built upon decades of overexpansion continue to impose substantial procedural burdens on AI-related infrastructure—particularly energy.

As the need for abundant energy production grows more vital, this regulatory barrier to energy production is particularly relevant in light of small modular nuclear reactors (SMRs), which have emerged as a promising source of clean, abundant energy to power the energy-intensive AI data centers at the heart of U.S. technological superiority.

Regulatory barriers limit the expansion of automated track inspection

Automated track inspection (ATI) technologies have been tested in recent years to improve railway track defect detection and have the potential to improve rail safety while also increasing operational efficiency of the network. Instead of shutting down tracks for human inspectors to walk, or using specialized rail vehicles to inspect track visually, ATI sensors are mounted to trains as they are in service to collect track component data as part of normal rail operations. These robust sensor data are then fed to AI-powered models to better plan maintenance activities.

Through pilot programs established by railroads, which obtained waivers from the Federal Railroad Administration (FRA), ATI was demonstrated to more reliably detect defects than traditional inspections—and improve maintenance forecasting and planning over time. Pilot program data submitted to FRA show that defects per 100 miles of inspected track declined from 3.08 before the use of ATI to 0.24 during the ATI pilots, or a 92.2% reduction. Reportable track-caused train derailments on main track per year during that same period declined from eleven to three, or a 72.7% reduction. None of those three derailments was attributable to ATI-targeted defects, with two occurring while manual visual inspections were still taking place twice weekly and one while pilot testing was inactive.

These results are in line with successful ATI performance expectations, with a shift in maintenance practices from being guided by a “find and fix” approach to a “predict and prevent” approach. Better and earlier detection of geometry defects allows track maintenance to be performed in a more preventative manner. Further, the higher-quality data collected by ATI over time allows for AI-powered improvements to maintenance forecasting and strategy. As such, as ATI use is expanded and repeated over time, defect detection rates—and defect-related hazards—should decline.

Realizing the benefits of ATI requires changes to manual inspection practices. ATI cannot inspect turnouts (i.e., the point where trains switch from one track to another), turnout components (e.g., “frogs”), and other special trackwork. By focusing ATI on track geometry defects, human inspectors can be redeployed to infrastructure where they are best positioned to inspect. If legacy visual inspection requirements are not modernized, railroads will have less incentive to invest in ATI and improve their inspection practices.

Analysis of the ATI pilot program data found that visual inspectors identified far more non-geometry defects than track geometry defects. Prior to ATI testing on the pilot corridors, visual inspectors identified 10,645 non-geometry defects and 422 geometry defects. In 2021, during the ATI pilots, visual inspectors identified 14,831 non-geometry defects (a 39.3% increase) and 238 geometry defects (a 43.6% decrease). Of the non-geometry defects identified by visual inspectors, 60-80% were in turnouts and special trackwork that ATI cannot inspect.

Another important benefit of ATI is reducing visual inspectors’ exposure to on-track hazards. Substituting ATI for routine geometry defect inspection, coupled with a corresponding reduction in visual inspections, will remove inspectors from harm’s way. Data from the ATI pilot program indicate that inspector track occupancy duration declined by approximately one-quarter after visual inspections were reduced to once per week as part of the ATI pilots, suggesting substantial inspector workforce safety risk reductions are likely to occur if ATI is widely deployed.

The Association of American Railroads recently petitioned for an industry-wide waiver to enable significantly expanded ATI deployments. The necessity of a waiver is indicative of the inflexibility of legacy rail safety regulations, which mandate rigid manual visual inspection frequencies (49 C.F.R. § 213.233). Importantly, these long-standing inspection frequency rules are based on questionable assumptions about accumulated tonnage loads and lack the scientific rigor that ought to guide safety policy. FRA has yet to act on the pending ATI waiver petition, thereby preventing rail carriers, rail workers, shippers, and consumers from realizing the safety and efficiency benefits of ATI.

Conclusion

We greatly appreciate OSTP’s attention to regulatory barriers to the development and deployment of AI technologies. Realizing the full benefits of these various technologies and applications will require a sustained, concerted effort on the part of policymakers.

Thank you for the opportunity to provide these comments to OSTP. We look forward to further participation and stand by to assist as requested.

Download the full public comment:

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