How states can facilitate an AI ecosystem

Note: This is a joint op-ed with Kevin Frazier of the Abundance Institute.

Policymakers have an important opportunity to move from justified skepticism of Artificial Intelligence (AI) to pragmatic experimentation with its use. Many of the shortcomings associated with AI–high rates of hallucination, excessive sycophancy, and opaque processes–will be less prevalent in the near future as the models learn and grow.

AI labs are developing tools that can autonomously complete complex tasks with high rates of accuracy and auditability. All signs suggest that these tools will only become more capable with each passing day. As these exponential gains continue, pressure will mount on lawmakers to help existing institutions adapt and to support the creation of new businesses, programs, and regulatory frameworks. 

Those states that deliberately respond to that pressure have brighter futures ahead. Recent data indicates that young, fast-growing firms continue to create new jobs. AI pilots demonstrate that this technology can streamline and improve government services. Trials of AI tools in schools show that with the right scaffolding, students and educators can benefit tremendously from AI support. States that adopt a regulatory ecosystem supportive of those activities will draw new investments, new residents, and new opportunities. 

AI is only as useful as the data used to develop and apply models. Policymakers can assist students and educators, startups and nonprofits, and government offices in making full use of AI by developing robust data hubs. As of now, state data is often fragmented and maintained in a format that’s ill-suited for AI development and deployment. 

Lawmakers should consider the following actions to ensure their data is being put to its full use:

1. Mandate that agencies improve their data collection and storage practices; 

   
   

2. Create or further support data hubs that house high-quality datasets on pressing public policy issues such as education, healthcare, and workforce training;

   
   

3. Establish protocols for making that data available to third parties, subject to privacy protections and use limitations;

   
   

4. Investigate how to allow third parties to contribute their own data to the hub, which may require new laws or regulations specifying common definitions for data and standardized data collection practices; and

   
   

5. Evaluate processes by which any collected data could be shared with other states developing similar data hubs.

The AI tools made possible by better data collection and distribution will contribute to the general welfare if the state has the workforce in place to put these tools to use. Too few people have a meaningful understanding of the latest AI tools. They may use AI for basic tasks but have yet to explore more novel and transformational use cases. Policymakers can increase the odds of the best AI tools being used by cultivating and attracting AI talent. Several actions may assist with that work:

1. Launch or otherwise support the creation of a general AI training corps that can teach educators, small business owners, civil society leaders, and others to learn the ins and outs of AI;

   
   

2. Partner with existing research institutions, investor groups, and business development organizations to designate AI hubs–areas that are densely populated with nascent AI firms and educational programs–that foster information sharing and entrepreneurship; and

3. Update existing law to reflect new labor market realities by making benefits portable and initiating a review of existing occupational licenses to assess if their scope needs to be curtailed in light of the risks and benefits posed by that gatekeeping mechanism. 

The pros and cons of any AI use case are difficult to predict. Yet, fear of the unknown and a failure to appreciate the shortcomings of the status quo may cause policymakers to place unnecessarily high barriers to deployment. A failure to design pathways for AI companies to make their latest tools available may deprive residents of tools that could markedly improve their quality of life.

Delay in deployment could also cause the state’s government offices and businesses to lag behind their peers in improving existing operations and offering new goods and services. Lawmakers can establish an evidence-based approach to governing AI tool deployment and use by adopting the following policies: 

1. Build a regulatory sandbox program through which AI developers can deploy their tools subject to increased oversight, data sharing, and means for residents to share any harms or benefits;

2. Specify priority areas for AI use, such that applicants for the regulatory sandbox with tools addressing those areas receive expedited consideration; and

3. Start a grant program for researchers and startups to develop tools that may address those priority areas to spur in-state AI activity.

Those states that work to facilitate a functional AI ecosystem will be best positioned for efficient governance and economic success. The time to act is now.

Kevin Frazier is the Director of the AI Innovation and Law Program at the University of Texas School of Law and a Senior Fellow at the Abundance Institute. Chris Cargill is the President of Mountain States Policy Center, an independent free market think tank based in Idaho, Montana, Wyoming and Washington.