TL;DR:
- Google supports a decentralized “hub-and-spoke model” of national AI regulation.
- The model emphasizes sector-specific regulators and discourages a centralized “Department of AI.”
- Google proposes utilizing existing authorities to expedite governance and align AI with traditional rules.
- Sectoral regulators can better address AI challenges in areas such as finance, healthcare, education, and transportation.
- The R Street Institute echoes Google’s stance and highlights the potential hindrance of a one-size-fits-all approach to AI regulation.
Main AI News:
In the realm of artificial intelligence (AI), Google and its renowned AI lab DeepMind are leading the charge toward effective and prudent regulation. They have embraced a decentralized approach to regulating new generative AI tools such as the ChatGPT and Bard large language models, recognizing the immense potential these technologies hold. Google rightly acknowledges that AI can unlock significant benefits, ranging from advancements in disease understanding to combatting climate change and fostering economic growth through expanded opportunities.
To harness these benefits, Google proposes a “hub-and-spoke model” of national AI regulation, which stands in stark contrast to the ill-conceived centralized, top-down licensing scheme put forth by rival AI developers OpenAI and Microsoft. This proposal is detailed in Google’s response to the National Telecommunications and Information Administration’s (NTIA) request for comments on AI system accountability measures and policies, issued in April 2023. The NTIA sought public input, specifically on self-regulatory and regulatory measures that ensure the legality, effectiveness, ethics, safety, and overall trustworthiness of AI systems for external stakeholders.
At the core of Google’s comment is the endorsement of a national-level hub-and-spoke approach, where a central agency like the National Institute of Standards and Technology (NIST) informs sectoral regulators responsible for overseeing AI implementation. In contrast, Google firmly opposes the establishment of a dedicated “Department of AI.” NIST has already taken proactive measures by launching its Artificial Intelligence Risk Management Framework in January, indicating its commitment to managing the risks associated with AI.
Google emphasizes that AI presents unique challenges in various sectors, such as financial services, healthcare, and other regulated industries. To address these challenges effectively, sectoral regulators with expertise in specific domains should utilize existing authorities to expedite governance and align AI with traditional rules. Google argues that this approach is far more effective than creating a new regulatory agency tasked with promulgating and implementing rigid rules that may not adapt well to the diverse contexts of AI deployment.
The alignment between AI regulation and specific sectors is crucial. Regulators overseeing financial services can focus on AI’s impact on loan approvals and credit reporting, while medical regulators can better assess diagnostic accuracy and healthcare privacy concerns. Similarly, educational institutions and agencies can evaluate how AI influences student learning, and transportation officials can monitor the progress of self-driving vehicles. This sectoral approach complements NIST’s AI Risk Management Framework, which is designed to be flexible, align with existing risk practices, and adapt to emerging risks.
The R Street Institute, a prominent free market think tank, supports Google’s stance in its response to the NTIA. The institute concurs that the NTIA and other potential regulators tend to highlight worst-case scenarios when it comes to deploying new AI tools. Consequently, AI innovations are burdened with an undue presumption of guilt and are subject to onerous and costly certification processes before entering the market.
Similar to Google, the R Street Institute recognizes that AI technologies hold immense potential for improving living standards, healthcare, transportation, community safety, education, and financial services. Imposing a pre-market licensing scheme administered by a Department of AI would severely impede Americans’ access to the substantial benefits these systems and technologies offer.
Conclusion:
Google’s advocacy for a decentralized approach to AI regulation, focused on sector-specific expertise, reflects a recognition of the diverse challenges posed by AI implementation. By avoiding a centralized regulatory body and instead leveraging existing authorities, the market can benefit from tailored governance and expedited decision-making. This approach aligns with fostering innovation while ensuring accountability and responsible deployment of AI technologies.
