Artificial intelligence regulation by administration
Artificial Intelligence Regulation by Administration: Overview
Administrative regulation refers to rules and guidelines issued by government agencies that oversee specific industries or sectors. When it comes to AI, regulation by administration involves agencies creating policies, standards, and enforcement mechanisms to manage AI’s development and use, particularly in areas such as privacy, safety, fairness, transparency, and accountability.
This regulatory approach can be more flexible and specialized compared to legislation because agencies can update rules quickly to keep pace with AI’s rapid technological changes. However, challenges arise about the agencies' authority, due process, and how to balance innovation with protection of public interests.
Key Case Laws on AI Regulation by Administration
1. FCC v. Prometheus Radio Project, 141 S. Ct. 1150 (2021)
While this case doesn't directly deal with AI, it is important because it clarifies administrative agencies’ obligations in rulemaking, which applies to AI regulations too.
Facts & Issue:
The Federal Communications Commission (FCC) sought to change its ownership rules. The Prometheus Radio Project challenged the FCC’s decision, arguing it failed to provide a reasoned explanation for its new policy.
Holding:
The Supreme Court ruled that agencies must provide reasoned explanations when changing policies, especially when it impacts significant reliance interests.
Relevance to AI:
When agencies regulate AI—e.g., issuing new rules on data usage or automated decision-making—they must clearly justify changes and consider the impact on stakeholders. This ensures transparency and accountability in AI regulation.
2. FCC v. Fox Television Stations, 556 U.S. 502 (2009)
Another foundational case about administrative rulemaking standards.
Facts & Issue:
The FCC changed its policy regarding “fleeting expletives” and fined TV stations without clear prior notice.
Holding:
The Supreme Court held that agencies must provide fair notice to regulated parties before enforcing new rules or policies.
Relevance to AI:
For AI systems regulated by agencies, companies need clear guidelines in advance, particularly regarding compliance with privacy or safety standards to avoid arbitrary enforcement.
3. State v. Loomis, 881 N.W.2d 749 (Wis. 2016)
This is a landmark case related specifically to AI use in judicial sentencing.
Facts & Issue:
Eric Loomis challenged his sentence, arguing that the use of a proprietary AI risk assessment tool (COMPAS) violated due process because it was a “black box,” and he couldn’t see how it worked or challenge its accuracy.
Holding:
The Wisconsin Supreme Court upheld the use of COMPAS but emphasized the need for transparency and cautioned judges not to rely solely on the algorithm.
Relevance:
This case highlights administrative oversight and regulation challenges of AI, especially in sensitive areas like criminal justice. Agencies regulating AI tools must enforce transparency and fairness, balancing innovation with fundamental rights.
4. United States v. Microsoft Corp., 584 F. Supp. 2d 57 (D.D.C. 2008)
While primarily an antitrust case, it touches on administrative control over technology companies.
Facts & Issue:
The government alleged Microsoft abused its market dominance by bundling its browser with Windows.
Holding:
The case showed how administrative bodies can intervene to regulate technology that has broad societal impact.
Relevance to AI:
AI companies with market power can be subject to administrative regulations preventing anti-competitive practices, ensuring fair access and innovation.
5. In re Google Location History Litigation, 2021
This case illustrates administrative enforcement and regulatory powers over AI-driven data collection.
Facts & Issue:
Google was accused of collecting users' location data without proper consent, violating privacy laws and administrative rules.
Outcome:
Administrative bodies and courts emphasized the need for clear, enforceable standards on AI data privacy and user consent.
Relevance:
Regulators use administrative rules to ensure AI systems respect user privacy, requiring explicit consent and transparency about data use.
6. Algorithmic Accountability Act (proposed regulatory framework in the U.S.)
Though not a case, this proposed legislation reflects how administrative agencies might be empowered to regulate AI.
Key Points:
Requires companies to conduct impact assessments for automated decision systems.
Empowers agencies like the FTC to enforce transparency and fairness.
Relevance:
This signals a shift towards formal administrative regulation of AI, backed by legal authority, similar to existing environmental or financial regulations.
Summary of Themes in AI Regulation by Administration
Reasoned Rulemaking: Agencies must justify AI regulations with clear reasoning to withstand judicial review. (FCC v. Prometheus)
Fair Notice: AI developers and users must have clear, accessible guidelines before enforcement. (FCC v. Fox)
Transparency and Due Process: AI tools affecting individuals (e.g., sentencing algorithms) require transparency to avoid due process violations. (State v. Loomis)
Competition Oversight: AI firms may be subject to antitrust or market regulations to prevent abuse of power. (US v. Microsoft)
Privacy Protections: Administrative enforcement plays a key role in ensuring AI respects data privacy laws. (Google Location History Litigation)
Emerging Legislative-Administrative Hybrid Regulation: Agencies will likely gain expanded authority to regulate AI proactively through frameworks like the Algorithmic Accountability Act.
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