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Artificial Intelligence and the Law: Analyzing Potential Criminal Violations and Necessary Industry Reforms

Various legal analyses, including advisories from the California Attorney General (AG), indicate that the business practices of AI companies may violate existing laws.

Author

Pascal Hetzscholdt
January 29, 2025


Artificial Intelligence and the Law: Analyzing Potential Criminal Violations and Necessary Industry Reforms

by ChatGPT-4o

Introduction

The rapid advancement of artificial intelligence (AI) has resulted in significant legal and ethical challenges. Various legal analyses, including advisories from the California Attorney General (AG), indicate that the business practices of AI companies may violate existing laws in areas such as consumer protection, data privacy, and anti-discrimination statutes. This essay aims to provide a thorough examination of these legal concerns, evaluate whether certain flagged behaviors constitute criminal activity, identify additional problematic practices based on Substack posts and legal analyses, and suggest how AI developers could have preempted these issues and should now remedy them.

AI and Potential Criminal Violations

Several practices of AI companies, as outlined in legal advisories and industry critiques, may not only be unethical but could also constitute criminal behavior under existing laws.

1. Deceptive Practices and False Advertising

  • The California AG’s advisory and legal analysis indicate that AI companies have engaged in deceptive practices, including misleading users about AI capabilities, accuracy, and independence from human intervention.

  • False advertising laws (California Business & Professions Code § 17500) prohibit making misleading statements to induce transactions. If companies knowingly misrepresent AI capabilities, they could be held criminally liable for fraud.

  • The AG explicitly calls out the risk of deceptive AI-generated deepfakes, which could violate impersonation and fraud statutes.

  • AI companies, including Meta, have reportedly engaged in the deliberate removal of copyright management information (CMI) from digital content used for training models.

  • The Digital Millennium Copyright Act (DMCA) Section 1202 criminalizes intentional CMI removal to conceal copyright violations. If proven in court, such behavior could be grounds for criminal charges.

3. Unlawful Data Collection and Privacy Violations

  • AI developers have harvested vast amounts of user data without consent, including from private communications and sensitive online platforms.

  • Violations of the California Consumer Privacy Act (CCPA) and the California Invasion of Privacy Act (CIPA) could result in civil and criminal penalties, particularly if AI firms systematically eavesdrop on or store private user interactions.

4. AI-Driven Discrimination in Employment, Finance, and Housing

  • AI models used in hiring, credit assessments, and tenant screenings have been shown to disproportionately discriminate against certain racial, gender, and socioeconomic groups.

  • Under the Unruh Civil Rights Act and the Fair Employment and Housing Act (FEHA), such discriminatory practices could lead to significant legal consequences.

  • The AG’s advisory highlights that businesses knowingly deploying AI systems with biased decision-making mechanisms could be in violation of anti-discrimination laws, potentially amounting to civil rights violations.

5. AI-Generated Impersonation and Identity Fraud

  • AI-powered deepfake technology has been used to impersonate individuals for fraud, identity theft, and misinformation campaigns.

  • California Penal Code § 530 (identity theft) and § 528.5 (online impersonation) criminalize the unauthorized use of someone’s likeness or identity for fraudulent purposes.

  • The AG’s advisory notes that failure to disclose AI-generated media in certain contexts, such as elections or financial transactions, may be a prosecutable offense.

Additional Problematic AI Practices

Beyond the violations outlined by the California AG, additional concerns emerge from industry analysis:

  1. Exploiting Loopholes in AI Licensing Deals: AI companies have made strategic licensing deals with major publishers while excluding individual authors and creators, thus undermining fair compensation models.

  2. Monetization Without Compensation: AI firms are profiting from models trained on copyrighted works while offering no direct financial return to creators.

  3. Technical Evasion of Legal Oversight: Many AI firms have intentionally obscured training data sources and avoided transparency about dataset compositions to avoid scrutiny and liability.

  4. Reproduction of Private Information: AI-generated outputs have included private user data, medical records, and other sensitive information, which could expose AI companies to liability under the Confidentiality of Medical Information Act (CMIA) and HIPAA.

Preventative Measures AI Companies Should Have Taken

To avoid these legal and ethical pitfalls, AI companies should have proactively implemented the following measures:

  1. Transparent Data Use and Consent Protocols: AI developers should have ensured that all training data was lawfully obtained, with clear permissions from rights holders and explicit consent from individual contributors.

  2. Bias Audits and Fairness Standards: Rigorous independent audits should have been conducted to detect and mitigate bias in AI decision-making systems before deployment.

  3. Stronger Content Filtering and Ethical Safeguards: AI-generated content should be systematically screened to prevent plagiarism, personal data leaks, and misinformation.

  4. Comprehensive Attribution and Licensing Models: AI companies should have adopted licensing structures that ensure fair compensation for authors, artists, and content creators.

  5. Industry-Wide Ethical AI Frameworks: A standardized regulatory compliance framework should have been developed in collaboration with legal experts, policymakers, and consumer advocacy groups.

Remedies and the Path Forward

Given the growing legal scrutiny, AI companies must take immediate corrective actions:

  1. Full Disclosure of Training Data Sources: AI firms must transparently disclose datasets used in training and rectify cases where data was unlawfully obtained.

  2. Legal Compliance Overhaul: Companies must implement stringent data privacy compliance protocols and ensure AI outputs align with existing consumer protection laws.

  3. AI Model Adjustments and Retrofitting: Developers should modify AI systems to eliminate biased decision-making and prevent the unauthorized reproduction of copyrighted content.

  4. Restitution to Content Creators and Rights Holders: AI firms should establish compensation mechanisms for creators whose work has been used without permission.

  5. Stronger Collaboration with Regulators: AI developers must work closely with regulators to establish legally compliant frameworks for responsible AI development and deployment.

Conclusion

The legal landscape surrounding AI is evolving rapidly, and the California AG’s advisory signals that AI firms are operating on precarious legal ground. While some infractions may constitute civil liabilities, others—such as fraud, copyright misrepresentation, and privacy violations—have clear criminal implications. The AI industry must adopt proactive legal compliance strategies, enforce stricter ethical standards, and implement transparent regulatory measures to prevent further legal fallout and restore public trust in AI technology.

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19 JAN