Josh Fairfield Publishes Articles on AI’s Impact on the Law In his recent work, Fairfield examines how artificial intelligence impacts consensus building and resists the detection of discrimination.

By Law Communications
June 11, 2026

Washington and Lee law professor Josh Fairfield has published two articles recently that examine AI’s impact on the law, including the ability to generate legal consensus and the degree to which AI has evolved to amplify discrimination and avoid detection.

In the article “The Last Human Question: Generative AI’s Existential Threat to Consensus and Law,” published in the West Virginia Law Review, Fairfield notes that the true threat of AI is not that the “toasters will rise up” against us but that AI will be indifferent to human welfare as it accomplishes human tasks.

“Further, a more precise and existential description of the threat is that generative AI will disrupt and crowd out humanity’s evolutionary superpower, our ability to generate agreement on how to live together—law,” writes Fairfield. “Generative AI disrupts our ability to generate consensus through the medium of meaning, culture, and language. As generative AI spams the channel, it drowns out human voices and human-constructed meaning. This Article describes how AI threatens our ability to create legal consensus, and proposes specific interventions to keep the question of how we live together—the last human question—one that permits human thriving.”

In the article “Generative Adversarial Discrimination,” published in the W&L Journal of Civil Rights and Social Justice, Fairfield notes that in the legal realm, anti-discrimination law can detect and rectify discrimination. However, the evolutionary logic of AI training causes it to target vulnerable groups, lie about reasoning, and above all resist detection. In the article, Fairfield explores a different legal toolset and set of mechanisms for detecting, preventing, and imposing consequences on entities that deploy discriminatory AI.

“Because of hidden core prompts in generative AI systems, and how those prompts interact with the nature of AI training and deployment, AI will often actively hide discrimination rather than surface and address it. Stopping this will be difficult. At present, neither humans or AI can detect this emergent dark-pattern behavior. Without legal intervention, the broad use of AI in hiring, to make policing decisions, immigration decisions, medical decisions, educational evaluations, mortgage loan terms, and many more similar decisions will continue to be optimized to target the intersectionally vulnerable and avoid being detected as discriminatory,” writes Fairfield.

These articles are available online in the W&L Scholarly Commons.

Josh Fairfield is an internationally recognized legal scholar and technology law expert serving as the Bain Professor of Law and AI Institute Director at Washington and Lee University School of Law. His work focuses on artificial intelligence, cognitive security, digital property, privacy, blockchain, cryptocurrencies, smart contracts, and emerging technology law, and he frequently serves as an expert witness in related litigation and arbitration.

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