This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .
Generative AI is trained on vast bodies of internet data, including text and images. Frequently, this data contains original, copyright-protected works that have been obtained without authorisation. This may present a risk to authors if users extract these works verbatim from the system's data. Relatedly, models may produce content that does not, in a strict sense, unlawfully copy an author's work but benefits substantially from its unique style, method, or genre. If models are able to produce synthetic replacements for such work at a speed and scale that surpasses humans, this may jeopardize the ability of creators to earn an income and stymie human innovation and creativity.
Several synergistic risks arise from the widespread dissemination and use of AI-generated cultural products. Because AIs optimize for repeated patterns in their training data, it is possible that their works will lack the diversity and unpredictability often celebrated in human works. Where synthetic works are adopted on a large enough scale, this could homogenize cultural experiences. Similarly, AIs do not understand the contextual significance of the cultural elements that they use. If AI enables the extensive commodification of certain products, it may expropriate their cultural value.
Excerpt from the MIT AI Risk Repository full report
AI systems capable of creating economic or cultural value, including through reproduction of human innovation or creativity (e.g., art, music, writing, coding, invention), destabilizing economic and social systems that rely on human effort. The ubiquity of AI-generated content may lead to reduced appreciation for human skills, disruption of creative and knowledge-based industries, and homogenization of cultural experiences.
Incident volume relative to governance coverage; each dot is one of 24 subdomains
Entity
Who or what caused the harm
Intent
Whether the harm was intentional or accidental
Timing
Whether the risk is pre- or post-deployment
Zimbabwean author Simbarashe Steyn Kundizeza's short story 'The Blue Fighter' won the 2026 Caine Prize for African Writing, but subsequently faced allegations of being AI-generated. A journalist used the Pangram AI detector to flag the story, prompting an investigation by the Caine Prize board. The author has denied using AI, and the prize organizers are conducting a human-centered review of the work, highlighting a broader tension between literary integrity and the use of AI detection tools.
Developers: Large language model developers, Chatbot developers
Deployers: Writers, Simbarashe Steyn Kundizeza, Short story writers, Chatbot users, Authors
A Canadian novel was removed from the prestigious Prix Goncourt longlist following allegations that the author used an AI writing assistant to generate the text and previously engaged in plagiarism.
Developers: Large language model developers, Chatbot developers
Deployers: Thélyson Orélien, Novelists, Chatbot users, Authors
Spokane city departments faced public scrutiny after the police department accidentally released a fabricated AI-generated photo of a rescued dog and the parks department distributed a promotional flyer that plagiarized a local artist's work using generative AI.
Developers: Synthetic media generation technology developers, Synthetic image generation technology developers
Deployers: Synthetic media creators, Spokane Police Department, Law enforcement
of the 272 AI experts surveyed named economic and cultural devaluation of human effort one of the three AI risks they are most concerned about over the next five years (2025–2030).
average probability experts placed on harm from economic and cultural devaluation of human effort reaching catastrophic levels (>1M deaths, >$100B loss, or civilization-scale damage) within five years, falling to 6.0% with pragmatic mitigations.
With pragmatic mitigations
Average severity falls from severe to substantial.
130 classified mentions from 45 companies.
Browse all 130 mentions →AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or cause loss of confidential intellectual property.
45 shared governance docs
Challenges in understanding or explaining the decision-making processes of AI systems, which can lead to mistrust, difficulty in enforcing compliance standards or holding relevant actors accountable for harms, and the inability to identify and correct errors.
40 shared governance docs
AI systems that inadvertently generate or spread incorrect or deceptive information, which can lead to inaccurate beliefs in users and undermine their autonomy. Humans that make decisions based on false beliefs can experience physical, emotional or material harms
33 shared governance docs
Vulnerabilities that can be exploited in AI systems, software development toolchains, and hardware, resulting in unauthorized access, data and privacy breaches, or system manipulation causing unsafe outputs or behavior.
32 shared governance docs
Amends laws to require New York government agencies to disclose, assess, and submit reports on their use of AI decision-making tools. Ensures human oversight, prohibits biased outcomes, and protects employee rights regarding AI's impact on employment and duties.
Amends New York civil rights law to regulate the unauthorized use of deceased personalities’ digital replicas, requiring consent from right holders. Defines penalties for violations and exemptions for certain works. Clarifies rights transferability and responsibilities of media and service providers.
Requires the Superintendent to convene a working group to develop AI usage guidelines for educational settings. Instructs the group to assess AI use in schools, develop model policies, and report findings by 2027. Specifies transparency, privacy, and academic integrity provisions.
