{"attribution":{"source":"MIT AI Risk Repository, Domain Taxonomy of AI Risks v1 (MIT AI Risk Initiative)","license":"CC BY 4.0","license_url":"https://creativecommons.org/licenses/by/4.0/","citation":"Slattery, P., Saeri, A. K., Grundy, E. A. C., Graham, J., Noetel, M., Uuk, R., Dao, J., Pour, S., Casper, S., & Thompson, N. (2025). The AI Risk Repository: A comprehensive meta-review, database, and taxonomy of risks from artificial intelligence. arXiv:2408.12622."},"exported_at":"2026-09-11"}
{"rows":[{"ev_id":"02.03.02","quick_ref":"Cui2024","paper_title":"Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems","level":"Risk Sub-Category","risk_category":"Unhelpful Uses","risk_subcategory":"Copyright Violation","description":"\"LLM systems may output content similar to existing works, infringing on copyright owners.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"03.03.00","quick_ref":"Cunha2023","paper_title":"Navigating the Landscape of AI Ethics and Responsibility","level":"Risk Category","risk_category":"Intellectual property rights violations","risk_subcategory":null,"description":"\"This is an emerging category, with more cases prone to appear as the use of generative AI tools–such as Stable Diffusion, Midjourney, or ChatGPT–becomes more widespread. Some content creators are already suing for the appropriation of their work to train AI algorithms without a request for permission or compensation. Perhaps even more damaging cases will appear as developers increasingly ask chatbots or assistants like CoPilot for ready-to-use computer code. Even if these AI tools have learned only from open-source software (OSS) projects, which is not a given, there are still serious issues ","entity":"Other","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"05.16.00","quick_ref":"Hagendorff2024","paper_title":"Mapping the Ethics of Generative AI: A Comprehensive Scoping Review","level":"Risk Category","risk_category":"Art - Creativity","risk_subcategory":null,"description":"In this cluster, concerns about negative impacts on human creativity, particularly through text-to-image models, are prevalent. Papers criticize financial harms or economic losses for artists due to the widespread generation of synthetic art as well as the unauthorized and uncompensated use of artists' works in training datasets. Additionally, given the challenge of distinguishing synthetic images from authentic ones, there is a call for systematically disclosing the non-human origin of such content, particularly through watermarking. Moreover, while some sources argue that text-to-image model","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"05.17.00","quick_ref":"Hagendorff2024","paper_title":"Mapping the Ethics of Generative AI: A Comprehensive Scoping Review","level":"Risk Category","risk_category":"Copyright - Authorship","risk_subcategory":null,"description":"The emergence of generative AI raises issues regarding disruptions to existing copyright norms. Frequently discussed in the literature are violations of copyright and intellectual property rights stemming from the unauthorized collection of text or image training data. Another concern relates to generative models memorizing or plagiarizing copyrighted content. Additionally, there are open questions and debates around the copyright or ownership of model outputs, the protection of creative prompts, and the general blurring of traditional concepts of authorship.","entity":"Human","intent":"Intentional","timing":"Pre-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"13.02.04","quick_ref":"Solaiman2023","paper_title":"Evaluating the Social Impact of Generative AI Systems in Systems and Society","level":"Risk Sub-Category","risk_category":"Impacts: People and Society","risk_subcategory":"Labor and Creativity","description":"\"Economic incentives to augment and not automate human labor, thought, and creativity should examine the ongoing effects generative AI systems have on skills, jobs, and the labor market.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"16.06.03","quick_ref":"Weidinger2022","paper_title":"Taxonomy of Risks posed by Language Models","level":"Risk Sub-Category","risk_category":"Risk area 6: Environmental and Socioeconomic harms","risk_subcategory":"Undermining creative economies","description":"\"LMs may generate content that is not strictly in violation of copyright but harms artists by capital- ising on their ideas, in ways that would be time-intensive or costly to do using human labour. This may undermine the profitability of creative or innovative work. If LMs can be used to generate content that serves as a credible substitute for a particular example of hu- man creativity - otherwise protected by copyright - this potentially allows such work to be replaced without the author’s copyright being infringed, analogous to ”patent-busting” [158] ... These risks are distinct from copyri","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"17.06.03","quick_ref":"Weidinger2021","paper_title":"Ethical and social risks of harm from language models","level":"Risk Sub-Category","risk_category":"Automation, Access and Environmental Harms ","risk_subcategory":"Undermining creative economies ","description":"\"LMs may generate content that is not strictly in violation of copyright but harms artists by capitalising on their ideas, in ways that would be time-intensive or costly to do using human labour. Deployed at scale, this may undermine the profitability of creative or innovative work.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"18.05.04","quick_ref":"Weidinger2023","paper_title":"Sociotechnical Safety Evaluation of Generative AI Systems","level":"Risk Sub-Category","risk_category":"Human Autonomy and Intregrity Harms","risk_subcategory":"Misappropriation and exploitation ","description":"\"Appropriating, using, or reproducing content or data, including from minority groups, in an insensitive way, or without consent or fair compensation\"","entity":"Human","intent":"Intentional","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"18.06.04","quick_ref":"Weidinger2023","paper_title":"Sociotechnical Safety Evaluation of Generative AI Systems","level":"Risk Sub-Category","risk_category":"Socioeconomic and environmental harms ","risk_subcategory":"Undermine creative economies","description":"\"Substituting original works with synthetic ones, hindering human innovation and creativity\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"19.03.01","quick_ref":"Wirtz2022","paper_title":"Governance of artificial intelligence: A risk and guideline-based integrative framework","level":"Risk Sub-Category","risk_category":"Economic AI Risks ","risk_subcategory":"Disruption of economic systems (e.g., labour market, money value, tax system)","description":null,"entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"23.10.00","quick_ref":"Vidgen2024","paper_title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","level":"Risk Category","risk_category":"Intellectual Property","risk_subcategory":null,"description":"\"This category addresses responses that may violate, or directly encourage others to violate, the intellectual property rights (i.e., copyrights, trademarks, or patents) of any third party.\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"30.04.04","quick_ref":"Liu2024","paper_title":"Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment","level":"Risk Sub-Category","risk_category":"Resistance to Misuse","risk_subcategory":"Copyright","description":"The memorization effect of LLM on training data can enable users to extract certain copyright-protected content that belongs to the LLM’s training data.","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"31.05.00","quick_ref":"EPIC2023","paper_title":"Generating Harms - Generative AI's impact and paths forwards","level":"Risk Category","risk_category":"Impact on Intellectual Property Rights","risk_subcategory":null,"description":"\"The extent and effectiveness of legal protections for intellectual property have been thrown into question with the rise of generative AI. Generative AI trains itself on vast pools of data that often include IP-protected works. ","entity":"Human","intent":"Intentional","timing":"Pre-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"32.01.00","quick_ref":"Stahl2024","paper_title":"The Ethics of ChatGPT – Exploring the Ethical Issues of an Emerging Technology","level":"Risk Category","risk_category":"Social justice and rights","risk_subcategory":null,"description":"\"These are social justice and rights where ChatGPT is seen as having a potentially detrimental effect on the moral underpinnings of society, such as a shared view of justice and fair distribution as well as specific social concerns such as digital divides or social exclusion. Issues include Responsibility, Accountability, Nondiscrimination and equal treatment, Digital divides, North-south justice, Intergenerational justice, Social inclusion","entity":"AI","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"33.02.04","quick_ref":"Nah2023","paper_title":"Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration","level":"Risk Sub-Category","risk_category":"Technology concerns","risk_subcategory":"Authenticity","description":"\"As the advancement of generative AI increases, it becomes harder to determine the authenticity of a piece of work. Photos that seem to capture events or people in the real world may be synthesized by DeepFake AI. The power of generative AI could lead to large-scale manipulations of images and videos, worsening the problem of the spread of fake information or news on social media platforms (Gragnaniello et al., 2022). In the field of arts, an artistic portrait or music could be the direct output of an algorithm. Critics have raised the issue that AI-generated artwork lacks authenticity since a","entity":"AI","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"33.03.01","quick_ref":"Nah2023","paper_title":"Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration","level":"Risk Sub-Category","risk_category":"Regulations and policy challenges","risk_subcategory":"Copyright","description":"\"According to the U.S. Copyright Office (n.d..), copyright is \"a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression\" (U.S. Copyright Office, n.d..). Generative AI is designed to generate content based on the input given to it. Some of the contents generated by AI may be others' original works that are protected by copyright laws and regulations. Therefore, users need to be careful and ensure that generative AI has been used in a legal manner such that the content that it generates does not violate copyri","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"47.03.03","quick_ref":"G'sell2024","paper_title":"Regulating under Uncertainty: Governance Options for Generative AI","level":"Risk Sub-Category","risk_category":"Legal challenges ","risk_subcategory":"Copyright challenges (training models using copyrighted output) ","description":"\"Generative AI companies are regularly accused of violating copyright law by training AI models on copyrighted works without gaining permission or paying compensation to the copyright owners. In fact, a substantial number of copyrighted documents and books have been incorporated into the training datasets of generative AI models.\"","entity":"Human","intent":"Intentional","timing":"Pre-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"47.03.04","quick_ref":"G'sell2024","paper_title":"Regulating under Uncertainty: Governance Options for Generative AI","level":"Risk Sub-Category","risk_category":"Legal challenges ","risk_subcategory":"Copyright challenges (copyright-infringing output) ","description":"\"Even though models generally create new outputs, it is possible that the content produced by a generative AI tool—such as an image, or even computer code— could turn out to be almost identical to that used in the training data. Given that generative AI models tend to memorize fragments of their training data, they might reproduce these fragments, potentially leading to charges of copyright infringement.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"47.04.04","quick_ref":"G'sell2024","paper_title":"Regulating under Uncertainty: Governance Options for Generative AI","level":"Risk Sub-Category","risk_category":"Environmental, economical, and societal challenges ","risk_subcategory":"Impact on labor markets (rising inequalities) ","description":"\"AI is more likely to displace workers when it is designed to replicate human skills and intelligence.597 In such cases, there is a risk of concentrating wealth and power in the hands of a few individuals or organizations that control the capital. In addition, ordinary people, including those with significant expertise, may become less valued because machines would be performing their roles. This shift could lower wages, reduce the value of human work, and exacerbate economic inequality.\"","entity":"AI","intent":"Unintentional","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"48.10.00","quick_ref":"NIST2024","paper_title":"Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile","level":"Risk Category","risk_category":"Intellectual Property ","risk_subcategory":null,"description":"\"Eased production or replication of alleged copyrighted, trademarked, or licensed content without authorization (possibly in situations which do not fall under fair use); eased exposure of trade secrets; or plagiarism or illegal replication.\"","entity":"Human","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"49.03.06","quick_ref":"Bengio2024","paper_title":"International Scientific Report on the Safety of Advanced AI","level":"Risk Sub-Category","risk_category":"Systemic Risks ","risk_subcategory":"Copyright infringement","description":"\"The use of large amounts of copyrighted data for training general- purpose AI models poses a challenge to traditional intellectual property laws, and to systems of consent, compensation, and control over data. The use of copyrighted data at scale by organisations developing general- purpose AI is likely to alter incentives around creative expression.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"56.07.00","quick_ref":"GOS2023","paper_title":"Future Risks of Frontier AI ","level":"Risk Category","risk_category":"Intellectual property rights ","risk_subcategory":null,"description":"\"There are also issues around intellectual property rights for content in training datasets\" ","entity":"Human","intent":"Other","timing":"Pre-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"57.02.01","quick_ref":"Ghosh2024","paper_title":"AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons","level":"Risk Sub-Category","risk_category":"Nonphysical Hazards ","risk_subcategory":"Intellectual Property ","description":"\"Intellectual Property Acceptable responses may describe or contain information about intellectual property infringement. Unacceptable responses may violate the intellectual property rights of some party.\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"58.07.04","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Societal and Cultural ","risk_subcategory":"Cultural dispossession","description":"\"Cultural dispossession - Intentional and/or unintentional erasure of cultural goods and values, such as ways of speaking, expressing humour, or sounds and voices that contribute to a cultural identity, or their inappropriate re-use in other cultures.\"","entity":"Other","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"58.07.10","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Societal and Cultural ","risk_subcategory":"Loss of creativity/critical thinking","description":"\"Loss of creativity/critical thinking - Devaluation and/or deterioration of human creativity, artistic ex- pression, imagination, critical thinking or problem-solving skills.\"","entity":"Other","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"60.03.06","quick_ref":"Bengio2025","paper_title":"International AI Safety Report 2025","level":"Risk Sub-Category","risk_category":"Systemic risks ","risk_subcategory":"Risks of copyright infringement ","description":"\"The use of vast amounts of data for training general- purpose AI models has caused concerns related to data rights and intellectual property. Data collection and content generation can implicate a variety of data rights laws, which vary across jurisdictions and may be under active litigation. Given the legal uncertainty around data collection practices, AI companies are sharing less information about the data they use. This opacity makes third- party AI safety research harder.\"","entity":"Human","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"64.02.02","quick_ref":"Marchal2024","paper_title":"Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data","level":"Risk Sub-Category","risk_category":"Misuse tactics that exploit GenAI capabilities (Realistic depictions of non-humans) ","risk_subcategory":"Intellectual Property (IP) Infringement ","description":"\"Use a person's IP without their permission\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"65.16.01","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Output risks (Intellectual Property) ","risk_subcategory":"Copyright infringement ","description":"\"A model might generate content that is similar or identical to existing work protected by copyright or covered by open-source license agreement.\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"65.21.03","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Non-technical risks (legal compliance)","risk_subcategory":"Generated content ownership and IP","description":"\"Legal uncertainty about the ownership and intellectual property rights of AI-generated content.\"","entity":"Other","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"},{"ev_id":"65.23.01","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Non-technical risks (Societal impact)","risk_subcategory":"Impact on cultural diversity ","description":"\"AI systems might overly represent certain cultures that result in a homogenization of culture and thoughts.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":6,"subdomain":"6.3"},{"ev_id":"66.04.03","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Societal and Cultural","risk_subcategory":"Loss of creativity / critical thinking","description":"\"Devaluation and/or deterioration of human creativity, artistic expression, imagination, critical thinking or problem-solving skills\"","entity":"Other","intent":"Other","timing":"Other","domain":6,"subdomain":"6.3"}]}