MIT AI Risk Repository
Browse AI risks
80 risk entries extracted from 74 frameworks, coded by domain, subdomain, causal entity, intent and timing. Filter, then export the current selection with its licence and citation attached.
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69.01.00 · Risk Category
"The chatbot outputs information that contradicts known facts, authoritative sources, or provided source documents (also known as hallucination)."
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"Non-embodied AIs are known to propagate misinformation [81, 82]. Various studies have shown that LLMs hallucinate information, including academic citations [83], clinical knowledge [84], and cultural references [85]. EAI systems inherit these shortcomings in the physical world, answering user questions with deceptive or incorrect information [86]. Because VLAs fuse vision and language, their hallucinatory failures can be spatially grounded—e.g., misidentifying an object in view and then generating a plausible yet unsafe action plan around it. And although automated home assistants like Amazon
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"Despite the rapid advancement of LLMs, hallucinations have emerged as one of the most vital concerns surrounding their use [54, 79, 86, 110, 242]. Hallucinations are often referred to as LLMs’ generating content that is nonfactual or unfaithful to the provided information [54, 79, 86, 242]. Therefore, hallucinations can be typically categorized into two main classes. The first is factuality hallucination, which describes the discrepancy between LLMs’ generated content and real-world facts. For example, if LLMs mistakenly take Charles Lindbergh as the first person who walked on the moon, it is
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06.05.00 · Risk Category
"With online news feeds, both on websites and social media platforms, the news is now highly personalized for us. We risk losing a shared sense of reality, a basic solidarity."
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"Contaminating publicly available information with false or inaccurate information"
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24.11.01 · Risk Sub-Category
Entrenched viewpoints and reduced political efficacy
"Design choices such as greater personalisation of AI assistants and efforts to align them with human preferences could also reinforce people’s pre-existing biases and entrench specific ideologies. Increasingly agentic AI assistants trained using techniques such as reinforcement learning from human feedback (RLHF) and with the ability to access and analyse users’ behavioural data, for example, may learn to tailor their responses to users’ preferences and feedback. In doing so, these systems could end up producing partial or ideologically biased statements in an attempt to conform to user expec
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"Beyond this, the widespread adoption of advanced AI assistants for content generation could have a number of negative consequences for our shared information ecosystem. One concern is that it could result in a degradation of the quality of the information available online. Researchers have already observed an uptick in the amount of audiovisual misinformation, elaborate scams and fake websites created using generative AI tools (Hanley and Durumeric, 2023). As more and more people turn to AI assistants to autonomously create and disseminate information to public audiences at scale, it may beco
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"AI assistants may provide ideologically biased or otherwise partial information in attempting to align to user expectations. In doing so, AI assistants may reinforce people’s pre-existing biases and compromise productive political debate."
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"AI assistants may contribute to the spread of large quantities of factually inaccurate and misleading content, with negative consequences for societal trust in information sources and institutions, as individuals increasingly struggle to discern truth from falsehood."
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31.01.05 · Risk Sub-Category
Clickbait and feeding the surveillance advertising ecosystem
"Beyond misinformation and disinformation, generative AI can be used to create clickbait headlines and articles, which manipulate how users navigate the internet and applications. For example, generative AI is being used to create full articles, regardless of their veracity, grammar, or lack of common sense, to drive search engine optimization and create more webpages that users will click on. These mechanisms attempt to maximize clicks and engagement at the truth’s expense, degrading users’ experiences in the process. Generative AI continues to feed this harmful cycle by spreading misinformat
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35.03.00 · Risk Category
Strong AI may... enable personally customized disinformation campaigns at scale... AI itself could generate highly persuasive arguments that invoke primal human responses and inflame crowds... d undermine collective decision-making, radicalize individuals, derail moral progress, or erode consensus reality
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45.02.09 · Risk Sub-Category
Safety risks in AI Applications
Cognitive risks (Risks of amplifying the effects of "information cocoons")
"AI can be extensively utilized for customized information services, collecting user information, and analyzing types of users, their needs, intentions, preferences, habits, and even mainstream public awareness over a certain period. It can then be used to offer formulaic and tailored information and services, aggravating the effects of "information cocoons.""
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53.04.03 · Risk Sub-Category
Indirect AI contributions to existential risks
Impacts on “epistemic security” and the information environment
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55.04.00 · Risk Category
"Epistemic processes and problem solving: we currently see more reasons to be concerned about AI worsening society's epistemic processes than reasons to be optimistic about AI helping us better solve problems as a society. For example, increased use of content selection algorithms could drive epistemic insularity and a decline in trust in credible multipartisan sources, which reducing our ability to deal with important long-term threats and challenges such as pandemics and climate change."
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55.04.01 · Risk Sub-Category
Worsened epistemic processes for society
AI contributes to increased online polarisation
"One of the most significant commercial uses of current AI systems is in the content recommendation algorithms of social media companies, and there are already concerns that this is contributing to worsened polarisation online"
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55.04.04 · Risk Sub-Category
Worsened epistemic processes for society
Widespread use of persuasive tools contributes to splintered epistemic communities
"Even without deliberate misuse, widespread use of powerful persuasion tools could have negative impacts. If such tools were used by many different groups to advance many different ideas, we could see the world splintering into isolated “epistemic communities”, with little room for dialogue or transfer between communities. A similar scenario could emerge via the increasing personalisation of people’s online experiences—in other words, we may see a continuation of the trend towards “filter bubbles” and “echo chambers”, driven by content selection algorithms, that some argue is already happening
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55.04.05 · Risk Sub-Category
Worsened epistemic processes for society
Reduced decision-making capacity as a result of decreased trust in information
"In addition, the increased awareness of these trends in information production and distribution could make it harder for anyone to evaluate the trustworthiness of any information source, reducing overall trust in information. In all of these scenarios, it would be much harder for humanity to make good decisions on important issues, particularly due to declining trust in credible multipartisan sources, which could hamper attempts at cooperation and collective action. The vaccine and mask hesitancy that exacerbated Covid-19, for example, were likely the result of insufficient trust in public he
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"Radicalisation - Adoption of extreme political, social, or religious ideals and aspirations due to the nature or misuse of an algorithmic system, potentially resulting in abuse, violence, or terrorism."
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"Information degradation - Creation or spread of false, hallucinatory, low-quality, misleading, or inaccurate information that degrades the information ecosystem and causes people to develop false or inaccurate perceptions, decisions and beliefs; or to lose trust in accurate information."
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"Institutional trust loss - Erosion of trust in public institutions and weakened checks and balances due to mis/disinformation, influence operations, over-dependence on technology, etc."
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61.02.20 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Detection challenges in content
"The difficulty in distinguishing synthetic content from authentic material adds to information risks."
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"Contaminating publicly available information with false or inaccurate information (i.e., the generative tool's output is disseminated beyond the end user)"
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"Eroding trust in public information and knowledge"
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"Pollution of a space/ecosystem that is expected to be free of AI involvement/influence (e.g., creative material submission portals, job applications)"
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"Frontier AI can cheaply generate realistic content which can falsely portray people and events. There is potential risk of compromised decision-making by individuals and institutions who rely on inaccurate or misleading publicly available information, as well as lower overall trust in true information."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.