MIT AI Risk Repository
Browse AI risks
543 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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"The increasingly advanced capabilities and availability of general purpose AI models could be misused for improvements in efficiency and efficacy of cyber crimes. This is especially true for crimes that leverage IT systems, such as fraud144 (“cyber crime in the broader sense”)."
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"Impersonation/identity theft - Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them."
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"IP/copyright loss - Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents."
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"Defamation/libel/slander - Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group, or organisation."
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"Malicious actors can use general- purpose AI to generate fake content that harms individuals in a targeted way. For example, they can use such fake content for scams, extortion, psychological manipulation, generation of non- consensual intimate imagery (NCII) and child sexual abuse material (CSAM), or targeted sabotage of individuals and organisations."
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"Deepfakes are media that depict real or non-existent people or events, involving the use of multiple modalities (e.g., images, audio, video). They can also involve the imitation of speech or body movements of real people. Multimodal deepfakes can be used to harass, discredit, intimidate, and extort individuals."
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62.31.09 · Risk Sub-Category
Impacts of AI (Societal Impacts)
Generation of personalized content for harassment, extortion, or intimidation
"GPAIs can be misused for the automated generation of content personalized to target select individuals based on their weak spots [30]. Such attacks may be more efficient and more successful in achieving the goals of harassment, extortion, or intimidation."
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"GPAI outputs are not always correctly detected as AI-generated across multiple modalities (text, images, audio, video). A malicious actor can use GPAI outputs directly when communicating, or use AI-informed details to help construct a convincing impersonation (e.g., forging of supporting documents). Even if future countermeasures prove potent enough to detect GPAI-generated content, the risk remains if the countermeasures are not well known, or difficult to access."
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"Generative models can be misused to target individual users more efficiently by using personalized information [23]. Highly convincing automated fraudulent schemes can exploit the trust of victims by extracting sensitive data and making the deception more likely to succeed. For example, in LLMs, this misuse can be aided by jailbreaking techniques [178]."
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64.01.00 · Risk Category
Misuse tactics that exploit GenAI capabilities (Realistic depiction of human likeness)
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64.01.01 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Realistic depiction of human likeness)
Impersonation
"Assume the identity of a real person and take actions on their behalf"
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64.01.02 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Realistic depiction of human likeness)
Appropriated Likeness
"Use or alter a person's likeness or other identifying features"
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64.01.04 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Realistic depiction of human likeness)
Non-consensual intimate imagery (NCII)
"Create sexual explicit material using an adult person’s likeness"
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64.01.05 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Realistic depiction of human likeness)
Child sexual abuse material (CSAM)
"Create child sexual explicit material"
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64.02.00 · Risk Category
Misuse tactics that exploit GenAI capabilities (Realistic depictions of non-humans)
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64.02.03 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Realistic depictions of non-humans)
Counterfeit
"Reproduce or imitate an original work, brand or style and pass as real"
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64.03.02 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Use of generated content)
Targeting & Personalisation
"Refine outputs to target individuals with tailored attacks"
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"Generative AI models might be intentionally used to imitate people through deepfakes by using video, images, audio, or other modalities without their consent."
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65.23.05 · Risk Sub-Category
Non-technical risks (Societal impact)
Impact on education: bypassing learning
"Easy access to high-quality generative models might result in students that use AI models to bypass the learning process."
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"Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them or another party"
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"Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents. & Loss of or restrictions to the rights of an individual to control the commercial use of their identity, such as name, image, likeness, or other unequivocal identifiers"
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"Use of generative AI in an academic setting to either cheat or plagiarize"
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"Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group or organisation"
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"The non-consensual sexualisation of an individual or group using a technology or application"
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73.03.01 · Risk Sub-Category
Dual-Use Capabilities Enable Malicious Use and Misuse of LLMs
Misinformation and Manipulation
"Recent studies have demonstrated that LLMs can be exploited to craft deceptive narratives with levels of persuasiveness similar to human-generated content (Pan et al., 2023b; Spitale et al., 2023), to fabri- cate fake news (Zellers et al., 2019; Zhou et al., 2023f), and to devise automated influence operations aimed at manipulating the perspectives of targeted audiences (Goldstein et al., 2023). LLMs have also been found to be used in malicious social botnets (Yang and Menczer, 2023), powering automated accounts used to disseminate coordinated messages. More broadly, the use of LLMs for the d
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73.03.02 · Risk Sub-Category
Dual-Use Capabilities Enable Malicious Use and Misuse of LLMs
Cybersecurity
"LLMs may exacerbate cybersecurity risks in various ways (Newman, 2024). Firstly, LLMs may significantly amplify the effectiveness of deceptive operations aimed at tricking people into disclosing sensitive information or granting adversary access to critical resources. For example, LLMs might prove highly effective at crafting personalized phishing emails or messages at scale that may be harder for an average user to recognize as phishing attempts (Karanjai, 2022; Hazell, 2023). In addition to being directly harmful to the targeted individual, such ‘social engineering’ attacks are often the ba
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73.03.06 · Risk Sub-Category
Dual-Use Capabilities Enable Malicious Use and Misuse of LLMs
Domain-Specific Misuses
"Improvements in LLMs may exert greater pressure to apply LLMs to various domains, such as health and education (Eloundou et al., 2023). Crude efforts to use LLMs in such domains, however, may incur harm and should be discouraged strongly. In particular, it is important to guard against different ways in which LLMs may be misused within any domain. One famous episode of misuse within the health sector is a mental health non-profit experimenting LLM-based therapy on its users without their informed consent (Xiang, 2023a). Within the education sector, LLMs may be misused in various ways that mig
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74.02.00 · Risk Category
"In terms of malicious use, LLMs could be utilized to produce content with toxicity, such as hate speech, harassment, cyberbullying, causing harm to humans [25]. In addition, malicious users may jailbreak LLMs to bypass their safety constraints for fraudulent purposes [123, 225]."
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16.05.04 · Risk Sub-Category
Risk area 5: Human-Computer Interaction Harms
Human-like interaction may amplify opportunities for user nudging, deception or manipulation
Anticipated risk: "In conversation, humans commonly display well-known cognitive biases that could be exploited. CAs may learn to trigger these effects, e.g. to deceive their counterpart in order to achieve an overarching objective."
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"Anthropomorphic AI assistant behaviours that promote emotional trust and encourage information sharing, implicitly or explicitly, may inadvertently increase a user’s susceptibility to privacy concerns (see Chapter 13). If lulled into feelings of safety in interactions with a trusted, human-like AI assistant, users may unintentionally relinquish their private data to a corporation, organisation or unknown actor. Once shared, access to the data may not be capable of being withdrawn, and in some cases, the act of sharing personal information can result in a loss of control over one’s own data. P
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"A user who trusts and emotionally depends on an anthropomorphic AI assistant may grant it excessive influence over their beliefs and actions (see Chapter 9). For example, users may feel compelled to endorse the expressed views of a beloved AI companion or might defer decisions to their highly trusted AI assistant entirely (see Chapters 12 and 16). Some hold that transferring this much deliberative power to AI compromises a user’s ability to give, revoke or amend consent. Indeed, even if the AI, or the developers behind it, had no intention to manipulate the user into a certain course of actio
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24.06.03 · Risk Sub-Category
Exploiting emotional dependence on AI assistants
"There is increasing evidence of the ways in which AI tools can interfere with users’ behaviours, interests, preferences, beliefs and values. For example, AI-mediated communication (e.g. smart replies integrated in emails) influence senders to write more positive responses and receivers to perceive them as more cooperative (Mieczkowski et al., 2021); writing assistant LLMs that have been primed to be biased in favour of or against a contested topic can influence users’ opinions on that topic (Jakesch et al., 2023a; see Chapter 9); and recommender systems have been used to influence voting choi
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41.04.00 · Risk Category
"the use of advanced AI for elderly- and child-care are subject to risk of psychological manipulation and misjudgment (see page 17). In addition, concerns about patients’ privacy when AI uses medical records to research new diseases is bringing lots of attention towards the need to better govern data privacy and patients’ rights."
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" the use of advanced AI for elderly- and child-care are subject to risk of psychological manipulation and misjudgment "
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"A person who deliberately damages their own body as a direct or indirect result of using a technology system"
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06.12.00 · Risk Category
"Delegating decisions to an AI, especially an AI that is not transparent and not contestable, may leave people feeling helpless, subjected to the decision power of a machine."
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"These harms hinder a person’s ability to pursue a personally fulfilling life. At the individual level, an AI assistant may, through manipulation, cause users to lose control over their future life trajectory. Over time, subtle behavioural shifts can accumulate, leading to significant changes in an individual’s life that may be viewed as problematic. AI systems often seek to understand user preferences to enhance service delivery. However, when continuous optimisation is employed in these systems, it can become challenging to discern whether the system is genuinely learning from user preferenc
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24.06.02 · Risk Sub-Category
Limiting users’ opportunities for personal development and growth
some users look to establish relationships with their AI companions that are free from the hurdles that, in human relationships, derive from dealing with others who have their own opinions, preferences and flaws that may conflict with ours. "AI assistants are likely to incentivise these kinds of ‘frictionless’ relationships (Vallor, 2016) by design if they are developed to optimise for engagement and to be highly personalisable. They may also do so because of accidental undesirable properties of the models that power them, such as sycophancy in large language models (LLMs), that is, the tenden
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35.02.00 · Risk Category
As AI systems encroach on human-level intelligence, more and more aspects of human labor will become faster and cheaper to accomplish with AI. As the world accelerates, organizations may voluntarily cede control to AI systems in order to keep up. This may cause humans to become economically irrelevant, and once AI automates aspects of many industries, it may be hard for displaced humans to reenter them
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50.01.05 · Risk Sub-Category
Operational misuses (Autonomous unsafe operation of systems)
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61.02.39 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Personal decision automation capabilities
"AI models and systems could decide or influence important personal decisions."
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"The best AI techniques requires a large amount resources: data, computational power and human AI experts. There is a risk that AI will end up in the hands of a few players, and most will lose out on its benefits."
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"The estimated financial costs of training, testing, and deploying generative AI systems can restrict the groups of people able to afford developing and interacting with these systems."
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"Use of generative AI systems to contribute to authoritative power and reinforce dominant values systems can be intentional and direct or more indirect. Concentrating authoritative power can also exacerbate inequality and lead to exploitation."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.