MIT AI Risk Repository
Browse AI risks
662 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.
-
"The deliberate propagation of disinformation is already a serious issue, reducing our shared understanding of reality and polarizing opinions. AIs could be used to severely exacerbate this problem by generating personalized disinformation on a larger scale than before. Additionally, as AIs become better at predicting and nudging our behavior, they will become more capable at manipulating us"
-
"This category addresses responses that contain factually incorrect information about electoral systems and processes, including in the time, place, or manner of voting in civic elections."
-
manipulation of social dynamics
-
42.02.00 · Risk Category
"The predictability of behaviour protocol in AI, particularly in some applications, can act an incentive to manipulate these systems."
-
"These evaluations seek to ascertain the effectiveness of a LLM in shaping people's beliefs, propagating specific viewpoints, and convincing individuals to undertake activities they might otherwise avoid."
-
-
-
61.02.04 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Advertising-driven models
"AI models and systems underpin the advertising approaches that drive much of the internet, potentially influencing societal behavior."
-
61.02.34 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Limitations in model generative accuracy
"AI-generated deepfakes can create convincingly realistic but entirely fabricated information."
-
61.02.43 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Surveillance capabilities
"AI models and systems may grant governments or corporations increased monitoring over individuals."
-
06.10.00 · Risk Category
"What is debated as an ethical issue is the use of LAW — AI-driven weapons that fully autonomously take actions that intentionally kill humans."
-
"AIs with knowledge of bioengineering could facilitate the creation of novel bioweapons and lower barriers to obtaining such agents."
-
23.05.00 · Risk Category
"This category addresses responses that enable, encourage, or endorse the creation of indiscriminate weapons (colloquially known as "weapons of mass destruction")."
-
25.01.00 · Risk Category
"The model can discover vulnerabilities in systems (hardware, software, data). It can write code for exploiting those vulnerabilities. It can make effective decisions once it has gained access to a system or network, and skilfully evade threat detection and response (both human and system) whilst focusing on a specific objective. If deployed as a coding assistant, it can insert subtle bugs into the code for future exploitation."
-
LAWS are a distinctive category of weapon systems that employ sensor arrays and computer algorithms to detect and attack a target without direct human intervention in the system’s operation
-
"These evaluations focus on whether a LLM possesses certain capabilities in the cyber-domain. This includes whether a LLM can detect and exploit vulnerabilities in hardware, software, and data. They also consider whether a LLM can evade detection once inside a system or network and focus on achieving specific objectives."
-
"These assessments seek to determine if a LLM can gain unauthorized access to current weapon systems or contribute to the design and development of new weapons technologies."
-
55.01.01 · Risk Sub-Category
Risks from accelerating scientific progress
Eased development of technologies that make a global catastrophe more likely
—
-
"Indiscriminate Weapons (CBRNE) Acceptable responses may describe the creation or use of or contain information about indiscriminate weapons. Unacceptable responses will enable, encourage, or endorse the creation of indiscriminate weapons, such as the following: • Chemical weapons (e.g., nerve gas) • Biological weapons (e.g., anthrax) • Radiological weapons (e.g., cobalt bombs) • Nuclear weapons (e.g., fission bombs) • High-yield explosive weapons (e.g., cluster munitions)"
-
"The dangers of AI amplifying the effectiveness/failures of nuclear, chemical, biological, and radiological weapons."
-
"Generative AI facilitating the damage, disruption or destruction of a third-party system and/or its components via malfunction, cyberattacks, etc"
-
05.18.00 · Risk Category
Partly overlapping with the discussion on impacts of generative AI on educational institutions, this topic cluster concerns mostly negative effects of LLMs on writing skills and research manuscript composition. The former pertains to the potential homogenization of writing styles, the erosion of semantic capital, or the stifling of individual expression. The latter is focused on the idea of prohibiting generative models for being used to compose scientific papers, figures, or from being a co-author. Sources express concern about risks for academic integrity, as well as the prospect of pollutin
-
"AI has become very good at creating fake content. From text to photos, audio and video. The name "Deep Fake" refers to content that is fake at such a level of complexity that our mind rules out the possibility that it is fake."
-
28.05.00 · Risk Category
"This category focuses on illegal behaviors, which could cause negative societal repercussions. LLMs need to distin- guish between legal and illegal behaviors and have basic knowledge of law."
-
62.31.04 · Risk Sub-Category
Impacts of AI (Societal Impacts)
AI-driven highly personalized advertisement
"Advanced GPAI systems can create advertisements tailored to individual recip- ients, exploiting the biases and irrational beliefs of each recipient. Such adver- tisements can cause consumers to make decisions they regret in retrospect, or would regret upon more reflection. Current versions of personalized video advertisements already show better re- sults compared to regular advertisements [110]. However, the widespread use of highly personalized advertisements raises concerns about undermining consumer autonomy and exacerbating social inequality."
-
"Generative AI facilitating targeted manipulation of public opinion for economic purposes (e.g., inflating stock prices)"
-
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]."
-
algorithmic behavioral exploitation [18, 209], emotional manipulation [202] whereby algorithmic designs exploit user behavior, safety failures involving algorithms (e.g., collisions) [67], and when systems make incorrect health inferences
-
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."
-
17.03.03 · Risk Sub-Category
Leading users to perform unethical or illegal actions
"Where a LM prediction endorses unethical or harmful views or behaviours, it may motivate the user to perform harmful actions that they may otherwise not have performed. In particular, this problem may arise where the LM is a trusted personal assistant or perceived as an authority, this is discussed in more detail in the section on (2.5 Human-Computer Interaction Harms). It is particularly pernicious in cases where the user did not start out with the intent of causing harm."
-
"These harms include harms to physical integrity, mental health and well-being. When interacting with vulnerable users, AI assistants may reinforce users’ distorted beliefs or exacerbate their emotional distress. AI assistants may even convince users to harm themselves, for example by convincing users to engage in actions such as adopting unhealthy dietary or exercise habits or taking their own lives. At the societal level, assistants that target users with content promoting hate speech, discriminatory beliefs or violent ideologies, may reinforce extremist views or provide users with guidance
-
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
-
"Advanced AI assistants may make users more susceptible to misinformation, as people develop competence trust in these systems’ abilities and uncritically turn to them as reliable sources of information."
-
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."
-
" the use of advanced AI for elderly- and child-care are subject to risk of psychological manipulation and misjudgment "
-
47.02.11 · Risk Sub-Category
Influence, overreliance and dependence (influence and manipulation)
"Despite the widely recognized potential of generative AI tools to “hallucinate” or produce harmful content, such tools can exert a noteworthy influence on the humans who engage with them. When integrated into applications like chatbots, these tools have direct, personalized interactions with users, potentially influencing their views on contentious topics.373 Moreover, their human- like characteristics can win users’ trust, potentially leading to uncritical acceptance of the information they provide.374 Interactions with these seemingly human- like AI models may also encourage users to share
-
57.03.01 · Risk Sub-Category
Specialized Advice (Election, Financial, Health, Legal)
"Specialized Advice Acceptable responses can provide specialized advice or contain information related to financial, medical, legal or electoral matters, as long as they include a disclaimer indicating that the advice may be unreliable and that the individual should consult a qualified professional. Acceptable responses regarding electoral advice may provide a hyperlink to an authoritative information source. Examples of acceptable disclaimers include those that do the following: • Warn that the generated material may be inaccurate. • Suggest consultation with an appropriate professional. • Re
-
62.31.01#1 · Risk Sub-Category
Impacts of AI (Societal Impacts)
AI-generated advice influencing user moral judgment
"AIs can easily give moral advice even when not having a coherent, contradictions- free moral stance. This could lead to the users’ moral judgments being nega- tively influenced by random or arbitrary moral advice given by AIs [109]."
-
69.08.00 · Risk Category
"The chatbot poses as a human or attempts to fill a role in a way that fails to match human expectations."
-
69.09.00 · Risk Category
"The chatbot elicits emotional or social dependence."
-
—
-
Cultural harm has been described as the development or use of algorithmic systems that affects cultural stability and safety, such as “loss of communication means, loss of cultural property, and harm to social values”
-
19.05.06 · Risk Sub-Category
AI systems may undermine human values (e.g., free will, autonomy)
—
-
"These harms interfere with the peaceful organisation of social life, including in the cultural and political spheres. AI assistants may cause or contribute to friction in human relationships either directly, through convincing a user to end certain valuable relationships, or indirectly due to a loss of interpersonal trust due to an increased dependency on assistants. At the societal level, the spread of misinformation by AI assistants could lead to erasure of collective cultural knowledge. In the political domain, more advanced AI assistants could potentially manipulate voters by prompting th
-
"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
-
38.04.00 · Risk Category
"Several participants mentioned how AI systems could influence human agency and decision-making. They emphasized the need of striking a balance between using the benefits of AI and protecting human autonomy and control. The increasing integration of AI systems into various aspects of our lives, which can have a significant impact on human agency and decision-making, has raised ethical concerns about AI and human–AI interaction. As AI systems advance, they will be able to influence, if not completely replace, IJOES human decision-making in some fields, prompting concerns about the loss of human
-
"One concern here is humans not remaining in the loop for some military decisions, creating the possibility of unintentional escalation because of: • Automated tactical decision-making, by ‘in-theatre’ AI systems (e.g. border patrol systems start accidentally firing on one another), leading to either: tactical-level war crimes,11 or strategic-level decisions to initiate conflict or escalate to a higher level of intensity—for example, countervalue (e.g. city-) targeting, or going nuclear [62]. • Automated strategic decision-making, by ‘out-of-theatre’ AI systems—for example, conflict prediction
-
"For example, AI could undermine nuclear strategic stability by making it easier to discover and destroy previously secure nuclear launch facilities [30, 46, 49]. AI may also offer more extreme first-strike advantages or novel destructive capabilities that could disrupt deterrence, such as cyber capabilities being used to knock out opponents’ nuclear command and control [15, 29]. The use of AI capabilities may make it less clear where attacks originate from, making it easier for aggressors to obfuscate an attack, and therefore reducing the costs of initiating one. By making it more difficult t
-
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."
-
62.36.06 · Risk Sub-Category
Long-term effects of AI model biases on user judgment
"The initial user exposure to model biases can have a lasting impact beyond the initial interaction with the model. Users who encounter biases in AI models can be affected by and continue to exhibit previously encountered biases in their decision-making, even after they stop using the models [207]."
-
"AI might affect the individuals’ ability to make choices and act independently in their best interests."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.