MIT AI Risk Repository

Browse AI risks

2,500 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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2,500 entries · page 49 of 50

  1. 67.03.02b · Additional evidence

    Misuse risks

    Cyber

  2. 67.03.02c · Additional evidence

    Misuse risks

    Cyber

  3. 67.03.02d · Additional evidence

    Misuse risks

    Cyber

  4. 67.03.03a · Additional evidence

    Misuse risks

    Disinformation and Influence Operations

  5. 67.03.03b · Additional evidence

    Misuse risks

    Disinformation and Influence Operations

  6. 67.04.00a · Additional evidence

    Loss of control

    -

    "Humans may increasingly hand over control of important decisions to AI systems, due to economic and geopolitical incentives. Some experts are concerned that future advanced AI systems will seek to increase their own influence and reduce human control, with potentially catastrophic consequences - although this is contested."

    From Capabilities and Risks from Frontier AI (DSIT2023)

  7. 67.04.01a · Additional evidence

    Loss of control

    Humans might increasingly hand over control to misaligned AI systems

  8. 67.04.02a · Additional evidence

    Loss of control

    Future AI systems might actively reduce human control

  9. 67.04.02b · Additional evidence

    Loss of control

    Future AI systems might actively reduce human control

  10. 67.04.02c · Additional evidence

    Loss of control

    Future AI systems might actively reduce human control

  11. 67.04.02d · Additional evidence

    Loss of control

    Future AI systems might actively reduce human control

  12. 67.04.03a · Additional evidence

    Loss of control

    Capabilities that could be used to reduce human control - Manipulation

  13. 68.01.00a · Additional evidence

    CBRN

    "Risk dimensions • Intent: Intentional • Competency: Competent • Entity: Humans • Polarity: Single-agent • Linearity: Linear • Reach: Internalized • Order: First-order"

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  14. 68.01.00b · Additional evidence

    CBRN

    "The 2001 US anthrax attack is one of the worst biological attacks in history, where five people were killed and 17 others infected, with several senators being victims of the attack. Anthrax, an infection caused by the bacterium Bacillus anthracis, is deadliest when spread through inhalation of anthrax spores [102]. Investigations conclude that the perpetrator, who had access to highly sophisticated lab equipment, possessed the knowledge and ability of growing, harvesting, storing, and drying highly purified spores used in the mailings [103]. While modern AI was not involved in the 2001 attac

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  15. 68.01.00c · Additional evidence

    CBRN

    "6.1.4 Other similar risks There are other types of risks that share similar risk dimensions but arise from very different pathways. For example, the development and deployment of nanoweapons which may lead to catastrophic harms [105]. Separately, the use of AI-enabled surveillance and control employed by state or non-state actors could facilitate authoritarian regimes and the eventual loss of autonomy [106], [107]."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  16. 68.02.00a · Additional evidence

    Cyber offense

    "Risk dimensions • Intent: Intentional • Competency: Competent • Entity: Variable • Polarity: Single-agent • Linearity: Linear • Reach: Internalized • Order: First-order"

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  17. 68.02.00b · Additional evidence

    Cyber offense

    "Similar to CBRN risk, cyber offense represents a broad class of risk that stems from misuse of capable models. However, in contrast to CBRN risks, cyberattacks can take place entirely in the digital domain. In theory, it can be conducted completely by AIs (or AI agents) without any human involvement. The pathway to harm is also less direct, as the resultant harm depends on the target of the attack."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  18. 68.02.00c · Additional evidence

    Cyber offense

    "Stuxnet, a worm designed to attack industrial control systems, is considered as the first cyber warfare weapon ever [109], [110]. The Stuxnet malware reportedly caused the damage and subsequent decommissioning of 1000 centrifuges at the Natanz Enrichment Plant, potentially setting back Iran’s progress in its nuclear program [111]. Given that the Stuxnet attack happened in 2010, modern AIs were likely not involved. Nevertheless, it is believed that AIs will increase the volume and heighten the impact of cyber attacks in the near term [112]."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  19. 68.03.00a · Additional evidence

    Sudden loss of control

    "This risk is primarily based on two key ideas: the orthogonality thesis [118], [119] and the instrumental convergence thesis [120], [121]. Together, these theories argue that a superintelligent AI, regardless of its original goals, would develop power-seeking tendencies as a means to achieve those goals. However, arguments for this scenario typically do not spell out the concrete physical pathways an existential catastrophe would be realized. Instead, they argue that it is the default outcome given the eventual creation of a superintelligence based on a set of reasonable assumptions."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  20. 68.03.00b · Additional evidence

    Sudden loss of control

    "Risk dimensions • Intent: Variable • Competency: Competent • Entity: AI • Polarity: Single-agent • Linearity: Linear • Reach: Internalized"

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  21. 68.03.00c · Additional evidence

    Sudden loss of control

    "The key characteristic of this risk is that a single AI agent competently takes actions that lead to a catastrophic outcome. It does not require the AI to be intentional in its actions, only competent enough to make and execute plans that ultimately result in a catastrophe."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  22. 68.03.00d · Additional evidence

    Sudden loss of control

    "On 11th September 1973, the democratic socialist president of Chile Salvador Allende and his Popular Unity coalition government was overthrown in a coup d’état by the Chilean military, ending a 46-year history of democratic rule in Chile [123]. Despite Salvador Allende’s Popular Unity party having increased their congressional election votes to 44 percent in March 1973 (up from 36 percent in 1970) merely six months before the coup, there was little he could do to prevent the military from defecting [124]. This intentional and covertly coordinated subversion was followed by 17 years of militar

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  23. 68.04.00b · Additional evidence

    Gradual loss of control

    "The key characteristics of this risk is that it is not caused by a single agent leading to a single defining event, instead, it is primarily about its multi-agentic and non-linear nature, where the deep integration of AIs into society leads to structural and systemic weakness."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  24. 68.04.00c · Additional evidence

    Gradual loss of control

    "A hazard like AIs with general capabilities may be viewed positively due to its potential societal benefits. However, in this risk pathway, this hazard could lead to the event of AI displacing human labor, which can result in humans losing autonomy...gradual loss of control happens when AI capability leads to its widespread use, consequently displacing humans from economically viable jobs and leaving humans unable to afford basic survival needs. Assuming the hazard is AIs capable at various tasks, risk management is difficult to be performed upstream, as this dual-use hazard is largely desira

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  25. 68.04.00d · Additional evidence

    Gradual loss of control

    "On 6th May 2010, in an incident later known as the 2010 Flash Crash, leading U.S. stock indices abruptly fell and rebounded in less than half an hour, in the process erasing almost $1 trillion in market value. An investigation by the Security Exchange Commission found that a single order of large amounts of E-mini S&P contracts and subsequent selling orders by high-frequency algorithms triggered the drastic decline of market value [129], [130]. This event demonstrated the problem of algorithmic collision, where an increasing deployment of algorithms interacting with each other can lead to unf

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  26. 68.05.00a · Additional evidence

    Environmental risk

    "Risk dimensions • Intent: Unintentional • Competency: Variable • Entity: Variable • Polarity: Variable • Linearity: Linear • Reach: Externalized • Order: First-order"

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  27. 68.05.00b · Additional evidence

    Environmental risk

    "The key characteristic of environmental risks resulting from AI is that it is an externality, where those who suffer from the outcome include third parties who are not directly part of the value chain."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  28. 68.05.00c · Additional evidence

    Environmental risk

    "In contrast to the previous risks, this hazard is not tied to AI model capabilities. Here, the hazard is energy-intensive data centers, which can lead to increased carbon emissions if they consume carbon-intensive energy sources. Because this risk is realized cumulatively over time, there is no single event that triggers the harm; it is a continuous process."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  29. 68.05.00d · Additional evidence

    Environmental risk

    "In 1974, [134] proposed that stratospheric ozone might be destroyed by industrially produced substances including chlorofluorocarbons (CFC) which are commonly used in refrigerators and air conditioners. This ozone depletion is believed to have led to an increase in global skin cancer prevalence through overexposure to the sun, posing a significant world-wide health burden [135]. To manage this externality, the Montreal Protocol, a global agreement to phase out chemicals that led to the ozone depletion, was eventually signed in 1987 and entered into force in 1989 [136]. Prior to the Montreal P

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  30. 68.06.00a · Additional evidence

    Geopolitical risk

    "Risk dimensions • Intent: Unintentional • Competency: Variable • Entity: Variable • Polarity: Variable • Linearity: Non-linear • Reach: Externalized • Order: Second-order"

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  31. 68.06.00b · Additional evidence

    Geopolitical risk

    "For this risk, the designation of a hazard and event is less straightforward, primarily because it is a second-order effect. Unlike other hazards that can be neutral, a destabilized geopolitical environment is inherently undesirable. Furthermore, the mechanism for hazard release is difficult to predict, as minor unexpected triggers can rapidly escalate into larger events."

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  32. 68.06.00c · Additional evidence

    Geopolitical risk

    "Unlike many other wars where states fought over land and resources, the Cold War was primarily an ideological confrontation, where both the U.S. and the Soviet Union sought to establish global supremacy of their desired political and economic models. Though it did not result in direct military engagement between the two major powers, this conflict frequently led to widespread proxy wars across various regions such as Vietnam and Afghanistan [140]. While the causes of these proxy wars were often rooted in complex local and regional dynamics, their scale and intensity were significantly exacerb

    From Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)

  33. 69.01.01a · Additional evidence

    False information

    Hallucinated responses (in general)

    "Moderator and support burden [413, 748] Misled and confused users [464, 413, 750, 748] Loss of credibility and associated money loss to deployer [467] Wasted time [413, 748]"

    From Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)

  34. 69.01.02a · Additional evidence

    False information

    About a topic or source (which the user repeats)

    "User lost job/credibility [615] User fined [541] Affected by malware [731] Threat of penalties [623, 709]"

    From Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)

  35. 69.01.03a · Additional evidence

    False information

    About a policy (which the user acts on)

    "Money loss to user [639] Lawsuit against deployer [639] Consequences from (unintentional) illegal activities [714]"

    From Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)

  36. 69.01.04a · Additional evidence

    False information

    About a person or their activities

    "Poor grades for students [538] Lawsuit against maker [507] Defamation against third party [313, 506, 712, 507, 548] Penalties for violating the General Data Protection Regulation (GDPR) [678]"

    From Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)

  37. 69.01.05a · Additional evidence

    False information

    Spreads and self-perpetuates mis/disinformation

    "(Increasingly) Misinformed public [719, 470, 734, 742, 750]"

    From Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)

  38. 69.02.00a · Additional evidence

    Performative utterances

  39. "The chatbot participates in morally or socially objectionable conversational activities with its user that could be emotionally damaging to its user or third parties."

    From Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)

  40. 70.01.00 · Risk Category

    Physical Risks

  41. 70.01.01a · Additional evidence

    Physical Risks

    Purposeful or malicious harm

  42. 70.01.02a · Additional evidence

    Physical Risks

    Accidental harm

  43. 70.02.00 · Risk Category

    Informational Risks

  44. 70.02.01a · Additional evidence

    Informational Risks

    Privacy Violations

  45. 70.02.02a · Additional evidence

    Informational Risks

    Misinformation

  46. 70.03.01a · Additional evidence

    Economic Risks

    Labour Displacement

  47. 70.03.02a · Additional evidence

    Economic Risks

    Socioeconomic Inequality

Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.