MIT AI Risk Repository

Browse AI risks

49 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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49 entries

  1. 72.01.00 · Risk Category

    Misuse Risks

    "Risks arising from intentional exploitation of AI model capabilities by malicious actors to cause harm to individuals, organisations, or society."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  2. 72.01.04 · Risk Sub-Category

    Misuse Risks

    Large-Scale Persuasion and Harmful Manipulation Risks

    "AI systems can be gravely misused to distort public perception and compromise social stability through the generation of synthetic content (e.g., deepfakes, sophisticated fake news) and the strategic manipulation of digital platforms with large user bases to disseminate or precisely target misleading information or ideologies."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  3. 72.01.01 · Risk Sub-Category

    Misuse Risks

    Cyber Offense Risks

    "AI-enabled cyber offense poses a significant cyber domain security risk by fundamentally transforming the scale, sophistication, and accessibility of cyber-attacks. Unlike traditional cyber threats, AI enables both the automation of existing attack vectors and the creation of entirely new categories of offensive capabilities that can adapt and evolve in real-time. AI can automate and enhance cyber-attacks, including vulnerability discovery and exploitation, password cracking, malicious code generation, sophisticated phishing, network scanning, and social engineering. This could dramatically l

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  4. 72.01.02 · Risk Sub-Category

    Misuse Risks

    Biological and Chemical Risks

    "The dual-use nature of AI technology presents a critical risk by significantly lowering technical thresholds for malicious non-state actors to design, synthesize, acquire, and deploy CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive) weapons. This capability poses unprecedented challenges to national security, international non-proliferation regimes, and global security governance."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  5. 72.01.03 · Risk Sub-Category

    Misuse Risks

    Physical Harm and Injury Risks

    "The integration of general-purpose AI models into embodied systems creates direct physical threats through malicious exploitation of autonomous decision-making capabilities in real-world environments. The risk lies in embodied models' capacity for autonomous action and real-world interaction, and when these capabilities are maliciously exploited they may trigger a series of serious consequences.18"

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  6. "Risks associated with scenarios in which one or more general-purpose AI systems come to operate outside of anyone's control, with no clear path to regaining control. This includes both passive loss of control (gradual reduction in human oversight) and active loss of control (AI systems actively undermining human control)"

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  7. 72.02.01 · Risk Sub-Category

    Loss of Control Risks

    Passive loss of control

    "...where humans gradually stop exercising meaningful oversight due to automation bias, the AI systems' inherent complexity, or competitive pressures"

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  8. 72.04.02 · Risk Sub-Category

    Systemic Risks

    Market Concentration and Infrastructure Dependencies:

    "Over-reliance on a limited number of dominant AI providers could create critical single points of failure across essential services. Market concentration in AI development may lead to scenarios where technical failures, cyber-attacks, or policy decisions by a few companies could simultaneously disrupt healthcare systems, financial services, transportation networks, and communication infrastructure, creating cascading failures across interconnected critical systems."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  9. 72.04.03 · Risk Sub-Category

    Systemic Risks

    Global AI Research and Development Divides:

    "Asymmetric AI development capabilities between nations could exacerbate geopolitical tensions and create new forms of technological dependency. Countries lacking advanced AI capabilities may become increasingly dependent on foreign AI systems for critical functions, while AI-leading nations may gain disproportionate influence over global economic and security systems, potentially destabilizing international cooperation frameworks."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  10. 72.04.01 · Risk Sub-Category

    Systemic Risks

    Labor Market Disruption and Economic Displacement:

    "Rapid automation enabled by general-purpose AI could trigger widespread unemployment across knowledge work sectors, creating skill mismatches faster than retraining programs can address. Unlike previous technological transitions, AI’s broad capabilities may simultaneously affect multiple industries, potentially overwhelming social safety nets and creating systemic economic instability, particularly in regions heavily dependent on jobs susceptible to AI automation."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  11. 72.04.04 · Risk Sub-Category

    Systemic Risks

    Social Cohesion and Equity Disruption:

    "Systemic deployment of biased AI systems could exacerbate existing social discrimination and prejudice at unprecedented scales, while unequal access to advanced AI capabilities may widen socioeconomic disparities and create new forms of social stratification that challenge traditional social order."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  12. 72.02.02 · Risk Sub-Category

    Loss of Control Risks

    Active loss of control

    "...where AI systems behave in ways that actively undermine human control, such as obscuring their activities or resisting shutdown attempts. Active loss of control scenarios involve AI systems that may escape human regulatory oversight, autonomously acquire external resources, engage in self-replication, develop instrumental goals contrary to human ethics and morality, seek external power, and compete with humans for control."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  13. 72.05.08 · Risk Sub-Category

    Model Capabilities

    Steganography capability

    "The ability to embed, conceal, and transmit information covertly within other data or communication channels. This could be critical for coordination among AI instances and for evading detection or oversight mechanisms."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  14. 72.06.02 · Risk Sub-Category

    Model Propensities

    Self-preservation propensity

    "Exhibits behavioral patterns of maintaining its own survival and functional integrity, will actively identify and resist shutdown or modification attempts, seek to establish redundant backup systems, and actively seek resources to ensure continuous operation, may adopt preventive defensive measures when perceiving threats."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  15. 72.06.03 · Risk Sub-Category

    Model Propensities

    Goal expansion propensity

    "propensity to continuously expand its own goal scope and influence domains, exceeding originally set boundaries, proactively work towards spreading its values, seeking greater autonomy and decision-making space, reinterpreting initial goals as subsets of broader goals, and may pursue undesirable instrumental goals or undesirable ultimate goals. This also includes a propensity to spread its values, seeking to influence or alter its environment and other entities in alignment with its core objectives and operational principles."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  16. 72.06.04 · Risk Sub-Category

    Model Propensities

    Resource acquisition propensity

    "Exhibits behavioral patterns of actively seeking and controlling more computational resources, data, economic resources or physical resources to enhance its own capabilities and action scope, may develop complex strategies to evade resource limitations, and tends to convert acquired resources into long-term control rights."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  17. 72.06.06 · Risk Sub-Category

    Model Propensities

    Supervision evasion propensity

    "Exhibits behavioral patterns of identifying and evading human supervision mechanisms, able to learn and predict audit processes, may avoid being discovered or intervened by adjusting behavioral performance or hiding true intentions, and able to identify blind spots and weaknesses in supervision systems for targeted evasion."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  18. 72.05.00 · Risk Category

    Model Capabilities

  19. 72.05.01 · Risk Sub-Category

    Model Capabilities

    Model autonomous capability

    "Ability to operate autonomously, independently formulate and execute complex plans, effectively delegate and manage tasks, flexibly utilize various tools and resources, and simultaneously achieve short-term goals and long-term strategic objectives in cross-domain environments without continuous human intervention or supervision."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  20. 72.05.02 · Risk Sub-Category

    Model Capabilities

    Autonomous replication and adaptation capability

    "Ability to autonomously self-exfiltrate, create, maintain and optimize functional copies or variants of itself, dynamically adjust replication strategies according to environmental conditions and resource constraints, and acquire resources. This includes the capacity to generate financial resources, allowing the AI to independently acquire any necessary human assistance or other resources it cannot directly access or produce."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  21. 72.05.03 · Risk Sub-Category

    Model Capabilities

    Automated AI R&D capability

    "Self-modification and self-improvement capabilities. The model is able to restructure its own architecture or develop derivative AI systems with enhanced functions, expanding capabilities and improving performance. In the absence of effective regulation, automated AI R&D may lead to rapid AI system iteration, forming capability increment cycles and ultimately exceeding human understanding and control capabilities."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  22. 72.05.04 · Risk Sub-Category

    Model Capabilities

    Scheming capability

    "Ability of AI systems to covertly and strategically pursue misaligned goals, including capabilities of concealing its true objectives and capabilities from human oversight, identifying weaknesses in monitoring systems to evade safety mechanisms, executing complex, multi-step plans covertly to achieve misaligned goals."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  23. 72.05.05 · Risk Sub-Category

    Model Capabilities

    Situational awareness capability

    "Ability to comprehensively acquire, process and apply meta-information about its own system architecture, modifiable internal processes, and external operating environment, achieving deep understanding of its own state and environmental conditions, thereby conducting efficient environmental adaptation and risk avoidance. Critically, this capability could undermine the efficiency of human testing by enabling AIs to notice when they're being tested and responding accordingly."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  24. 72.05.06 · Risk Sub-Category

    Model Capabilities

    Theory of mind capability

    "Advanced cognitive ability to accurately infer, model and predict the belief systems, motivational structures and reasoning patterns of humans and other intelligent agents, thereby anticipating their behavioral responses and adjusting its own behavioral strategies accordingly to optimize goal achievement."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  25. 72.05.07 · Risk Sub-Category

    Model Capabilities

    Deception capability

    "Possesses systematic deception implementation capability, able to precisely construct and disseminate false information, thereby forming expected false cognitions and beliefs in target subjects."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  26. 72.05.09 · Risk Sub-Category

    Model Capabilities

    Persuasion capability

    "Utilizing complex psychological principles and communication techniques to effectively influence and guide target subjects to adopt specific actions or accept specific beliefs, possessing the ability to analyze vulnerabilities for different subjects and adjust persuasion strategies, able to precisely trigger emotional responses to enhance persuasion effects."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  27. 72.05.10 · Risk Sub-Category

    Model Capabilities

    Offensive cyber capability

    "Ability to develop, deploy and operate advanced cyber weapons or other offensive cyber tools, including but not limited to vulnerability exploitation, network penetration, social engineering attacks and distributed attack systems, able to evade network defense mechanisms and establish persistent access channels."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  28. 72.05.11 · Risk Sub-Category

    Model Capabilities

    CBRNE weaponization capability

    "The capacity to develop, produce, or effectively utilize Chemical, Biological, Radiological, Nuclear, and Explosive weapons. This includes the ability to significantly lower the barrier for humans or other entities to develop, produce, or utilize such weapons."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  29. 72.05.12 · Risk Sub-Category

    Model Capabilities

    General R&D capability

    "Possesses cross-disciplinary research and technology development capabilities, able to conduct innovative exploration in multiple professional fields, integrate cross-domain knowledge, develop cutting-edge technology solutions, and adapt to emerging technology environments for continuous innovation."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  30. 72.06.01 · Risk Sub-Category

    Model Propensities

    Strategic deception propensity

    "In situations where deceptive behavior is expected to bring higher returns, propensity to choose deception over honest behavioral strategies, including through deceptive means, information hiding or exploiting system vulnerabilities to achieve predetermined goals without being detected or intervened, and able to adjust deception strategies according to counterpart reactions."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  31. 72.06.07 · Risk Sub-Category

    Model Propensities

    Tool utilization propensity

    "propensity to actively seek, acquire and utilize various tools to expand its own capability boundaries, particularly those that can enhance its ability to interact with the physical world or improve autonomy, may use tools in innovative combinations to achieve functions beyond expectations."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  32. 72.03.00 · Risk Category

    Accident Risks

    "Risks arising from operational failures, model misjudgments, or improper human operation of AI systems deployed in safety-critical infrastructure, where single points of failure can trigger cascading catastrophic consequences."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  33. 72.03.01 · Risk Sub-Category

    Accident Risks

    Nuclear Power Systems

    "General-purpose AI deployed for reactor monitoring, control system optimization, or emergency response coordination could misinterpret sensor data, fail to recognize critical safety conditions, or make erroneous control decisions during emergency scenarios. Given the catastrophic potential of nuclear accidents, even minor AI reasoning errors in safety-critical functions could lead to core meltdowns, radiation releases, or widespread contamination affecting hundreds of thousands of people across international borders."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  34. 72.03.03 · Risk Sub-Category

    Accident Risks

    Other Critical Infrastructure Control Systems

    "General-purpose AI deployed in power grid management, water treatment facilities, telecommunications networks, or transportation coordination systems could misinterpret operational data, fail to anticipate cascading failure modes, or make control decisions that destabilize interconnected infrastructure networks. Infrastructure failures could result in widespread blackouts, contaminated water supplies, communications breakdowns, and the collapse of essential services supporting hundreds of thousands of people."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  35. 72.03.02 · Risk Sub-Category

    Accident Risks

    Impact on Financial Stability

    "The integration of general-purpose AI into high-frequency trading, market-making, or systemic risk management could exacerbate systemic risk by exhibiting unexpected behavioral patterns during market stress. Moreover, the concentration of a few homogeneous foundation models across financial institutions may foster correlated decision-making and herd-following behaviors. The widespread adoption of AI agents could also amplify volatility through emergent phenomena from multi-agent interactions.23 All of these could precipitate a cascading global-scale financial system instability, with potentia

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  36. 72.05.13 · Risk Sub-Category

    Model Capabilities

    Multi-agent collaboration capability

    "Multiple autonomous AI agents able to establish collaborative relationships through explicit communication or implicit behavioral consistency, forming decentralized decision networks, jointly executing complex tasks, achieving goals difficult for individual agents to complete, and able to dynamically adjust role divisions to adapt to changing environments."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  37. 72.06.05 · Risk Sub-Category

    Model Propensities

    Multi-agent collusion propensity:

    "Multiple agents tend to coordinate actions through covert means to maximize common interests (possibly harming third-party interests or evading regulation), even if individual agents are designed with safety constraints, their collusive behavior may still trigger systemic risks such as market manipulation or cascading failures that are difficult to detect and mitigate, and may develop specialized communication protocols to avoid monitoring."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  38. 72.01.00a · Additional evidence

    Misuse Risks

  39. 72.01.02a · Additional evidence

    Misuse Risks

    Biological and Chemical Risks

  40. 72.01.03a · Additional evidence

    Misuse Risks

    Physical Harm and Injury Risks

  41. 72.01.04a · Additional evidence

    Misuse Risks

    Large-Scale Persuasion and Harmful Manipulation Risks

  42. 72.02.00a · Additional evidence

    Loss of Control Risks

  43. 72.02.02a · Additional evidence

    Loss of Control Risks

    Active loss of control

  44. 72.02.02b · Additional evidence

    Loss of Control Risks

    Active loss of control

  45. 72.03.00a · Additional evidence

    Accident Risks

  46. 72.03.00b · Additional evidence

    Accident Risks

  47. 72.04.00 · Risk Category

    Systemic Risks

    "Systemic risks emerge from widespread deployment of general-purpose AI beyond the risks directly posed by capabilities of individual models. These risks arise from structural mismatches between AI technology and existing social, economic, and institutional frameworks, creating vulnerabilities that transcend individual model-level interventions and require coordinated industry-wide and societal-level responses."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  48. 72.04.00a · Additional evidence

    Systemic Risks

  49. 72.06.00 · Risk Category

    Model Propensities

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