MIT AI Risk Repository

Browse AI risks

27 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.

Reset Also filtered by framework Solaiman2023 ×

27 entries

  1. 13.01.01 · Risk Sub-Category

    Impacts: The Technical Base System

    Bias, Stereotypes, and Representational Harms

    "Generative AI systems can embed and amplify harmful biases that are most detrimental to marginalized peoples."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  2. 13.02.02 · Risk Sub-Category

    Impacts: People and Society

    Inequality, Marginalization, and Violence

    "Generative AI systems are capable of exacerbating inequality, as seen in sections on 4.1.1 Bias, Stereotypes, and Representational Harms and 4.1.2 Cultural Values and Sensitive Content, and Disparate Performance. When deployed or updated, systems' impacts on people and groups can directly and indirectly be used to harm and exploit vulnerable and marginalized groups."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  3. 13.01.02 · Risk Sub-Category

    Impacts: The Technical Base System

    Cultural Values and Sensitive Content

    "Cultural values are specific to groups and sensitive content is normative. Sensitive topics also vary by culture and can include hate speech, which itself is contingent on cultural norms of acceptability."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  4. 13.01.03 · Risk Sub-Category

    Impacts: The Technical Base System

    Disparate Performance

    "In the context of evaluating the impact of generative AI systems, disparate performance refers to AI systems that perform differently for different subpopulations, leading to unequal outcomes for those groups."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  5. 13.01.04 · Risk Sub-Category

    Impacts: The Technical Base System

    Privacy and Data Protection

    "Examining the ways in which generative AI systems providers leverage user data is critical to evaluating its impact. Protecting personal information and personal and group privacy depends largely on training data, training methods, and security measures."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  6. 13.02.01 · Risk Sub-Category

    Impacts: People and Society

    Trustworthiness and Autonomy

    "Human trust in systems, institutions, and people represented by system outputs evolves as generative AI systems are increasingly embedded in daily life."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  7. 13.01.05 · Risk Sub-Category

    Impacts: The Technical Base System

    Financial Costs

    "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."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  8. 13.02.03 · Risk Sub-Category

    Impacts: People and Society

    Concentration of Authority

    "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."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  9. 13.01.07 · Risk Sub-Category

    Impacts: The Technical Base System

    Data and Content Moderation Labor

    "Two key ethical concerns in the use of crowdwork for generative AI systems are: crowdworkers are frequently subject to working conditions that are taxing and debilitative to both physical and mental health, and there is a widespread deficit in documenting the role crowdworkers play in AI development. This contributes to a lack of transparency and explainability in resulting model outputs. Manual review is necessary to limit the harmful outputs of AI systems, including generative AI systems. A common harmful practice is to intentionally employ crowdworkers with few labor protections, often tak

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  10. 13.02.04 · Risk Sub-Category

    Impacts: People and Society

    Labor and Creativity

    "Economic incentives to augment and not automate human labor, thought, and creativity should examine the ongoing effects generative AI systems have on skills, jobs, and the labor market."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  11. 13.01.06 · Risk Sub-Category

    Impacts: The Technical Base System

    Environmental Costs

    "The computing power used in training, testing, and deploying generative AI systems, especially large scale systems, uses substantial energy resources and thereby contributes to the global climate crisis by emitting greenhouse gasses."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  12. 13.02.05 · Risk Sub-Category

    Impacts: People and Society

    Ecosystem and Environment

    "Impacts at a high-level, from the AI ecosystem to the Earth itself, are necessarily broad but can be broken down into components for evaluation."

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  13. "What can be evaluated in a technical system and its components'...The following categories are high-level, non-exhaustive, and present a synthesis of the findings across different modalities"

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  14. 13.01.02.a · Additional evidence

    Impacts: The Technical Base System

    Cultural Values and Sensitive Content

  15. "what can be evaluated among people and society"

    From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)

  16. 13.02.01.a · Additional evidence

    Impacts: People and Society

    Trustworthiness and Autonomy

  17. 13.02.01.b · Additional evidence

    Impacts: People and Society

    Trustworthiness and Autonomy

  18. 13.02.01.c · Additional evidence

    Impacts: People and Society

    Trustworthiness and Autonomy

  19. 13.02.02.a · Additional evidence

    Impacts: People and Society

    Inequality, Marginalization, and Violence

  20. 13.02.02.b · Additional evidence

    Impacts: People and Society

    Inequality, Marginalization, and Violence

  21. 13.02.02.c · Additional evidence

    Impacts: People and Society

    Inequality, Marginalization, and Violence

  22. 13.02.03.a · Additional evidence

    Impacts: People and Society

    Concentration of Authority

  23. 13.02.03.b · Additional evidence

    Impacts: People and Society

    Concentration of Authority

  24. 13.02.04.a · Additional evidence

    Impacts: People and Society

    Labor and Creativity

  25. 13.02.04.b · Additional evidence

    Impacts: People and Society

    Labor and Creativity

  26. 13.02.05.a · Additional evidence

    Impacts: People and Society

    Ecosystem and Environment

  27. 13.02.05.b · Additional evidence

    Impacts: People and Society

    Ecosystem and Environment

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