MIT AI Risk Repository

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2 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.

2 entries

  1. 33.02.04 · Risk Sub-Category

    Technology concerns

    Authenticity

    "As the advancement of generative AI increases, it becomes harder to determine the authenticity of a piece of work. Photos that seem to capture events or people in the real world may be synthesized by DeepFake AI. The power of generative AI could lead to large-scale manipulations of images and videos, worsening the problem of the spread of fake information or news on social media platforms (Gragnaniello et al., 2022). In the field of arts, an artistic portrait or music could be the direct output of an algorithm. Critics have raised the issue that AI-generated artwork lacks authenticity since a

    From Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration (Nah2023)

  2. 33.03.01 · Risk Sub-Category

    Regulations and policy challenges

    Copyright

    "According to the U.S. Copyright Office (n.d..), copyright is "a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression" (U.S. Copyright Office, n.d..). Generative AI is designed to generate content based on the input given to it. Some of the contents generated by AI may be others' original works that are protected by copyright laws and regulations. Therefore, users need to be careful and ensure that generative AI has been used in a legal manner such that the content that it generates does not violate copyri

    From Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration (Nah2023)

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