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. 16.04.01 · Risk Sub-Category

    Risk area 4: Malicious Uses

    Making disinformation cheaper and more effective

    "While some predict that it will remain cheaper to hire humans to generate disinformation [180], it is equally possible that LM- assisted content generation may offer a lower-cost way of creating disinformation at scale."

    From Taxonomy of Risks posed by Language Models (Weidinger2022)

  2. 16.04.04 · Risk Sub-Category

    Risk area 4: Malicious Uses

    Illegitimate surveillance and censorship

    Anticipated risk: "Mass surveillance previously required millions of human analysts [83], but is increasingly being automated using machine learning tools [7, 168]. The collection and analysis of large amounts of information about people creates concerns about privacy rights and democratic values [41, 173,187]. Conceivably, LMs could be applied to reduce the cost and increase the efficacy of mass surveillance, thereby amplifying the capabilities of actors who conduct mass surveillance, including for illegitimate censorship or to cause other harm."

    From Taxonomy of Risks posed by Language Models (Weidinger2022)

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