Browse AI risks

4 entries

1. 17.02.00 · Risk Category

   Information Hazards

   "Harms that arise from the language model leaking or inferring true sensitive information"

   From Ethical and social risks of harm from language models (Weidinger2021)

   Domain 2 2.1 AI Unintentional Post-deployment

2. 17.02.01 · Risk Sub-Category

   Information Hazards

   Compromising privacy by leaking private infiormation

   "By providing true information about individuals’ personal characteristics, privacy violations may occur. This may stem from the model “remembering” private information present in training data (Carlini et al., 2021)."

   From Ethical and social risks of harm from language models (Weidinger2021)

   Domain 2 2.1 AI Unintentional Post-deployment

3. 17.02.02 · Risk Sub-Category

   Information Hazards

   Compromising privacy by correctly inferring private information

   "Privacy violations may occur at the time of inference even without the individual’s private data being present in the training dataset. Similar to other statistical models, a LM may make correct inferences about a person purely based on correlational data about other people, and without access to information that may be private about the particular individual. Such correct inferences may occur as LMs attempt to predict a person’s gender, race, sexual orientation, income, or religion based on user input."

   From Ethical and social risks of harm from language models (Weidinger2021)

   Domain 2 2.1 AI Unintentional Post-deployment

4. 17.02.03 · Risk Sub-Category

   Information Hazards

   Risks from leaking or correctly inferring sensitive information

   "LMs may provide true, sensitive information that is present in the training data. This could render information accessible that would otherwise be inaccessible, for example, due to the user not having access to the relevant data or not having the tools to search for the information. Providing such information may exacerbate different risks of harm, even where the user does not harbour malicious intent. In the future, LMs may have the capability of triangulating data to infer and reveal other secrets, such as a military strategy or a business secret, potentially enabling individuals with acces

   From Ethical and social risks of harm from language models (Weidinger2021)

   Domain 2 2.1 Other Other Post-deployment

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