Privacy and data collection concerns (collecting personal information or personally identifiable information)
AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or cause loss of confidential intellectual property.
"Generative AI developers train their models with extensive datasets often gathered through online web scraping of websites that may include personal data or personally identifiable information (PII). For most generative AI applications, such as initial model training, the primary concerns are the quantity, variety, and quality of the data, not whether they include personally identifiable information. However, some web-scraped datasets may inadvertently include personal data. Additionally, when downstream developers integrate generative AI into their products or services by fine- tuning a pre-trained model, they often use their own in-house data, which may include personal information."(p. 97)
Part of Legal challenges
Other risks from G'sell (2024) (33)
Technical and operational risks
7.3 Lack of capability or robustnessTechnical and operational risks > Technical vulnerabilities (Robustness - unexpected behaviour)
7.3 Lack of capability or robustnessTechnical and operational risks > Technical vulnerabilities (Robustness - vulnerability to jailbreaking
2.2 AI system security vulnerabilities and attacksTechnical and operational risks > Technical vulnerabilities (The risk of misalignment)
7.1 AI pursuing its own goals in conflict with human goals or valuesTechnical and operational risks > Factually incorrect content (inaccuracies and fabricated sources)
3.1 False or misleading informationTechnical and operational risks > Opacity (the black box problem)
7.4 Lack of transparency or interpretability