QB4AIRA: A Question Bank for AI Risk Assessment (2305.09300v2)
Abstract: The rapid advancement of AI, represented by ChatGPT, has raised concerns about responsible AI development and utilization. Existing frameworks lack a comprehensive synthesis of AI risk assessment questions. To address this, we introduce QB4AIRA, a novel question bank developed by refining questions from five globally recognized AI risk frameworks, categorized according to Australia's AI ethics principles. QB4AIRA comprises 293 prioritized questions covering a wide range of AI risk areas, facilitating effective risk assessment. It serves as a valuable resource for stakeholders in assessing and managing AI risks, while paving the way for new risk frameworks and guidelines. By promoting responsible AI practices, QB4AIRA contributes to responsible AI deployment, mitigating potential risks and harms.
- OpenAI. Gpt-4 system card. Technical report, OpenAI, March 2023.
- Responsible ai pattern catalogue: a multivocal literature review. arXiv preprint arXiv:2209.04963, 2022.
- A systematic mapping study on responsible ai risk assessment. arXiv preprint arXiv:2301.11616, 2023.
- Questioning the ai: informing design practices for explainable ai user experiences. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pages 1–15, 2020.
- Question-driven design process for explainable ai user experiences. arXiv preprint arXiv:2104.03483, 2021.
- DISER. Australia’s ai ethics principles, 2019.
- William MK Trochim. An introduction to concept mapping for planning and evaluation. Evaluation and program planning, 12(1):1–16, 1989.
- Yan-Yan Song and LU Ying. Decision tree methods: applications for classification and prediction. Shanghai archives of psychiatry, 27(2):130, 2015.
- The global landscape of ai ethics guidelines. Nature Machine Intelligence, 1(9):389–399, 2019.
- Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for ai. Berkman Klein Center Research Publication, (2020-1), 2020.
- Derisking ai by design: How to build risk management into ai development. McKinsey & Company, 2020.
- Edward N Adams III. Another representation of binary tree traversal. Information Processing Letters, 2(2):52–54, 1973.
- Sung Une Lee (8 papers)
- Harsha Perera (14 papers)
- Boming Xia (14 papers)
- Yue Liu (256 papers)
- Qinghua Lu (100 papers)
- Liming Zhu (101 papers)
- Olivier Salvado (16 papers)
- Jon Whittle (32 papers)