MIT AI Risk Repository · Risk Category · 19.01.00
Technological, Data and Analytical AI Risks
Description
"Fig 3 shows that technological, data, and analytical AI risks are characterised by the loss of control over AI systems, whereby in particular the autonomous decision and its consequences are classified as risk factors since they are not subject to human influence (Boyd & Wilson, 2017; Scherer, 2016; Wirtz et al., 2019). Programming errors in algorithms due to the lack of expert knowledge or to the increasing complexity and black-box character of AI systems may also lead to undesired AI results (Boyd & Wilson, 2017; Danaher et al., 2017). In addition, a lack of data, poor data quality, and bia
From Governance of artificial intelligence: A risk and guideline-based integrative framework (Wirtz2022), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
Other entries from Wirtz2022
- Loss of control of autonomous systems and unforeseen behaviour due to lack of transparency and self-programming/ reprogramming
- Programming error
- Lack of data, poor data quality, and biases in training data
- Vulnerability of AI systems to attacks and misuse
- Lack of AI experts with comprehensive AI knowledge
- Immaturity of AI technology can cause incorrect decisions
- High investment costs of AI hinder integration
- Informational and Communicational AI Risks
- Manipulation and control of information provision (e.g., personalised adds, filtered news)
- Disinformation and computational propaganda
- Censorship of opinions expressed in the Internet restricts freedom of expression
- Endangerment of data protection through AI cyberattacks