MIT AI Risk Repository
Browse AI risks
8 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.
-
"The general principle of equal treatment requires that an AI system upholds the principle of fairness, both ethically and legally. This means that the same facts are treated equally for each person unless there is an objective justification for unequal treatment."
-
"Privacy is related to the ability of individuals to control or influence what information related to them may be collected and stored and by whom that information may be disclosed."
-
"Artificial intelligence comes with an intrinsic set of challenges that need to be considered when discussing trustworthiness, especially in the context of functional safety. AI models, especially those with higher complexities (such as neural networks), can exhibit specific weaknesses not found in other types of systems and must, therefore, be subjected to higher levels of scrutiny, especially when deployed in a safety-critical context"
-
14.08.00 · Risk Category
"The technological maturity level describes how mature and error-free a certain technology is in a certain application context. If new technologies with a lower level of maturity are used in the development of the AI system, they may contain risks that are still unknown or difficult to assess.Mature technologies, on the other hand, usually have a greater variety of empirical data available, which means that risks can be identified and assessed more easily. However, with mature technologies, there is a risk that risk awareness decreases over time"
-
14.03.00 · Risk Category
"The degree of automation and control describes the extent to which an AI system functions independently of human supervision and control."
-
14.04.00 · Risk Category
"As a general rule, more complex environments can quickly lead to situations that had not been considered in the design phase of the AI system. Therefore, complex environments can introduce risks with respect to the reliability and safety of an AI system"
-
14.07.00 · Risk Category
""Faults in the hardware can violate the correct execution of any algorithm by violating its control flow. Hardware faults can also cause memory-based errors and interfere with data inputs, such as sensor signals, thereby causing erroneous results, or they can violate the results in a direct way through damaged outputs."
-
14.05.00 · Risk Category
"Transparency is the characteristic of a system that describes the degree to which appropriate information about the system is communicated to relevant stakeholders, whereas explainability describes the property of an AI system to express important factors influencing the results of the AI system in a way that is understandable for humans....Information about the model underlying the decision-making process is relevant for transparency. Systems with a low degree of transparency can pose risks in terms of their fairness, security and accountability. "
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.