MIT AI Risk Repository
Browse AI risks
39 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.
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19.05.00 · Risk Category
"In the context of ethical AI risks, two risks are of particular importance. First, AI systems may lack a legitimate ethical basis in establishing rules that greatly influence society and human relationships (Wirtz & Müller, 2019). In addition, AI-based discrimination refers to an unfair treatment of certain population groups by AI systems. As humans initially programme AI systems, serve as their potential data source, and have an impact on the associated data processes and databases, human biases and prejudices may also become part of AI systems and be reproduced (Weyerer & Langer, 2019, 2020
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19.01.03 · Risk Sub-Category
Technological, Data and Analytical AI Risks
Lack of data, poor data quality, and biases in training data
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19.05.02 · Risk Sub-Category
Unfair statistical AI decisions and discrimination of minorities
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19.04.02 · Risk Sub-Category
Privacy and safety concerns due to ubiquity of AI systems in economy and society (lack of social acceptance)
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19.01.04 · Risk Sub-Category
Technological, Data and Analytical AI Risks
Vulnerability of AI systems to attacks and misuse
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19.02.00 · Risk Category
"Informational and communicational AI risks refer particularly to informational manipulation through AI systems that influence the provision of information (Rahwan, 2018; Wirtz & Müller, 2019), AIbased disinformation and computational propaganda, as well as targeted censorship through AI systems that use respectively modified algorithms, and thus restrict freedom of speech."
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19.02.01 · Risk Sub-Category
Informational and Communicational AI Risks
Manipulation and control of information provision (e.g., personalised adds, filtered news)
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19.02.02 · Risk Sub-Category
Informational and Communicational AI Risks
Disinformation and computational propaganda
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19.02.04 · Risk Sub-Category
Informational and Communicational AI Risks
Endangerment of data protection through AI cyberattacks
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19.04.03 · Risk Sub-Category
Hazardous misuse of AI systems bears danger to the society in public spaces (e.g., hacker attacks on autonomous weapons)
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19.04.05 · Risk Sub-Category
Decreasing human interaction as AI systems assume human tasks, disturbing well-being
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19.02.03 · Risk Sub-Category
Informational and Communicational AI Risks
Censorship of opinions expressed in the Internet restricts freedom of expression
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19.03.03 · Risk Sub-Category
Loss of supervision and control of business processes
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19.05.06 · Risk Sub-Category
AI systems may undermine human values (e.g., free will, autonomy)
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19.06.02 · Risk Sub-Category
Technology obedience and lack of governance through increasing application of AI systems
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19.01.07 · Risk Sub-Category
Technological, Data and Analytical AI Risks
High investment costs of AI hinder integration
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19.03.04 · Risk Sub-Category
Financial feasibility and high investment costs for AI technology to remain competitive
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19.03.05 · Risk Sub-Category
Lack of AI strategy and acceptance/resistance among employees and customers
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19.06.04 · Risk Sub-Category
Hard legislation on AI hinders innovation processes and further AI development
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19.03.00 · Risk Category
"In the context of economic AI risks two major risks dominate. These refer to the disruption of the economic system due to an increase of AI technologies and automation. For instance, a higher level of AI integration into the manufacturing industry may result in massive unemployment, leading to a loss of taxpayers and thus negatively impacting the economic system (Boyd & Wilson, 2017; Scherer, 2016). This may also be associated with the risk of losing control and knowledge of organisational processes as AI systems take over an increasing number of tasks, replacing employees in these processes.
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19.03.02 · Risk Sub-Category
Replacement of humans and unemployment due to AI automation
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19.04.00 · Risk Category
"Social AI risks particularly refer to loss of jobs (technological unemployment) due to increasing automation, reflected in a growing resistance by employees towards the integration of AI (Thierer et al., 2017; Winfield & Jirotka, 2018). In addition, the increasing integration of AI systems into all spheres of life poses a growing threat to privacy and to the security of individuals and society as a whole (Winfield & Jirotka, 2018; Wirtz et al., 2019)."
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19.03.01 · Risk Sub-Category
Disruption of economic systems (e.g., labour market, money value, tax system)
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19.01.05 · Risk Sub-Category
Technological, Data and Analytical AI Risks
Lack of AI experts with comprehensive AI knowledge
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19.06.00 · Risk Category
"Legal and regulatory risks comprise in particular the unclear definition of responsibilities and accountability in case of AI failures and autonomous decisions with negative impacts (Reed, 2018; Scherer, 2016). Another great risk in this context refers to overlooking the scope of AI governance and missing out on important governance aspects, resulting in negative consequences (Gasser & Almeida, 2017; Thierer et al., 2017)."
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19.06.01 · Risk Sub-Category
Unclear definition of responsibilities and accountability for AI judgments and their consequences
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19.06.03 · Risk Sub-Category
Great scope and ubiquity of AI make appropriate governance difficult, coverage of governance scope almost impossibl
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19.06.05 · Risk Sub-Category
Capturing future AI development and their threats with appropriate mechanism
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19.01.01 · Risk Sub-Category
Technological, Data and Analytical AI Risks
Loss of control of autonomous systems and unforeseen behaviour due to lack of transparency and self-programming/ reprogramming
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19.01.06 · Risk Sub-Category
Technological, Data and Analytical AI Risks
Immaturity of AI technology can cause incorrect decisions
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19.05.04 · Risk Sub-Category
Misinterpretation of human value definitions/ ethics by AI systems
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19.05.05 · Risk Sub-Category
Incompatibility of human vs. AI value judgment due to missing human qualities
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19.01.00 · Risk Category
"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
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.