MIT AI Risk Repository
Browse AI risks
2,500 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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62.13.02 · Risk Sub-Category
Negative Externality Domains (Other harms from AI development and use)
Geopolitical harms (potential for conflict due to power imbalances)
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"EAI deployment could accelerate the consolidation of economic and political power. Unlocking increasing returns to capital for EAI owners, EAI will decrease employers’ reliance on and responsiveness to the needs of human labor [101]."
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"Over-reliance on a limited number of dominant AI providers could create critical single points of failure across essential services. Market concentration in AI development may lead to scenarios where technical failures, cyber-attacks, or policy decisions by a few companies could simultaneously disrupt healthcare systems, financial services, transportation networks, and communication infrastructure, creating cascading failures across interconnected critical systems."
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"Asymmetric AI development capabilities between nations could exacerbate geopolitical tensions and create new forms of technological dependency. Countries lacking advanced AI capabilities may become increasingly dependent on foreign AI systems for critical functions, while AI-leading nations may gain disproportionate influence over global economic and security systems, potentially destabilizing international cooperation frameworks."
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73.06.00 · Risk Category
"The increasing power and influence of large corporations may make effective governance difficult. There exists a power asymmetry between corporate entities profiting from LLMs and other social groups (e.g. civil society). State-of-the-art LLMs are developed by or in partnership with, some of the world’s largest private tech companies...This poses a risk of governance protocols related to LLMs becoming excessively favorable to tech companies, potentially leading to regulatory capture at the cost of the interests of other societal groups, particularly marginalized communities who have historica
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05.12.00 · Risk Category
The literature frequently highlights concerns that generative AI systems could adversely impact the economy, potentially even leading to mass unemployment. This pertains to various fields, ranging from customer services to software engineering or crowdwork platforms. While new occupational fields like prompt engineering are created, the prevailing worry is that generative AI may exacerbate socioeconomic inequalities and lead to labor displacement. Additionally, papers debate potential large-scale worker deskilling induced by generative AI, but also productivity gains contingent upon outsourcin
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09.02.06 · Risk Sub-Category
Domain-specific AI - Effects on humans and other living beings: Non-existential risks
Inequality of wealth
"Because a single human actor controlling an artificially intelligent agent will be able to harness greater power than a single human actor, this may create inequalities of wealth"
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09.03.01 · Risk Sub-Category
AGI - Effects on humans and other living beings: Existential risks
Direct competition with humans
"One or more artificial agent(s) could have the capacity to directly outcompete humans, for example through capacity to perform work faster, better adaptation to change, vaster knowledge base to draw from, etc. This may result in human labor becoming more expensive or less effective than artificial labor, leading to redundancies or extinction of the human labor force."
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"AI agents may compete against humans for jobs, though history shows that when a technology replaces a human job, it creates new jobs that need more skills."
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10.04.00 · Risk Category
"Eliminated jobs in various types of companies."
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"Two key ethical concerns in the use of crowdwork for generative AI systems are: crowdworkers are frequently subject to working conditions that are taxing and debilitative to both physical and mental health, and there is a widespread deficit in documenting the role crowdworkers play in AI development. This contributes to a lack of transparency and explainability in resulting model outputs. Manual review is necessary to limit the harmful outputs of AI systems, including generative AI systems. A common harmful practice is to intentionally employ crowdworkers with few labor protections, often tak
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16.06.02 · Risk Sub-Category
Risk area 6: Environmental and Socioeconomic harms
Increasing inequality and negative effects on job quality
"Advances in LMs and the language technologies based on them could lead to the automation of tasks that are currently done by paid human workers, such as responding to customer-service queries, with negative effects on employment [3, 192]."
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17.06.02 · Risk Sub-Category
Automation, Access and Environmental Harms
Increasing inequality and negative effects on job quality
"Advances in LMs, and the language technologies based on them, could lead to the automation of tasks that are currently done by paid human workers, such as responding to customer-service queries, translating documents or writing computer code, with negative effects on employment."
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"Amplifying social and economic inequality, or precarious or low-quality work"
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18.06.05 · Risk Sub-Category
Socioeconomic and environmental harms
Exploitative data sourcing and enrichment
"Perpetuating exploitative labour practices to build AI systems (sourcing, user testing)"
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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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"Frey and Osborne (2017) analyzed over 700 different jobs regarding their potential for replacement and automation, finding that 47 percent of the analyzed jobs are at risk of being completely substituted by robots or algorithms. This substitution of workforce can have grave impacts on unemployment and the social status of members of society (Stone et al., 2016)"
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"These harms pertain to an individual’s or group’s economic standing. At the individual level, such harms include adverse impacts on an individual’s income, job quality or employment status. At the group level, such harms include deepening inequalities between groups or frustrating a group’s access to resources. Advanced AI assistants could cause economic harm by controlling, limiting or eliminating an individual’s or society’s ability to access financial resources, money or financial decision-making, thereby influencing an individual’s ability to accumulate wealth.
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31.07.00 · Risk Category
Major tech companies have also been the dominant players in developing new generative AI systems because training generative AI models requires massive swaths of data, computing power, and technical and financial resources. Their market dominance has a ripple effect on the labor market, affecting both workers within these companies and those implementing their generative AI products externally. With so much concentrated market power, expertise, and investment resources, these handful of major tech companies employ most of the research and development jobs in the generative AI field. The power
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31.07.02 · Risk Sub-Category
Labor Manipulation, Theft, and Displacement
Job Automation Instead of Augmentation
"There are both positive and negative aspects to the impact of AI on labor. A White House report states that AI “has the potential to increase productivity, create new jobs, and raise living standards,” but it can also disrupt certain industries, causing significant changes, including job loss. Beyond risk of job loss, workers could find that generative AI tools automate parts of their jobs—or find that the requirements of their job have fundamentally changed. The impact of generative AI will depend on whether the technology is intended for automation (where automated systems replace human wor
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31.07.03 · Risk Sub-Category
Labor Manipulation, Theft, and Displacement
Devaluation of Labor & Heightened Economic Inequality
"According to a White House report, much of the development and adoption of AI is intended to automate rather than augment work. The report notes that a focus on automation could lead to a less democratic and less fair labor market...In addition, generative AI fuels the continued global labor disparities that exist in the research and development of AI technologies... The development of AI has always displayed a power disparity between those who work on AI models and those who control and profit from these tools. Overseas workers training AI chatbots or people whose online content has been inv
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"The labor market can face challenges from generative AI. As mentioned earlier, generative AI could be applied in a wide range of applications in many industries, such as education, healthcare, and advertising. In addition to increasing productivity, generative AI can create job displacement in the labor market (Zarifhonarvar, 2023). A new division of labor between humans and algorithms is likely to reshape the labor market in the coming years. Some jobs that are originally carried out by humans may become redundant, and hence, workers may lose their jobs and be replaced by algorithms (Pavlik,
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"Industries that require less creativity, critical thinking, and personal or affective interaction, such as translation, proofreading, responding to straightforward inquiries, and data processing and analysis, could be significantly impacted or even replaced by generative AI (Dwivedi et al., 2023). This disruption caused by generative AI could lead to economic turbulence and job volatility, while generative AI can facilitate and enable new business models because of its ability to personalize content, carry out human-like conversational service, and serve as intelligent assistants."
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33.04.03 · Risk Sub-Category
Challenges associated with the economy:
Income inequality and monopolies
"Generative AI can create not only income inequality at the societal level but also monopolies at the market level. Individuals who are engaged in low-skilled work may be replaced by generative AI, causing them to lose their jobs (Zarifhonarvar, 2023). The increase in unemployment would widen income inequality in society (Berg et al., 2016). With the penetration of generative AI, the income gap will widen between those who can upgrade their skills to utilize AI and those who cannot. At the market level, large companies will make significant advances in the utilization of generative AI, since t
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"This category involves almost 9% of the articles and deals with ethical concerns arising from AI's capacity to interact with humans in the workplace."
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"AI is predicted to bring increased GDP per capita by performing existing jobs more efficiently and compensating for a decline in the workforce, especially due to population aging, the potential substitution of many low- and middle-income jobs could bring extensive unemployment"
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"While AI is predicted to bring increased GDP per capita by performing existing jobs more efficiently and compensating for a decline in the workforce, especially due to population aging, the potential substitution of many low- and middle-income jobs could bring extensive unemployment."
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45.02.11 · Risk Sub-Category
Safety risks in AI Applications
Ethical Risks (Risks of exacerbating social discrimination and prejudice, and widening the intelligence divide)
"AI can be used to collect and analyze human behaviors, social status, economic status, and individual personalities, labeling and categorizing groups of people to treat them discriminatingly, thus causing systematic and structural social discrimination and prejudice. At the same time, the intelligence divide would be expanded among regions."
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47.04.03 · Risk Sub-Category
Environmental, economical, and societal challenges
Impact on labor markets (job loss and displacement)
"Currently, a significant share of workers (three in five) worry about losing their jobs entirely to AI in the next 10 years—particularly those who already work with AI. Some studies conclude that AI tools (generative and non-generative) will create significant job losses.573 The OECD has found that occupations at highest risk of being lost to automation from AI account for about 27% of employment.5"
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"Unlike previous waves of automation, general- purpose AI has the potential to automate a very broad range of tasks, which could have a significant effect on the labour market. This could mean many people could lose their current jobs. Labour market frictions, such as the time needed for workers to learn new skills or relocate for new jobs, could cause unemployment in the short run even if overall labour demand remained unchanged."
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"Without training data, ML cannot take place. Much of this data comes from paid clickwork (also called “platform work” [170] or “microwork” [558]), unpaid crowdsourcing, and unpaid user behavior capture. Clickworkers, mainly in the global south, perform repetitive data-labeling tasks for use in the training of ML models [558]. The market value of such annotations “is projected to reach $13.7 billion by 2030” [228] and the annotation industry is widely reported to have little concern for workers’ rights. Besides welfare and rights, the invisibility of this contribution arguably contributes to a
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55.03.02 · Risk Sub-Category
Increased power concentration and inequality
AI-based automation increases income inequality
"It seems quite plausible that progress in reinforcement learning and language models specifically could make it possible to automate a large amount of manual labour and knowledge work respectively [35, 45, 69], leading to widespread unemployment, and the wages for many remaining jobs being driven down by increased supply."
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56.02.00 · Risk Category
"More broadly, bad decisions or errors by AI tools could lead to discrimination or deeper inequality"
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"Job loss/losses - Replacement/displacement of human jobs by a technology system, leading to increased unemployment, inequality, reduced consumer spending, and social friction."
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"Labour exploitation - Use of under-paid and/or offshore labour to develop, manage or optimise a technology system."
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"Societal destabilisation - Societal instability in the form of strikes, demonstrations and other types of civil unrest caused by loss of jobs to technology, unfair algorithmic outcomes, disinformation, etc."
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"Societal inequality - Increased difference in social status or wealth between individuals or groups caused or amplified by a technology system, leading to the loss of social and community wellbeing/cohesion and destabilisation."
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"Political instability - Political polarisation or unrest caused by increased inequality, job losses, over- dependence on technology making societies vulnerable to systemic failures, etc, arising from or amplified by the use or misuse of a technology system."
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"Current general-purpose AI is likely to transform the nature of many existing jobs, create new jobs, and eliminate others. The net impact on employment and wages will vary significantly across countries, across sectors, and even across different workers within the same job."
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"Economic disruptions ranging from large impacts on the labor market to broader economic changes that could lead to exacerbated wealth inequality, instability in the financial system, labor exploitation or other economic dimensions."
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61.02.01 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Ability to automate jobs
"The ability to automate jobs by AI models and systems can lead to significant job displacement, economic disruption, and social inequality."
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61.02.10 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Capabilities that enable substitution of humans
"The progressive replacement of human roles by AI models and systems can lead to societal disruption."
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61.02.25 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Exploitation in AI development
"Outsourcing tasks like data labeling to low-income countries can perpetuate inequality."
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62.11.02 · Risk Sub-Category
Negative Externality Domains (Manufacturing of AI Hardware)
Human rights harms from exploitation of human labour
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"Widespread adoption of foundation model-based AI systems might lead to people's job loss as their work is automated if they are not reskilled."
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"When workers who train AI models such as ghost workers are not provided with adequate working conditions, fair compensation, and good health care benefits that also include mental health."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.