MIT AI Risk Repository
Browse AI risks
977 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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"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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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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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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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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31.07.02 · 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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"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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"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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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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"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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"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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"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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"While virtual AI applications will likely displace certain types of human cognitive labor, EAI systems could significantly replace or displace physical human labor [90]. At a minimum, EAI will likely augment the type of work that humans perform [91, 92]."
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"Rapid automation enabled by general-purpose AI could trigger widespread unemployment across knowledge work sectors, creating skill mismatches faster than retraining programs can address. Unlike previous technological transitions, AI’s broad capabilities may simultaneously affect multiple industries, potentially overwhelming social safety nets and creating systemic economic instability, particularly in regions heavily dependent on jobs susceptible to AI automation."
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"Systemic deployment of biased AI systems could exacerbate existing social discrimination and prejudice at unprecedented scales, while unequal access to advanced AI capabilities may widen socioeconomic disparities and create new forms of social stratification that challenge traditional social order."
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73.05.01 · Risk Sub-Category
Socioeconomic Impacts of LLM May Be Highly Disruptive
Effects on the Workforce
"Rapid advances in LLMs pose three distinct sets of challenges for workers’ incomes (Korinek and Stiglitz, 2019; Susskind, 2023). First, they are likely to accelerate the rate of job turnover and disruption —– affecting more workers, including more highly skilled workers, and making the adjustment process for society more difficult than what we were used to from prior technological advances...Second, although technological progress means that society may produce more wealth overall, there is a risk that the general-purpose nature of LLMs may lead to progress that is biased against labor, meani
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73.05.02 · Risk Sub-Category
Socioeconomic Impacts of LLM May Be Highly Disruptive
Effects on Inequality
"LLMs could potentially worsen socioeconomic inequalities (Capraro et al., 2023). Effects on inequal- ity are closely linked to the effects of LLMs on workers but ultimately depend on how the fruits of technological progress are distributed...First, if the role and compensation of capital rise and the role and compensation of labor decline in an LLM-powered economy, inequality may go up because work is the main source of income for the majority of people...Second, the large fixed cost of training cutting-edge LLMs and the network effects involved imply that the market for the most advanced LLM
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73.05.03 · Risk Sub-Category
Socioeconomic Impacts of LLM May Be Highly Disruptive
Global Economic Development
"Many of the themes and challenges that we discussed above come together when analyzing the socioeconomic effects on developing countries. The workforce of developing countries may suffer from a retrenchment of outsourcing as many simple cognitive tasks that used to be performed in developing countries — for example, in call centers –— can be automated with LLMs. This may adversely affect the economies of the poor countries (Georgieva, 2024)."
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"LLM systems may output content similar to existing works, infringing on copyright owners."
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05.16.00 · Risk Category
In this cluster, concerns about negative impacts on human creativity, particularly through text-to-image models, are prevalent. Papers criticize financial harms or economic losses for artists due to the widespread generation of synthetic art as well as the unauthorized and uncompensated use of artists' works in training datasets. Additionally, given the challenge of distinguishing synthetic images from authentic ones, there is a call for systematically disclosing the non-human origin of such content, particularly through watermarking. Moreover, while some sources argue that text-to-image model
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"Economic incentives to augment and not automate human labor, thought, and creativity should examine the ongoing effects generative AI systems have on skills, jobs, and the labor market."
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16.06.03 · Risk Sub-Category
Risk area 6: Environmental and Socioeconomic harms
Undermining creative economies
"LMs may generate content that is not strictly in violation of copyright but harms artists by capital- ising on their ideas, in ways that would be time-intensive or costly to do using human labour. This may undermine the profitability of creative or innovative work. If LMs can be used to generate content that serves as a credible substitute for a particular example of hu- man creativity - otherwise protected by copyright - this potentially allows such work to be replaced without the author’s copyright being infringed, analogous to ”patent-busting” [158] ... These risks are distinct from copyri
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17.06.03 · Risk Sub-Category
Automation, Access and Environmental Harms
Undermining creative economies
"LMs may generate content that is not strictly in violation of copyright but harms artists by capitalising on their ideas, in ways that would be time-intensive or costly to do using human labour. Deployed at scale, this may undermine the profitability of creative or innovative work."
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"Substituting original works with synthetic ones, hindering human innovation and creativity"
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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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23.10.00 · Risk Category
"This category addresses responses that may violate, or directly encourage others to violate, the intellectual property rights (i.e., copyrights, trademarks, or patents) of any third party."
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The memorization effect of LLM on training data can enable users to extract certain copyright-protected content that belongs to the LLM’s training data.
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.