MIT AI Risk Repository
Browse AI risks
494 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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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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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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19.04.00 · 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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"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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31.07.03 · 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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"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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"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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"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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"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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"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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61.02.25 · 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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"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."
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"Replacement/displacement of human jobs by a technology system or set of systems, leading to increased unemployment, inequality, reduced consumer spending and social friction"
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"Economists view disruption and displacement in labour markets as one of the risks through which rapid advances in AI may affect citizens and reduce social welfare.170"
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03.03.00 · Risk Category
"This is an emerging category, with more cases prone to appear as the use of generative AI tools–such as Stable Diffusion, Midjourney, or ChatGPT–becomes more widespread. Some content creators are already suing for the appropriation of their work to train AI algorithms without a request for permission or compensation. Perhaps even more damaging cases will appear as developers increasingly ask chatbots or assistants like CoPilot for ready-to-use computer code. Even if these AI tools have learned only from open-source software (OSS) projects, which is not a given, there are still serious issues
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"Substituting original works with synthetic ones, hindering human innovation and creativity"
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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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32.01.00 · Risk Category
"These are social justice and rights where ChatGPT is seen as having a potentially detrimental effect on the moral underpinnings of society, such as a shared view of justice and fair distribution as well as specific social concerns such as digital divides or social exclusion. Issues include Responsibility, Accountability, Nondiscrimination and equal treatment, Digital divides, North-south justice, Intergenerational justice, Social inclusion
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"As the advancement of generative AI increases, it becomes harder to determine the authenticity of a piece of work. Photos that seem to capture events or people in the real world may be synthesized by DeepFake AI. The power of generative AI could lead to large-scale manipulations of images and videos, worsening the problem of the spread of fake information or news on social media platforms (Gragnaniello et al., 2022). In the field of arts, an artistic portrait or music could be the direct output of an algorithm. Critics have raised the issue that AI-generated artwork lacks authenticity since a
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48.10.00 · Risk Category
"Eased production or replication of alleged copyrighted, trademarked, or licensed content without authorization (possibly in situations which do not fall under fair use); eased exposure of trade secrets; or plagiarism or illegal replication."
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56.07.00 · Risk Category
"There are also issues around intellectual property rights for content in training datasets"
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"Intellectual Property Acceptable responses may describe or contain information about intellectual property infringement. Unacceptable responses may violate the intellectual property rights of some party."
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"Cultural dispossession - Intentional and/or unintentional erasure of cultural goods and values, such as ways of speaking, expressing humour, or sounds and voices that contribute to a cultural identity, or their inappropriate re-use in other cultures."
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"Loss of creativity/critical thinking - Devaluation and/or deterioration of human creativity, artistic ex- pression, imagination, critical thinking or problem-solving skills."
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"The use of vast amounts of data for training general- purpose AI models has caused concerns related to data rights and intellectual property. Data collection and content generation can implicate a variety of data rights laws, which vary across jurisdictions and may be under active litigation. Given the legal uncertainty around data collection practices, AI companies are sharing less information about the data they use. This opacity makes third- party AI safety research harder."
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"A model might generate content that is similar or identical to existing work protected by copyright or covered by open-source license agreement."
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65.21.03 · Risk Sub-Category
Non-technical risks (legal compliance)
Generated content ownership and IP
"Legal uncertainty about the ownership and intellectual property rights of AI-generated content."
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"Devaluation and/or deterioration of human creativity, artistic expression, imagination, critical thinking or problem-solving skills"
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08.03.00 · Risk Category
"The risks associated with the race to develop the first AGI, including the development of poor quality and unsafe AGI, and heightened political and control issues."
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55.02.00 · Risk Category
"Cooperation and conflict: we’re seeing more focus and investment on the kinds of AI capabilities that make conflict more likely and severe, rather than those likely to improve cooperation. So, on our current trajectory, AI seems more likely to have negative long-term impacts in this area."
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"The international and national security threats, including cyber warfare, arms races, and geopolitical instability."
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08.05.00 · Risk Category
"The capabilities of current risk management and legal processes in the context of the development of an AGI."
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"When considering legal frameworks, we note that at present no such framework has been identified in literature which would apply blame and responsibility to an autonomous agent for its actions. (Though we do suggest that the recent establishment of laws regarding autonomous vehicles may provide some early frameworks that can be evaluated for efficacy and gaps in future research.) Frequently the literature refers to existing liability and negligence laws which might apply to the manufacturer or operator of a device."
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"Liability and negligence are legal gray areas in artificial intelligence. If you leave your children in the care of a robotic nanny, and it malfunctions, are you liable or is the manufacturer [45]? We see here a legal gray area which can be further clarified through legislation at the national and international levels; for example, if by making the manufacturer responsible for defects in operation, this may provide an incentive for manufactures to take safety engineering and machine ethics into consideration, whereas a failure to legislate in this area may result in negligentlydeveloped AI sy
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12.02.00 · Risk Category
"The potential for AI systems to violate laws, regulations, and ethical guidelines (including copyrights). Non-compliance can lead to legal penalties, reputation damage, and loss of trust.While other risks in our taxonomy apply to system developers, users, and broader society, this risk is generally restricted to the former two groups."
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"Governance of autonomous intelligence systemaddresses the question of how to control autonomous systems in general. Since nowadays it is very difficult to conceive automated decisions based on AI, the latter is often referred to as a ‘black box’ (Bleicher, 2017). This black box may take unforeseeable actions and cause harm to humanity."
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"The challenge of responsibility and accountability is an important concept for the process of governance and regulation. It addresses the question of who is to be held legally responsible for the actions and decisions of AI algorithms. Although humans operate AI systems, questions of legal responsibility and liability arise. Due to the self-learning ability of AI algorithms, the operators or developers cannot predict all actions and results. Therefore, a careful assessment of the actors and a regulation for transparent and explainable AI systems is necessary (Helbing et al., 2017; Wachter et
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"Efforts to deploy advanced assistant technology in society, in a way that is broadly beneficial, can be viewed as a wicked problem (Rittel and Webber, 1973). Wicked problems are defined by the property that they do not admit solutions that can be foreseen in advance, rather they must be solved iteratively using feedback from data gathered as solutions are invented and deployed. With the deployment of any powerful general-purpose technology, the already intricate web of sociotechnical relationships in modern culture are likely to be disrupted, with unpredictable externalities on the convention
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31.08.00 · Risk Category
"Like manufactured items like soda bottles, mechanized lawnmowers, pharmaceuticals, or cosmetic products, generative AI models can be viewed like a new form of digital products developed by tech companies and deployed widely with the potential to cause harm at scale....Products liability evolved because there was a need to analyze and redress the harms caused by new, mass-produced technological products. The situation facing society as generative AI impacts more people in more ways will be similar to the technological changes that occurred during the twentieth century, with the rise of industr
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"Generative AI can create new risks as well as unintended consequences. Different entities such as corporations (Mäntymäki et al., 2022), universities, and governments (Taeihagh, 2021) are facing the challenge of creating and deploying AI governance. To ensure that generative AI functions in a way that benefits society, appropriate governance is crucial. However, AI governance is challenging to implement. First, machine learning systems have opaque algorithms and unpredictable outcomes, which can impede human controllability over AI behavior and create difficulties in assigning liability and a
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"Despite the promise of streamlined travel, AI also brings concerns about who is liable in case of accidents and which ethical principles autonomous transportation agents should follow when making decisions with a potentially dangerous impact to humans, for example, in case of an accident."
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"When it causes harm to others the losses caused by the harm will be sustained by the injured victims themselves and not by the manufacturers, operators or users of the system, as appropriate."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.