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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"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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"According to the U.S. Copyright Office (n.d..), copyright is "a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression" (U.S. Copyright Office, n.d..). Generative AI is designed to generate content based on the input given to it. Some of the contents generated by AI may be others' original works that are protected by copyright laws and regulations. Therefore, users need to be careful and ensure that generative AI has been used in a legal manner such that the content that it generates does not violate copyri
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"Even though models generally create new outputs, it is possible that the content produced by a generative AI tool—such as an image, or even computer code— could turn out to be almost identical to that used in the training data. Given that generative AI models tend to memorize fragments of their training data, they might reproduce these fragments, potentially leading to charges of copyright infringement."
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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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"The use of large amounts of copyrighted data for training general- purpose AI models poses a challenge to traditional intellectual property laws, and to systems of consent, compensation, and control over data. The use of copyrighted data at scale by organisations developing general- purpose AI is likely to alter incentives around creative expression."
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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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64.02.02 · Risk Sub-Category
Misuse tactics that exploit GenAI capabilities (Realistic depictions of non-humans)
Intellectual Property (IP) Infringement
"Use a person's IP without their permission"
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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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"AI systems might overly represent certain cultures that result in a homogenization of culture and thoughts."
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01.04.00 · Risk Category
As a side effect of a primary goal like profit or influence, AI creators can willfully allow it to cause widespread societal harms like pollution, resource depletion, mental illness, misinformation, or injustice.
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53.04.01 · Risk Sub-Category
Indirect AI contributions to existential risks
Destabilising political impacts from AI systems
"(e.g., polarization, legitimacy of elections), international political economy, or international security196 in terms of the balance of power, technology races and international stability, and the speed and character of war"
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"Increased competition - The inappropriate or unethical use of technology to gain market share."
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61.02.27 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
High-speed AI operations
"The fast operational speed of AI models and systems in competitive environments can lead to errors that are difficult to detect and correct in time."
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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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19.06.01 · Risk Sub-Category
Unclear definition of responsibilities and accountability for AI judgments and their consequences
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20.01.00 · Risk Category
"This area strongly focuses on the control of AI by means of mechanisms like laws, standards or norms that are already established for different technological applications. Here, there are some challenges special to AI that need to be addressed in the near future, including the governance of autonomous intelligence systems, responsibility and accountability for algorithms as well as privacy and data security."
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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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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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39.10.00 · Risk Category
HLI-based systems such as self-driving drones and vehicles will act autonomously in our world. In these systems, a challenging question is “who is liable when a self-driving system is involved in a crash or failure?”.
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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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"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."
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53.04.04 · Risk Sub-Category
Indirect AI contributions to existential risks
Erosion of international law and global governance architectures;
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"The complex and rapidly evolving nature of AI makes them inherently difficult to govern effectively, leading to systemic regulatory and oversight failures."
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"Once a model is deployed, it can be exposed to benchmark data provided by the users [95, 170]. The model may then be further trained by these user inputs containing benchmark data."
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"A metric selected to measure or track a risk is incorrectly selected, incompletely measuring the risk, or measuring the wrong risk for the given context."
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"EAI deployment could fundamentally reshape society, particularly if the speed of technological development outpaces society’s ability to adapt [103, 120]. For example, EAI systems could provide physical threats of violence and mass surveillance capabilities to back up AI-enabled authoritarianism [121]."
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03.06.00 · Risk Category
"At a time of increasing climate urgency, energy consumption and the carbon footprint of AI applications are also matters of ethics and responsibility [68]. As with other energy-intensive technologies like proof-of-work blockchain, the call is to research more environmentally sustainable algorithms to offset the increasing use scale."
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10.09.00 · Risk Category
"The production process of these devices requires raw materials such as nickel, cobalt, and lithium in such high quantities that the Earth may soon no longer be able to sustain them in sufficient quantities."
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depletion or contamination of natural resources, and damage to built environments... that may occur throughout the lifecycle of digital technologies [170, 237] from “crale (mining) to usage (consumption) to grave (waste)”
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"Impacts at a high-level, from the AI ecosystem to the Earth itself, are necessarily broad but can be broken down into components for evaluation."
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41.06.00 · Risk Category
"AI is already helping to combat the impact of climate change with smart technology and sensors reducing emissions. However, it is also a key component in the development of nanobots, which could have dangerous environmental impacts by invisibly modifying substances at nanoscale."
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41.06.01 · Risk Sub-Category
Accelerated development of nanotechnology produces uncontrolled production of toxic nanoparticles
"AI is a key component for the development of nanobots, which could have dangerous environmental implications by invisibly modifying substances at nanoscale. For example, nanobots could start chemical reactions that would create invisible nanoparticles that are toxic and potentially lethal."
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44.01.00 · Risk Category
"Many intentional harms, including confinement, husbandry procedures like tail-docking, and slaughter, are legal or socially accepted, while others such as wildlife trafficking and violence against companion animals are generally socially condemned and often illegal. AI can be designed or adopted by humans who harm animals to pursue their goals more effectively. We therefore distinguish AI-facilitated intentional harms that are currently socially accepted and generally legal, from uses and abuses of AI that cause harms that are not socially accepted and are often illegal."
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44.01.01 · Risk Sub-Category
Intentional: socially condemned/illegal
AI intentionally designed and used to harm animals in ways that contradict social values or are illegal
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44.01.02 · Risk Sub-Category
Intentional: socially condemned/illegal
AI designed to benefit animals, humans, or ecosystems is intentionally abused to harm animals in ways that contradict social values or are illegal
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44.02.00 · Risk Category
"AI designed to impact animals in harmful ways that reflect and amplify existing social values or are legal"
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44.03.02 · Risk Sub-Category
AI harms animals due to mistake or misadventure in the way the AI operates in practice
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44.04.00 · Risk Category
"AI impacts human or ecological systems in ways that ultimately harm animals"
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"AI proliferation causes harm to the environment through energy use and e-waste thereby destroying animal habitat"
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"Replacement by AI of human observation and interaction leads to neglect of certain interests"
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"Algorithmic recommender systems reinforce and amplify anthropocentric bias or desire of some people for animal cruelty as entertainment — leading to greater harm to animals through reinforcement of meat eating from factory farms, cruel uses of animals for entertainment, etc"
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56.03.00 · Risk Category
"Increasing use of AI systems, and their growing energy needs, could also have environmental impacts. All of these could become more acute as AI becomes more capable."
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58.09.00 · Risk Category
"Environmental - Damage to the environment directly or indirectly caused by a technology system or set of systems."
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"Pollution - Actual or potential pollution to the air, ground, noise, or water caused by a technology system."
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"The impact of AI on the environment, including risks related to climate change and pollution."
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"AI, and large generative models in particular, might produce increased carbon emissions and increase water usage for their training and operation."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.