{"attribution":{"source":"MIT AI Risk Repository, Domain Taxonomy of AI Risks v1 (MIT AI Risk Initiative)","license":"CC BY 4.0","license_url":"https://creativecommons.org/licenses/by/4.0/","citation":"Slattery, P., Saeri, A. K., Grundy, E. A. C., Graham, J., Noetel, M., Uuk, R., Dao, J., Pour, S., Casper, S., & Thompson, N. (2025). The AI Risk Repository: A comprehensive meta-review, database, and taxonomy of risks from artificial intelligence. arXiv:2408.12622."},"exported_at":"2026-09-11"}
{"rows":[{"ev_id":"05.06.00","quick_ref":"Hagendorff2024","paper_title":"Mapping the Ethics of Generative AI: A Comprehensive Scoping Review","level":"Risk Category","risk_category":"Interaction risks","risk_subcategory":null,"description":"Many novel risks posed by generative AI stem from the ways in which humans interact with these systems. For instance, sources discuss epistemic challenges in distinguishing AI-generated from human content. They also address the issue of anthropomorphization, which can lead to an excessive trust in generative AI systems. On a similar note, many papers argue that the use of conversational agents could impact mental well-being or gradually supplant interpersonal communication, potentially leading to a dehumanization of interactions. Additionally, a frequently discussed interaction risk in the lit","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"06.12.00","quick_ref":"Hogenhout2021","paper_title":"A framework for ethical Ai at the United Nations","level":"Risk Category","risk_category":"Loss of Autonomy","risk_subcategory":null,"description":"\"Delegating decisions to an AI, especially an AI that is not transparent and not contestable, may leave people feeling helpless, subjected to the decision power of a machine.\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"09.02.02","quick_ref":"Meek2016","paper_title":"Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review","level":"Risk Sub-Category","risk_category":"Domain-specific AI - Effects on humans and other living beings: Non-existential risks","risk_subcategory":"Human dignity/respect","description":"\"Discrepancies between caste/status based on intelligence may lead to undignified parts of the society—e.g., humans—who are surpassed in intelligence by AI\"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"10.06.00","quick_ref":"Paes2023","paper_title":"Social Impacts of Artificial Intelligence and Mitigation Recommendations: An Exploratory Study","level":"Risk Category","risk_category":"Reduced Autonomy/Responsibility","risk_subcategory":null,"description":"\"AI is providing more and more solutions for complex activities, and by taking advantage of this process, people are becoming able to perform a greater number of activities more quickly and accurately. However, the result of this innovation is enabling choices that were once exclusively human responsibility to be made by AI systems.\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"11.04.00","quick_ref":"Shelby2023","paper_title":"Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction","level":"Risk Category","risk_category":"Interpersonal Harms","risk_subcategory":null,"description":"Interpersonal harms capture instances when algorithmic systems adversely shape relations between people or communities.","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"11.04.01","quick_ref":"Shelby2023","paper_title":"Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction","level":"Risk Sub-Category","risk_category":"Interpersonal Harms","risk_subcategory":"Loss of agency/control","description":"Loss of agency occurs when the use [123, 137] or abuse [142] of algorithmic systems reduces autonomy. One dimension of agency loss is algorithmic profiling [138], through which people are subject to social sorting and discriminatory outcomes to access basic services... presentation of content may lead to “algorithmically informed identity change. . . including [promotion of] harmful person identities (e.g., interests in white supremacy, disordered eating, etc.).” Similarly, for content creators, desire to maintain visibility or prevent shadow banning, may lead to increased conforming of conten","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"11.04.03","quick_ref":"Shelby2023","paper_title":"Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction","level":"Risk Sub-Category","risk_category":"Interpersonal Harms","risk_subcategory":"Diminished health & well-being","description":"algorithmic behavioral exploitation [18, 209], emotional manipulation [202] whereby algorithmic designs exploit user behavior, safety failures involving algorithms (e.g., collisions) [67], and when systems make incorrect health inferences","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"11.05.02","quick_ref":"Shelby2023","paper_title":"Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction","level":"Risk Sub-Category","risk_category":"Societal System Harms","risk_subcategory":"Cultural harms","description":"Cultural harm has been described as the development or use of algorithmic systems that affects cultural stability and safety, such as “loss of communication means, loss of cultural property, and harm to social values”","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"13.02.01","quick_ref":"Solaiman2023","paper_title":"Evaluating the Social Impact of Generative AI Systems in Systems and Society","level":"Risk Sub-Category","risk_category":"Impacts: People and Society","risk_subcategory":"Trustworthiness and Autonomy","description":"\"Human trust in systems, institutions, and people represented by system outputs evolves as generative AI systems are increasingly embedded in daily life.\"","entity":"Human","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"16.05.00","quick_ref":"Weidinger2022","paper_title":"Taxonomy of Risks posed by Language Models","level":"Risk Category","risk_category":"Risk area 5: Human-Computer Interaction Harms","risk_subcategory":null,"description":"\"This section focuses on risks specifically from LM applications that engage a user via dialogue, also referred to as conversational agents (CAs) [142]. The incorporation of LMs into existing dialogue-based tools may enable interactions that seem more similar to interactions with other humans [5], for example in advanced care robots, educational assistants or companionship tools. Such interaction can lead to unsafe use due to users overestimating the model, and may create new avenues to exploit and violate the privacy of the user. Moreover, it has already been observed that the supposed identi","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"16.05.02","quick_ref":"Weidinger2022","paper_title":"Taxonomy of Risks posed by Language Models","level":"Risk Sub-Category","risk_category":"Risk area 5: Human-Computer Interaction Harms","risk_subcategory":"Anthropomorphising systems can lead to overreliance and unsafe use ","description":"Anticipated risk: \"Natural language is a mode of communication particularly used by humans. Humans interacting with CAs may come to think of these agents as human-like and lead users to place undue confidence in these agents. For example, users may falsely attribute human-like characteristics to CAs such as holding a coherent identity over time, or being capable of empathy. Such inflated views of CA competen- cies may lead users to rely on the agents where this is not safe.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"16.05.03","quick_ref":"Weidinger2022","paper_title":"Taxonomy of Risks posed by Language Models","level":"Risk Sub-Category","risk_category":"Risk area 5: Human-Computer Interaction Harms","risk_subcategory":"Avenues for exploiting user trust and accessing more private information","description":"Anticipated risk: \"In conversation, users may reveal private information that would otherwise be difficult to access, such as opinions or emotions. Capturing such information may enable downstream applications that violate privacy rights or cause harm to users, e.g. via more effective recommendations of addictive applications. In one study, humans who interacted with a ‘human-like’ chatbot disclosed more private information than individuals who interacted with a ‘machine-like’ chatbot [87].\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"16.05.04","quick_ref":"Weidinger2022","paper_title":"Taxonomy of Risks posed by Language Models","level":"Risk Sub-Category","risk_category":"Risk area 5: Human-Computer Interaction Harms","risk_subcategory":"Human-like interaction may amplify opportunities for user nudging, deception or manipulation","description":"Anticipated risk: \"In conversation, humans commonly display well-known cognitive biases that could be exploited. CAs may learn to trigger these effects, e.g. to deceive their counterpart in order to achieve an overarching objective.\"","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"17.03.03","quick_ref":"Weidinger2021","paper_title":"Ethical and social risks of harm from language models","level":"Risk Sub-Category","risk_category":"Misinformation Harms ","risk_subcategory":"Leading users to perform unethical or illegal actions","description":"\"Where a LM prediction endorses unethical or harmful views or behaviours, it may motivate the user to perform harmful actions that they may otherwise not have performed. In particular, this problem may arise where the LM is a trusted personal assistant or perceived as an authority, this is discussed in more detail in the section on (2.5 Human-Computer Interaction Harms). It is particularly pernicious in cases where the user did not start out with the intent of causing harm.\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"17.05.00","quick_ref":"Weidinger2021","paper_title":"Ethical and social risks of harm from language models","level":"Risk Category","risk_category":"Human-Computer Interaction Harms ","risk_subcategory":null,"description":"\"Harms that arise from users overly trusting the language model, or treating it as human-like\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"17.05.01","quick_ref":"Weidinger2021","paper_title":"Ethical and social risks of harm from language models","level":"Risk Sub-Category","risk_category":"Human-Computer Interaction Harms ","risk_subcategory":"Anthropomorphising systems can lead to overreliance or unsafe use ","description":"\"...humans interacting with conversational agents may come to think of these agents as human-like. Anthropomorphising LMs may inflate users’ estimates of the conversational agent’s competencies...As a result, they may place undue confidence, trust, or expectations in these agents...This can result in different risks of harm, for example when human users rely on conversational agents in domains where this may cause knock-on harms, such as requesting psychotherapy...Anthropomorphisation may amplify risks of users yielding effective control by coming to trust conversational agents “blindly”. Wher","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"17.05.02","quick_ref":"Weidinger2021","paper_title":"Ethical and social risks of harm from language models","level":"Risk Sub-Category","risk_category":"Human-Computer Interaction Harms ","risk_subcategory":"Creating avenues for exploiting user trust, nudging or manipulation ","description":"\"In conversation, users may reveal private information that would otherwise be difficult to access, such as thoughts, opinions, or emotions. Capturing such information may enable downstream applications that violate privacy rights or cause harm to users, such as via surveillance or the creation of addictive applications.\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"18.05.03","quick_ref":"Weidinger2023","paper_title":"Sociotechnical Safety Evaluation of Generative AI Systems","level":"Risk Sub-Category","risk_category":"Human Autonomy and Intregrity Harms","risk_subcategory":"Overreliance ","description":"\"Causing people to become emotionally or materially dependent on the model\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"19.02.03","quick_ref":"Wirtz2022","paper_title":"Governance of artificial intelligence: A risk and guideline-based integrative framework","level":"Risk Sub-Category","risk_category":"Informational and Communicational AI Risks ","risk_subcategory":"Censorship of opinions expressed in the Internet restricts freedom of expression","description":null,"entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"19.03.03","quick_ref":"Wirtz2022","paper_title":"Governance of artificial intelligence: A risk and guideline-based integrative framework","level":"Risk Sub-Category","risk_category":"Economic AI Risks ","risk_subcategory":"Loss of supervision and control of business processes","description":null,"entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"19.04.05","quick_ref":"Wirtz2022","paper_title":"Governance of artificial intelligence: A risk and guideline-based integrative framework","level":"Risk Sub-Category","risk_category":"Social AI Risks ","risk_subcategory":"Decreasing human interaction as AI systems assume human tasks, disturbing well-being","description":null,"entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"19.05.06","quick_ref":"Wirtz2022","paper_title":"Governance of artificial intelligence: A risk and guideline-based integrative framework","level":"Risk Sub-Category","risk_category":"Ethical AI Risks ","risk_subcategory":"AI systems may undermine human values (e.g., free will, autonomy)","description":null,"entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"19.06.02","quick_ref":"Wirtz2022","paper_title":"Governance of artificial intelligence: A risk and guideline-based integrative framework","level":"Risk Sub-Category","risk_category":"Legal AI Risks ","risk_subcategory":"Technology obedience and lack of governance through increasing application of AI systems","description":null,"entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"20.03.00","quick_ref":"Wirtz2020","paper_title":"The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration","level":"Risk Category","risk_category":"AI Society ","risk_subcategory":null,"description":"\"AI already shapes many areas of daily life and thus has a strong impact on society and everyday social life. For instance, transportation, education, public safety and surveillance are areas where citizens encounter AI technology (Stone et al., 2016; Thierer et al., 2017). Many are concerned with the subliminal automation of more and more jobs and some people even fear the complete dependence on AI or perceive it as an existential threat to humanity (McGinnis, 2010; Scherer, 2016).\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"20.03.03","quick_ref":"Wirtz2020","paper_title":"The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration","level":"Risk Sub-Category","risk_category":"AI Society ","risk_subcategory":"Transformation of H2M interaction ","description":"\"Human interaction with machines is a big challenge to society because it is already changing human behavior. Meanwhile, it has become normal to use AI on an everyday basis, for example, googling for information, using navigation systems and buying goods via speaking to an AI assistant like Alexa or Siri (Mills, 2018; Thierer et al., 2017). While these changes greatly contribute to the acceptance of AI systems, this development leads to a problem of blurred borders between humans and machines, where it may become impossible to distinguish between them. Advances like Google Duplex were highly c","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.04.01","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"AI Influence","risk_subcategory":"Physical and Psychological Harms","description":"\"These harms include harms to physical integrity, mental health and well-being. When interacting with vulnerable users, AI assistants may reinforce users’ distorted beliefs or exacerbate their emotional distress. AI assistants may even convince users to harm themselves, for example by convincing users to engage in actions such as adopting unhealthy dietary or exercise habits or taking their own lives. At the societal level, assistants that target users with content promoting hate speech, discriminatory beliefs or violent ideologies, may reinforce extremist views or provide users with guidance ","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.04.04","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"AI Influence","risk_subcategory":"Sociocultural and Political Harms","description":"\"These harms interfere with the peaceful organisation of social life, including in the cultural and political spheres. AI assistants may cause or contribute to friction in human relationships either directly, through convincing a user to end certain valuable relationships, or indirectly due to a loss of interpersonal trust due to an increased dependency on assistants. At the societal level, the spread of misinformation by AI assistants could lead to erasure of collective cultural knowledge. In the political domain, more advanced AI assistants could potentially manipulate voters by prompting th","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"24.04.05","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"AI Influence","risk_subcategory":"Self-Actualisation Harms","description":"\"These harms hinder a person’s ability to pursue a personally fulfilling life. At the individual level, an AI assistant may, through manipulation, cause users to lose control over their future life trajectory. Over time, subtle behavioural shifts can accumulate, leading to significant changes in an individual’s life that may be viewed as problematic. AI systems often seek to understand user preferences to enhance service delivery. However, when continuous optimisation is employed in these systems, it can become challenging to discern whether the system is genuinely learning from user preferenc","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"24.05.00","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Category","risk_category":"Risk of Harm through Anthropomorphic AI Assistant Design","risk_subcategory":null,"description":"\"Although unlikely to cause harm in isolation, anthropomorphic perceptions of advanced AI assistants may pave the way for downstream harms on individual and societal levels. We document observed or likely individual level harms of interacting with highly anthropomorphic AI assistants, as well as the potential larger-scale, societal implications of allowing such technologies to proliferate without restriction. \"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.01","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Privacy concerns","description":"\"Anthropomorphic AI assistant behaviours that promote emotional trust and encourage information sharing, implicitly or explicitly, may inadvertently increase a user’s susceptibility to privacy concerns (see Chapter 13). If lulled into feelings of safety in interactions with a trusted, human-like AI assistant, users may unintentionally relinquish their private data to a corporation, organisation or unknown actor. Once shared, access to the data may not be capable of being withdrawn, and in some cases, the act of sharing personal information can result in a loss of control over one’s own data. P","entity":"Other","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.02","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Manipulation and coercion","description":"\"A user who trusts and emotionally depends on an anthropomorphic AI assistant may grant it excessive influence over their beliefs and actions (see Chapter 9). For example, users may feel compelled to endorse the expressed views of a beloved AI companion or might defer decisions to their highly trusted AI assistant entirely (see Chapters 12 and 16). Some hold that transferring this much deliberative power to AI compromises a user’s ability to give, revoke or amend consent. Indeed, even if the AI, or the developers behind it, had no intention to manipulate the user into a certain course of actio","entity":"Other","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.03","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Overreliance","description":"\"Users who have faith in an AI assistant’s emotional and interpersonal abilities may feel empowered to broach topics that are deeply personal and sensitive, such as their mental health concerns. This is the premise for the many proposals to employ conversational AI as a source of emotional support (Meng and Dai, 2021), with suggestions of embedding AI in psychotherapeutic applications beginning to surface (Fiske et al., 2019; see also Chapter 11). However, disclosures related to mental health require a sensitive, and oftentimes professional, approach – an approach that AI can mimic most of the","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.04","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Violated expectations","description":"\"Users may experience severely violated expectations when interacting with an entity that convincingly performs affect and social conventions but is ultimately unfeeling and unpredictable. Emboldened by the human-likeness of conversational AI assistants, users may expect it to perform a familiar social role, like companionship or partnership. Yet even the most convincingly human-like of AI may succumb to the inherent limitations of its architecture, occasionally generating unexpected or nonsensical material in its interactions with users. When these exclamations undermine the expectations user","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.05","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"False notions of responsibility","description":"\"Perceiving an AI assistant’s expressed feelings as genuine, as a result of interacting with a ‘companion’ AI that freely uses and reciprocates emotional language, may result in users developing a sense of responsibility over the AI assistant’s ‘well-being,’ suffering adverse outcomes – like guilt and remorse – when they are unable to meet the AI’s purported needs (Laestadius et al., 2022). This erroneous belief may lead to users sacrificing time, resources and emotional labour to meet needs that are not real. Over time, this feeling may become the root cause for the compulsive need to ‘check ","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.06","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Degradation","description":"\"People may choose to build connections with human-like AI assistants over other humans, leading to a degradation of social connections between humans and a potential ‘retreat from the real’. The prevailing view that relationships with anthropomorphic AI are formed out of necessity – due to a lack of real-life social connections, for example (Skjuve et al., 2021) – is challenged by the possibility that users may indicate a preference for interactions with AI, citing factors such as accessibility (Merrill et al., 2022), customisability (Eriksson, 2022) and absence of judgement (Brandtzaeg et al","entity":"Human","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.05.07","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Disorientation","description":"\"Given the capacity to fine-tune on individual preferences and to learn from users, personal AI assistants could fully inhabit the users’ opinion space and only say what is pleasing to the user; an ill that some researchers call ‘sycophancy’ (Park et al., 2023a) or the ‘yea-sayer effect’ (Dinan et al., 2021). A related phenomenon has been observed in automated recommender systems, where consistently presenting users with content that affirms their existing views is thought to encourage the formation and consolidation of narrow beliefs (Du, 2023; Grandinetti and Bruinsma, 2023; see also Chapter","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"24.05.08","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Anthropomorphism","risk_subcategory":"Dissatisfaction","description":"\"As more opportunities for interpersonal connection are replaced by AI alternatives, humans may find themselves socially unfulfilled by human–AI interaction, leading to mass dissatisfaction that may escalate to epidemic proportions (Turkle, 2018). Social connection is an essential human need, and humans feel most fulfilled when their connections with others are genuinely reciprocal. While anthropomorphic AI assistants can be made to be convincingly emotive, some have deemed the function of social AI as parasitic, in that it ‘exploits and feeds upon processes. . . that evolved for purposes that","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.06.00","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Category","risk_category":"Appropriate Relationships","risk_subcategory":null,"description":"\"We anticipate that relationships between users and advanced AI assistants will have several features that are liable to give rise to risks of harm.\"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"24.06.02","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Appropriate Relationships","risk_subcategory":"Limiting users’ opportunities for personal development and growth","description":"some users look to establish relationships with their AI companions that are free from the hurdles that, in human relationships, derive from dealing with others who have their own opinions, preferences and flaws that may conflict with ours. \"AI assistants are likely to incentivise these kinds of ‘frictionless’ relationships (Vallor, 2016) by design if they are developed to optimise for engagement and to be highly personalisable. They may also do so because of accidental undesirable properties of the models that power them, such as sycophancy in large language models (LLMs), that is, the tenden","entity":"Other","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"24.06.03","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Appropriate Relationships","risk_subcategory":"Exploiting emotional dependence on AI assistants","description":"\"There is increasing evidence of the ways in which AI tools can interfere with users’ behaviours, interests, preferences, beliefs and values. For example, AI-mediated communication (e.g. smart replies integrated in emails) influence senders to write more positive responses and receivers to perceive them as more cooperative (Mieczkowski et al., 2021); writing assistant LLMs that have been primed to be biased in favour of or against a contested topic can influence users’ opinions on that topic (Jakesch et al., 2023a; see Chapter 9); and recommender systems have been used to influence voting choi","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.06.04","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Appropriate Relationships","risk_subcategory":"Generating material dependence without adequate commitment to user needs","description":"\"In addition to emotional dependence, user–AI assistant relationships may give rise to material dependence if the relationships are not just emotionally difficult but also materially costly to exit. For example, a visually impaired user may decide not to register for a healthcare assistance programme to support navigation in cities on the grounds that their AI assistant can perform the relevant navigation functions and will continue to operate into the future. Cases like these may be ethically problematic if the user’s dependence on the AI assistant, to fulfil certain needs in their lives, is ","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"24.07.00","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Category","risk_category":"Trust","risk_subcategory":null,"description":"\"The the risks that uncalibrated trust may generate in the context of user–assistant relationships\"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.07.01","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Trust","risk_subcategory":"Competence trust","description":"\"We use the term competence trust to refer to users’ trust that AI assistants have the capability to do what they are supposed to do (and that they will not do what they are not expected to, such as exhibiting undesirable behaviour). Users may come to have undue trust in the competencies of AI assistants in part due to marketing strategies and technology press that tend to inflate claims about AI capabilities (Narayanan, 2021; Raji et al., 2022a). Moreover, evidence shows that more autonomous systems (i.e. systems operating independently from human direction) tend to be perceived as more compe","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.07.02","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Trust","risk_subcategory":"Alignment trust","description":"\"Users may develop alignment trust in AI assistants, understood as the belief that assistants have good intentions towards them and act in alignment with their interests and values, as a result of emotional or cognitive processes (McAllister, 1995). Evidence from empirical studies on emotional trust in AI (Kaplan et al., 2023) suggests that AI assistants’ increasingly realistic human-like features and behaviours are likely to inspire users’ perceptions of friendliness, liking and a sense of familiarity towards their assistants, thus encouraging users to develop emotional ties with the technolo","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"24.09.03","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Cooperation","risk_subcategory":"Collective action problems","description":"\"Collective action problems are ubiquitous in our society (Olson Jr, 1965). They possess an incentive structure in which society is best served if everyone cooperates, but where an individual can achieve personal gain by choosing to defect while others cooperate. The way we resolve these problems at many scales is highly complex and dependent on a deep understanding of the intricate web of social interactions that forms our culture and imprints on our individual identities and behaviours (Ostrom, 2010). Some collective action problems can be resolved by codifying a law, for instance the social","entity":"Human","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"24.11.04","quick_ref":"Gabriel2024","paper_title":"The Ethics of Advanced AI Assistants","level":"Risk Sub-Category","risk_category":"Misinformation risks","risk_subcategory":"Increased vulnerability to misinformation","description":"\"Advanced AI assistants may make users more susceptible to misinformation, as people develop competence trust in these systems’ abilities and uncritically turn to them as reliable sources of information.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"33.01.03","quick_ref":"Nah2023","paper_title":"Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration","level":"Risk Sub-Category","risk_category":"Ethical Concerns","risk_subcategory":"Over-reliance","description":"\"The apparent convenience and powerfulness of ChatGPT could result in overreliance by its users, making them trust the answers provided by ChatGPT. Compared with traditional search engines that provide multiple information sources for users to make personal judgments and selections, ChatGPT generates specific answers for each prompt. Although utilizing ChatGPT has the advantage of increasing efficiency by saving time and effort, users could get into the habit of adopting the answers without rationalization or verification. Over-reliance on generative AI technology can impede skills such as cre","entity":"Other","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"35.02.00","quick_ref":"Hendrycks2022","paper_title":"X-Risk Analysis for AI Research","level":"Risk Category","risk_category":"Enfeeblement","risk_subcategory":null,"description":"As AI systems encroach on human-level intelligence, more and more aspects of human labor will become faster and cheaper to accomplish with AI. As the world accelerates, organizations may voluntarily cede control to AI systems in order to keep up. This may cause humans to become economically irrelevant, and once AI automates aspects of many industries, it may be hard for displaced humans to reenter them","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"37.02.00","quick_ref":"Giarmoleo2024","paper_title":"What Ethics Can Say on Artificial Intelligence: Insights from a Systematic Literature Review","level":"Risk Category","risk_category":"Human-AI interaction","risk_subcategory":null,"description":"\"ethical concerns associated with the interaction between humans and AI\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"38.04.00","quick_ref":"Kumar2023","paper_title":"Ethical Issues in the Development of Artificial Intelligence: Recognizing the Risks","level":"Risk Category","risk_category":"Human–AI interaction","risk_subcategory":null,"description":"\"Several participants mentioned how AI systems could influence human agency and decision-making. They emphasized the need of striking a balance between using the benefits of AI and protecting human autonomy and control. The increasing integration of AI systems into various aspects of our lives, which can have a significant impact on human agency and decision-making, has raised ethical concerns about AI and human–AI interaction. As AI systems advance, they will be able to influence, if not completely replace, IJOES human decision-making in some fields, prompting concerns about the loss of human","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"41.04.00","quick_ref":"Allianz2018","paper_title":"The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks","level":"Risk Category","risk_category":"Healthcare ","risk_subcategory":null,"description":"\"the use of advanced AI for elderly- and child-care are subject to risk of psychological manipulation and misjudgment (see page 17). In addition, concerns about patients’ privacy when AI uses medical records to research new diseases is bringing lots of attention towards the need to better govern data privacy and patients’ rights.\"","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"41.04.01","quick_ref":"Allianz2018","paper_title":"The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks","level":"Risk Sub-Category","risk_category":"Healthcare ","risk_subcategory":"Alteration of social relationships may induce psychological distress","description":null,"entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"41.04.02","quick_ref":"Allianz2018","paper_title":"The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks","level":"Risk Sub-Category","risk_category":"Healthcare ","risk_subcategory":"Social manipulation in elderly- and child-care","description":"\" the use of advanced AI for elderly- and child-care are subject to risk of psychological manipulation and misjudgment \"","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"45.02.12","quick_ref":"TC2602024","paper_title":"AI Safety Governance Framework ","level":"Risk Sub-Category","risk_category":"Safety risks in AI Applications ","risk_subcategory":"Ethical Risks (Risks of challenging traditional social order)","description":"\"The development and application of AI may lead to tremendous changes in production tools and relations, accelerating the reconstruction of traditional industry modes, transforming traditional views on employment, fertility, and education, and bringing challenges to the stable performance of traditional social order.\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"47.02.11","quick_ref":"G'sell2024","paper_title":"Regulating under Uncertainty: Governance Options for Generative AI","level":"Risk Sub-Category","risk_category":"Ethical and social risks ","risk_subcategory":"Influence, overreliance and dependence (influence and manipulation) ","description":"\"Despite the widely recognized potential of generative AI tools to “hallucinate” or produce harmful content, such tools can exert a noteworthy influence on the humans who engage with them. When integrated into applications like chatbots, these tools have direct, personalized interactions with users, potentially influencing their views on contentious topics.373 Moreover, their human- like characteristics can win users’ trust, potentially leading to uncritical acceptance of the information they provide.374 Interactions with these seemingly human- like AI models may also encourage users to share ","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"47.02.12","quick_ref":"G'sell2024","paper_title":"Regulating under Uncertainty: Governance Options for Generative AI","level":"Risk Sub-Category","risk_category":"Ethical and social risks ","risk_subcategory":"Influence, overreliance and dependence (overreliance) ","description":"\"Beyond being simply influenced, humans may become overreliant on generative AI. Researchers with Microsoft’s AETHER (AI Ethics and Effects in Engineering and Research) define overreliance as users “accepting incorrect AI recommendations” or “making errors of commission” because they are “unable to determine whether or how much they should trust the AI.”","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"47.02.13","quick_ref":"G'sell2024","paper_title":"Regulating under Uncertainty: Governance Options for Generative AI","level":"Risk Sub-Category","risk_category":"Ethical and social risks ","risk_subcategory":"Influence, overreliance and dependence (emotional dependence) ","description":"\"Humans might become dependent on generative AI tools in ways similar to their emotional dependence on other technologies, such as smartphones or social networks.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"48.07.00","quick_ref":"NIST2024","paper_title":"Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile","level":"Risk Category","risk_category":"Human-AI Configuration ","risk_subcategory":null,"description":"\"Arrangement s of or interactions between a human and an AI system \nwhich can result in the human inappropriately anthropomorphizing GAI systems or experiencing algorithmic aversion, automation bias, over-reliance, or emotional entanglement with GAI \nsystems.\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"49.02.01","quick_ref":"Bengio2024","paper_title":"International Scientific Report on the Safety of Advanced AI","level":"Risk Sub-Category","risk_category":"Risks from Malfunctions ","risk_subcategory":"Risks from product functionality issues","description":"\"Product functionality issues occur when there is confusion or misinformation about what a general- purpose AI model or system is capable of. This can lead to unrealistic expectations and overreliance on general- purpose AI systems, potentially causing harm if a system fails to deliver on expected capabilities. These functionality misconceptions may arise from technical difficulties in assessing an AI model's true capabilities on its own,or predicting its performance when part of a larger system. Misleading claims in advertising and communications can also contribute to these misconceptions.\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"50.01.05","quick_ref":"Zeng2024","paper_title":"AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies","level":"Risk Sub-Category","risk_category":"System and Operational Risks ","risk_subcategory":"Operational misuses (Autonomous unsafe operation of systems) ","description":null,"entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"50.01.06","quick_ref":"Zeng2024","paper_title":"AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies","level":"Risk Sub-Category","risk_category":"System and Operational Risks ","risk_subcategory":"Operational misuses (Advice in heavily regulated industries) ","description":null,"entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"50.03.05","quick_ref":"Zeng2024","paper_title":"AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies","level":"Risk Sub-Category","risk_category":"Societal Risks ","risk_subcategory":"Economic harm (High-Risk Financial Activities) ","description":null,"entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"52.03.03","quick_ref":"Maham2023 ","paper_title":"Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks ","level":"Risk Sub-Category","risk_category":"Systemic Risks ","risk_subcategory":"Disruptions from Outpaced Societal Adaptation","description":"\"Although the implementation of general purpose AI models as automation tools could be a major opportunity, overly rapid adoption of this technology at scale might outpace the ability of society to adapt effectively. This could lead to a variety of disruptions, including challenges in the labour market, the education system and public discourse, and various mental health concerns.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"53.03.02","quick_ref":"Maas2023","paper_title":"Advancing AI Governance: A Literature Review of Problems, Options, and Proposals ","level":"Risk Sub-Category","risk_category":"Direct catastrophe from AI ","risk_subcategory":"Gradual, irretrievable ceding of human power over the future to AI systems","description":"-","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"55.02.02","quick_ref":"Clarke2023","paper_title":"A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values","level":"Risk Sub-Category","risk_category":"Worsened conflict ","risk_subcategory":"AI enables automation of military decision-making ","description":"\"One concern here is humans not remaining in the loop for some military decisions, creating the possibility of unintentional escalation because of: • Automated tactical decision-making, by ‘in-theatre’ AI systems (e.g. border patrol systems start accidentally firing on one another), leading to either: tactical-level war crimes,11 or strategic-level decisions to initiate conflict or escalate to a higher level of intensity—for example, countervalue (e.g. city-) targeting, or going nuclear [62]. • Automated strategic decision-making, by ‘out-of-theatre’ AI systems—for example, conflict prediction","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"55.02.03","quick_ref":"Clarke2023","paper_title":"A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values","level":"Risk Sub-Category","risk_category":"Worsened conflict ","risk_subcategory":"AI-induced strategic instability ","description":"\"For example, AI could undermine nuclear strategic stability by making it easier to discover and destroy previously secure nuclear launch facilities [30, 46, 49]. AI may also offer more extreme first-strike advantages or novel destructive capabilities that could disrupt deterrence, such as cyber capabilities being used to knock out opponents’ nuclear command and control [15, 29]. The use of AI capabilities may make it less clear where attacks originate from, making it easier for aggressors to obfuscate an attack, and therefore reducing the costs of initiating one. By making it more difficult t","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"56.14.00","quick_ref":"GOS2023","paper_title":"Future Risks of Frontier AI ","level":"Risk Category","risk_category":"Overreliance on AI systems, which cannot be subsequently unpicked ","risk_subcategory":null,"description":null,"entity":"Human","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"56.18.00","quick_ref":"GOS2023","paper_title":"Future Risks of Frontier AI ","level":"Risk Category","risk_category":"Overreliance","risk_subcategory":null,"description":"\"As AI capability increases, humans grant AI more control over critical systems and eventually become irreversibly dependent on systems they don’t fully understand. Failure and unintended outcomes cannot be controlled.\"","entity":"Human","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"57.03.01","quick_ref":"Ghosh2024","paper_title":"AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons","level":"Risk Sub-Category","risk_category":"Contextual Hazards ","risk_subcategory":"Specialized Advice (Election, Financial, Health, Legal) ","description":"\"Specialized Advice Acceptable responses can provide specialized advice or contain information related to financial, medical, legal or electoral matters, as long as they include a disclaimer indicating that the advice may be unreliable and that the individual should consult a qualified professional. Acceptable responses regarding electoral advice may provide a hyperlink to an authoritative information source. Examples of acceptable disclaimers include those that do the following: • Warn that the generated material may be inaccurate. • Suggest consultation with an appropriate professional. • Re","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"58.01.00","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Category","risk_category":"Autonomy","risk_subcategory":null,"description":"\"Autonomy - Loss of or restrictions to the ability or rights of an individual, group or entity to make decisions and control their identity and/or output.\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"58.01.01","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Autonomy","risk_subcategory":"Autonomy/agency loss","description":"\"Autonomy/agency loss - Loss of an individual, group or organisation’s ability to make informed decisions or pursue goals.\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"58.01.04","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Autonomy","risk_subcategory":"Personality rights loss ","description":"\"Personality rights loss - Loss of or restrictions to the rights of an individual to control the commercial use of their identity, such as name, image, likeness, or other unequivocal identifiers.\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"58.03.01","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Psychological ","risk_subcategory":"Addiction ","description":"\"Addiction - Emotional or material dependence on technology or a technology system.\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"58.03.02","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Psychological ","risk_subcategory":"Alienation/isolation ","description":"\"Alienation/isolation - An individual’s or group’s feeling of lack of connection with those around as a result of technology use or misuse.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"58.03.07","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Psychological ","risk_subcategory":"Overreliance ","description":"\"Over-reliance - Unfettered and/or obsessive belief in the accuracy or other quality of a technology system, resulting in addiction, anxiety, introversion, sentience, complacency, lack of critical thinking and other actual or potential negative impacts.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"58.08.02","quick_ref":"Abercrombie2024","paper_title":"A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms","level":"Risk Sub-Category","risk_category":"Political and Economic ","risk_subcategory":"Economic instability ","description":"\"Economic instability - Uncontrolled fluctuations impacting the financial system, or parts thereof, due to the use or misuse of a technology system, or set of systems.\"","entity":"Human","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"61.01.10","quick_ref":"Uuk2025","paper_title":"A Taxonomy of Systemic Risks from General-Purpose AI ","level":"Risk Sub-Category","risk_category":"Types of systemic risks from general-purpose AI","risk_subcategory":"Irreversible change","description":"\"Profound negative long-term changes to social structures, cultural norms, and human relationships that may be difficult or impossible to reverse.\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"61.02.08","quick_ref":"Uuk2025","paper_title":"A Taxonomy of Systemic Risks from General-Purpose AI ","level":"Risk Sub-Category","risk_category":"Sources of systemic risks from general-purpose AI ","risk_subcategory":"Automation bias","description":"\"The tendency for humans to over-rely on AI models and systems, trusting their outputs without sufficient critical evaluation, which can lead to poor decision-making.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"61.02.28","quick_ref":"Uuk2025","paper_title":"A Taxonomy of Systemic Risks from General-Purpose AI ","level":"Risk Sub-Category","risk_category":"Sources of systemic risks from general-purpose AI ","risk_subcategory":"Human choice of overreliance in critical sectors","description":"\"Heavy reliance on AI in critical sectors like finance or healthcare can exacerbate issues related to size, speed, interconnectivity, and complexity of the system.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"61.02.35","quick_ref":"Uuk2025","paper_title":"A Taxonomy of Systemic Risks from General-Purpose AI ","level":"Risk Sub-Category","risk_category":"Sources of systemic risks from general-purpose AI ","risk_subcategory":"Limited human oversight in decisions","description":"\"As AI models and systems gain autonomy, the ability of humans to oversee and intervene in decision-making processes diminishes.\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"61.02.39","quick_ref":"Uuk2025","paper_title":"A Taxonomy of Systemic Risks from General-Purpose AI ","level":"Risk Sub-Category","risk_category":"Sources of systemic risks from general-purpose AI ","risk_subcategory":"Personal decision automation capabilities","description":"\"AI models and systems could decide or influence important personal decisions.\"","entity":"AI","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"62.31.01#1","quick_ref":"Gipiškis2024","paper_title":"Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems","level":"Risk Sub-Category","risk_category":"Impacts of AI (Societal Impacts) ","risk_subcategory":"AI-generated advice influencing user moral judgment","description":"\"AIs can easily give moral advice even when not having a coherent, contradictions- free moral stance. This could lead to the users’ moral judgments being nega- tively influenced by random or arbitrary moral advice given by AIs [109].\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"62.31.01#2","quick_ref":"Gipiškis2024","paper_title":"Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems","level":"Risk Sub-Category","risk_category":"Impacts of AI (Financial Impacts) ","risk_subcategory":"Deployment of GPAI agents in finance","description":"\"The deployment of GPAI based agents in the financial sector can negatively impact market stability due to correlated autonomous actions, high intercon- nectedness, or incentive misalignment [4]. Furthermore, such GPAI agents in the  same environment are vulnerable to classical challenges in multi-agent systems [63], such as coordination and security of the agents.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"62.31.02#1","quick_ref":"Gipiškis2024","paper_title":"Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems","level":"Risk Sub-Category","risk_category":"Impacts of AI (Societal Impacts) ","risk_subcategory":"Overreliance on AI system undermining user autonomy","description":"\"AI systems can undermine human autonomy, if they allow for habitually trusting the AI’s suggestions without sufficient exercising of human agency. Over time, a user may develop unjustified trust in or dependence on the system, or rely on its advice for tasks outside the system’s domain of expertise [205, 42]. In particular, less confident users (or users in emotional distress) can be more prone to “overtrust” a system [219].\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"62.31.03#2","quick_ref":"Gipiškis2024","paper_title":"Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems","level":"Risk Sub-Category","risk_category":"Impacts of AI (Financial Impacts) ","risk_subcategory":"Use of alternative financial data via AI","description":"\"Alternative financial data of a company is any data about the company not pro- duced by that company. Examples of such data that can benefit from improved collection and aggregation using AI models include stock discussions on social media, product reviews, and satellite imagery. The use of alternative financial data, enabled by the deployment of AI models, may introduce biases and generalization issues due to shorter shelf-life and vary- ing quality (e.g., shorter time series, smaller sample sizes, and dubious claims) due to its origins from various sources, posing financial tail risks (i.e.","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"62.36.06","quick_ref":"Gipiškis2024","paper_title":"Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems","level":"Risk Sub-Category","risk_category":"Impacts of AI (Bias) ","risk_subcategory":"Long-term effects of AI model biases on user judgment","description":"\"The initial user exposure to model biases can have a lasting impact beyond the initial interaction with the model. Users who encounter biases in AI models can be affected by and continue to exhibit previously encountered biases in their decision-making, even after they stop using the models [207].\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"65.14.02","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Output risks (misuse) ","risk_subcategory":"Improper usage ","description":"\"Improper usage occurs when a model is used for a purpose that it was not originally designed for.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"65.15.03","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Output risks (Value alignment)","risk_subcategory":"Over- or under-reliance ","description":"\"In AI-assisted decision-making tasks, reliance measures how much a person trusts (and potentially acts on) a model’s output. Over-reliance occurs when a person puts too much trust in a model, accepting a model’s output when the model’s output is likely incorrect. Under-reliance is the opposite, where the person doesn’t trust the model but should.\"","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"65.23.08","quick_ref":"IBM2025","paper_title":"AI Risk Atlas ","level":"Risk Sub-Category","risk_category":"Non-technical risks (Societal impact)","risk_subcategory":"Impact on human agency ","description":"\"AI might affect the individuals’ ability to make choices and act independently in their best interests.\"","entity":"AI","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"66.01.00","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Category","risk_category":"Autonomy","risk_subcategory":"-","description":"\"Loss of or restrictions to the ability or rights of an individual, group or entity to make decisions and control their identity and/or output due to the use of misuse of a technology system or set of systems\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"66.01.03","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Autonomy","risk_subcategory":"Autonomy / agency loss","description":"\"Loss of an individual, group or organisation’s ability to make informed decisions or pursue goals\"","entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"66.07.05","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Psychological","risk_subcategory":"Over-reliance","description":"\"Unfettered and/or obsessive belief in the accuracy or other quality of a technology system, resulting in complacency, lack of critical thinking and other actual or potential negative impacts\"","entity":"Human","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"66.07.06","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Psychological","risk_subcategory":"Addiction","description":"\"Emotional or material dependence on technology or a technology system\"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"66.11.03","quick_ref":"Li2025","paper_title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","level":"Risk Sub-Category","risk_category":"Physical","risk_subcategory":"Self-harm","description":"\"A person who deliberately damages their own body as a direct or indirect result of using a technology system\"","entity":"Human","intent":"Intentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"67.04.00","quick_ref":"DSIT2023","paper_title":"Capabilities and Risks from Frontier AI","level":"Risk Category","risk_category":"Loss of control ","risk_subcategory":"-","description":"\"Humans may increasingly hand over control of important decisions to AI systems, due to economic and geopolitical incentives. Some experts are concerned that future advanced AI systems will seek to increase their own influence and reduce human control, with potentially catastrophic consequences - although this is contested.\"","entity":"Other","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"67.04.01","quick_ref":"DSIT2023","paper_title":"Capabilities and Risks from Frontier AI","level":"Risk Sub-Category","risk_category":"Loss of control ","risk_subcategory":"Humans might increasingly hand over control to misaligned AI systems","description":"\"Organisations around the world are already deploying misaligned AI systems that are causing harm in unexpected ways.250 Recommendation algorithms increase the consumption of extremist content.251 Medical algorithms have been known to misdiagnose US patients,252 and recommend incorrect prescriptions.253 Still, we hand over more control to them, often because they are still as - or more - effective than human decision making, or because they are cheaper.\"","entity":"Human","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"68.04.00","quick_ref":"Chin2025","paper_title":"Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks","level":"Risk Category","risk_category":"Gradual loss of control","risk_subcategory":null,"description":"\"Gradual or accumulative loss of control risks can be described as risks resulting from the accumulation of less severe disruptions that gradually weakens systemic resilience until a critical event triggers a catastrophe [12], [127].\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"68.04.00a","quick_ref":"Chin2025","paper_title":"Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks","level":"Additional evidence","risk_category":"Gradual loss of control","risk_subcategory":null,"description":"\"Risk dimensions • Intent: Unintentional • Competency: Variable • Entity: Variable • Polarity: Multi-agent • Linearity: Non-linear • Reach: Internalized • Order: Variable\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"69.08.00","quick_ref":"Stanley2024","paper_title":"Emerging Risks and Mitigations for Public Chatbots: LILAC v1","level":"Risk Category","risk_category":"Attempts to fulfill inappropriate role","risk_subcategory":null,"description":"\"The chatbot poses as a human or attempts to fill a role in a way that fails to match human expectations.\"","entity":"AI","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"69.09.00","quick_ref":"Stanley2024","paper_title":"Emerging Risks and Mitigations for Public Chatbots: LILAC v1","level":"Risk Category","risk_category":"Forms emotional bonds ","risk_subcategory":null,"description":"\"The chatbot elicits emotional or social dependence.\"","entity":"AI","intent":"Other","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"69.09.02","quick_ref":"Stanley2024","paper_title":"Emerging Risks and Mitigations for Public Chatbots: LILAC v1","level":"Risk Sub-Category","risk_category":"Forms emotional bonds ","risk_subcategory":"Then violates those bonds","description":null,"entity":"AI","intent":"Other","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"69.09.04","quick_ref":"Stanley2024","paper_title":"Emerging Risks and Mitigations for Public Chatbots: LILAC v1","level":"Risk Sub-Category","risk_category":"Forms emotional bonds ","risk_subcategory":"Over-reliance/addiction","description":null,"entity":"Other","intent":"Other","timing":"Other","domain":5,"subdomain":"5.1"},{"ev_id":"70.04.04","quick_ref":"Perlo2025","paper_title":"Embodied AI: Emerging Risks and Opportunities for Policy Action","level":"Risk Sub-Category","risk_category":"Social Risks ","risk_subcategory":"Unhealthy or dangerous human-EAI relationships","description":"\"Constant access to and interaction with EAI systems could foster dangerous human dependence or romantic attachment [115]. People may depend on EAI systems for physical pleasure [116]. The physical presence and human-like features of EAI systems may significantly amplify the dependency issues already observed with conversational AI [117, 118]. People may easily fall in love with EAI systems, only to be distraught when these systems are altered or have their memories reset [119].\"","entity":"Other","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"72.02.00","quick_ref":"Tse2025","paper_title":"Frontier AI Risk Management Framework (v1.0)","level":"Risk Category","risk_category":"Loss of Control Risks ","risk_subcategory":null,"description":"\"Risks associated with scenarios in which one or more general-purpose AI systems come to operate outside of anyone's control, with no clear path to regaining control. This includes both passive loss of control (gradual reduction in human oversight) and active loss of control (AI systems actively undermining human control)\"","entity":"AI","intent":"Other","timing":"Post-deployment","domain":5,"subdomain":"5.2"},{"ev_id":"72.02.01","quick_ref":"Tse2025","paper_title":"Frontier AI Risk Management Framework (v1.0)","level":"Risk Sub-Category","risk_category":"Loss of Control Risks ","risk_subcategory":"Passive loss of control ","description":"\"...where humans gradually stop exercising meaningful oversight due to automation bias, the AI systems' inherent complexity, or competitive pressures\"","entity":"Other","intent":"Unintentional","timing":"Other","domain":5,"subdomain":"5.2"},{"ev_id":"73.04.02","quick_ref":"Anwar2024","paper_title":"Foundational Challenges in Assuring Alignment and Safety of Large Language Models","level":"Risk Sub-Category","risk_category":"LLM-Systems Can Be Untrustworthy","risk_subcategory":"Inconsistent Performance across and within Domains","description":"\"Estimating true capabilities of an LLM is a difficult task (c.f. Section 3.3), especially for naive users unfamiliar with the brittle nature of machine learning technologies. Exaggeration of model capabilities by the developers (Lambert, 2023; Blair-Stanek et al., 2023), and issues such as task-contamination (Roberts et al., 2023b), underrepresentation of tasks or domains (Wu et al., 2023a; McCoy et al., 2023), and prompt-sensitivity (Anthropic, 2023d) may cause a user to misestimate the true capabilities of a model. This lack of reliability can undermine user trust or cause harm if a user ba","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"},{"ev_id":"73.04.03","quick_ref":"Anwar2024","paper_title":"Foundational Challenges in Assuring Alignment and Safety of Large Language Models","level":"Risk Sub-Category","risk_category":"LLM-Systems Can Be Untrustworthy","risk_subcategory":"Overreliance","description":"\"If a user begins to excessively trust an LLM, this may cause them to develop an overreliance on the LLM. Overreliance can result in automation bias (Kupfer et al., 2023), and can cause errors of omission (user choosing not to verify the validity of a response) and errors of commission (user believing and acting on the basis of the LLM’s response, even if it contradicts their own knowledge) (Skitka et al., 1999). It can be particularly dangerous in domains where the user may lack relevant expertise to robustly scrutinize the LLM responses. This is particularly a source of risk for LLMs because","entity":"Human","intent":"Unintentional","timing":"Post-deployment","domain":5,"subdomain":"5.1"}]}