MIT AI Risk Repository · domain 6: Socioeconomic & Environmental

6.1 Power centralization and unfair distribution of benefits

AI-driven concentration of power and resources within certain entities or groups, especially those with access to or ownership of powerful AI systems, leading to inequitable distribution of benefits and increased societal inequality.

Risk entries
54
Frameworks citing it
12
Recorded incidents
6
Incidents since 2020
2
Causal entity (risk entries)
Causal entity (risk entries) 35 0 Human: 35 Human 35 Other: 13 Other 13 AI: 3 AI 3 Not coded: 3 Not coded 3
Causal entity (risk entries)
LabelValue
Human35
Other13
AI3
Not coded3
Intent (risk entries)
Intent (risk entries) 18 0 Intentional: 18 Intentional 18 Unintentional: 17 Unintentional 17 Other: 16 Other 16 Not coded: 3 Not coded 3
Intent (risk entries)
LabelValue
Intentional18
Unintentional17
Other16
Not coded3
Timing (risk entries)
Timing (risk entries) 25 0 Post-deployment: 25 Post-deployment 25 Other: 24 Other 24 Not coded: 3 Not coded 3 Pre-deployment: 2 Pre-deployment 2
Timing (risk entries)
LabelValue
Post-deployment25
Other24
Not coded3
Pre-deployment2
Recorded incidents per yearIncident date; current year partial
Recorded incidents per year 2 0 2016: 1 2016 1 2017: 1 2017 1 2018: 2 2018 2 2021: 1 2021 1 2025: 1 2025 1
Recorded incidents per year
LabelValue
20161
20171
20182
20211
20251
Entries by levelRisk categories, subcategories and additional evidence coded to this subdomain
Entries by level 41 0 Risk Category: 13 Risk Category 13 Risk Sub-Category: 41 Risk Sub-Category 41
Entries by level
LabelValue
Risk Category13
Risk Sub-Category41
  • Value lock-in

    the most powerful AI systems may be designed by and available to fewer and fewer stakeholders. This may enable, for instance, regimes to enforce narrow values through pervasive surveillance and oppres...

    X-Risk Analysis for AI Research (Hendrycks2022) · Human · Intentional · Post-deployment

  • Concentration of Power

    "Governments might pursue intense surveillance and seek to keep AIs in the hands of a trusted minority. This reaction, however, could easily become an overcorrection, paving the way for an entrenched...

    An Overview of Catastrophic AI Risks (Hendrycks2023) · Human · Intentional · Other

  • Exclusion

    "The best AI techniques requires a large amount resources: data, computational power and human AI experts. There is a risk that AI will end up in the hands of a few players, and most will lose out on...

    A framework for ethical Ai at the United Nations (Hogenhout2021) · Human · Intentional · Post-deployment

  • Within-country issues: domestic inequality

    "Our next problem is the fact that the current AI workforce does not evenly represent world demographics. Men from the US and China, working in the US, for US corporations, are disproportionately high...

    Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024 ) · Other · Other · Other

  • Demographic diversity of researchers

    "The AI research establishment inherits patterns of under-representation that are dominant in most technical elds. In North America, large parts of professional AI research require a Ph.D., yet less t...

    Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024 ) · Other · Other · Other

  • Privatization of AI

    "Researchers in deep learning and those with greater research impact are more likely to migrate to industry, raising concerns about the “privatization of AI knowledge” [278]. Specically, if the most s...

    Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024 ) · Human · Intentional · Pre-deployment

  • Between-country issues: global inequality

    "There is an even greater divide between the countries currently leading in AI and those falling behind. While AI is widely considered a national priority, with almost 40% of countries having created...

    Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024 ) · Other · Other · Other

  • Dystopian trajectory lock-in because of misuse of advanced AI to establish and/or maintain totalitarian regimes;

    -

    Advancing AI Governance: A Literature Review of Problems, Options, and Proposals (Maas2023) · Human · Unintentional · Post-deployment

  • Systemic Risks

    "In addition to risks stemming from the unreliability or misuse of general purpose AI models, further Systemic Risks can originate from the centralisation of general purpose AI development as well as...

    Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023 ) · Other · Unintentional · Post-deployment

  • Economic Power Centralisation and Inequality

    "Increasingly advanced general purpose AI models pose the risk of a concentration of economic power and exacerbation of existing inequalities through disparities in effective access to these models. T...

    Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023 ) · Human · Other · Post-deployment

  • Digital divide

    "The digital divide is often defined as the gap between those who have and do not have access to computers and the Internet (Van Dijk, 2006). As the Internet gradually becomes ubiquitous, a second-lev...

    Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration (Nah2023) · Human · Unintentional · Post-deployment

  • Power concentration

    "EAI deployment could accelerate the consolidation of economic and political power. Unlocking increasing returns to capital for EAI owners, EAI will decrease employers’ reliance on and responsiveness...

    Embodied AI: Emerging Risks and Opportunities for Policy Action (Perlo2025) · AI · Unintentional · Post-deployment

  • Labor & material/Macro-socio economic harms

    Algorithmic systems can increase “power imbalances in socio-economic relations” at the societal level [4, 137, p. 182], including through exacerbating digital divides and entrenching systemic inequali...

    Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023) · Other · Other · Post-deployment

  • Financial Costs

    "The estimated financial costs of training, testing, and deploying generative AI systems can restrict the groups of people able to afford developing and interacting with these systems."

    Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023) · Human · Intentional · Other

  • Concentration of Authority

    "Use of generative AI systems to contribute to authoritative power and reinforce dominant values systems can be intentional and direct or more indirect. Concentrating authoritative power can also exac...

    Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023) · Human · Intentional · Post-deployment

  • Power

    "The political influence and competitive advantage obtained by having technology."

    An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance (Teixeira2022) · Human · Intentional · Other

  • Market Concentration and Infrastructure Dependencies:

    "Over-reliance on a limited number of dominant AI providers could create critical single points of failure across essential services. Market concentration in AI development may lead to scenarios where...

    Frontier AI Risk Management Framework (v1.0) (Tse2025) · Human · Unintentional · Other

  • Global AI Research and Development Divides:

    "Asymmetric AI development capabilities between nations could exacerbate geopolitical tensions and create new forms of technological dependency. Countries lacking advanced AI capabilities may become i...

    Frontier AI Risk Management Framework (v1.0) (Tse2025) · Other · Unintentional · Other

  • Power

    "The concentration of military, economic, or political power of entities in possession or control of AI or AI-enabled technologies."

    A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025) · Human · Intentional · Post-deployment

  • Algorithmic monoculture

    "The dominance of specific AI models could lead to a lack of diversity in approaches, amplifying systemic risks if these models fail."

    A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025) · AI · Unintentional · Post-deployment

  • Dependency on providers

    "Excessive reliance on specific AI providers can lead to vulnerabilities due to lack of alternatives or interoperability."

    A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025) · Human · Unintentional · Other

  • Winner-take-all dynamics

    "The competitive nature of AI development could lead to significant eco- nomic and security advantages for a few entities."

    A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025) · Other · Other · Other

  • Disparate access to benefits due to hardware, software, skills constraints

    "Due to differential internet access, language, skill, or hardware requirements, the benefits from LMs are unlikely to be equally accessible to all people and groups who would like to use them. Inacce...

    Ethical and social risks of harm from language models (Weidinger2021) · Human · Unintentional · Post-deployment

  • Disparate access to benefits due to hardware, software, skill constraints

    Due to differential internet access, language, skill, or hardware requirements, the benefits from LMs are unlikely to be equally accessible to all people and groups who would like to use them. Inacces...

    Taxonomy of Risks posed by Language Models (Weidinger2022) · Human · Unintentional · Post-deployment

  • Unfair distribution of benefits from model access

    "Unfairly allocating or withholding benefits from certain groups due to hardware, software, or skills constraints or deployment contexts (e.g. geographic region, internet speed, devices)"

    Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023) · Human · Unintentional · Post-deployment