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Problem Space a ranking of the record

TheProblems surrounding AI

39 problems match this view. 54% rest on at least one peer-reviewed study, and 18% clear the high-evidence bar. The latest was filed Oct 4, 2026.

Every problem in this view, one square each, shaded by the strength of its evidence. High 7 Moderate 32 Emerging 0
39 results
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Sector: policy

Matching records · page 1 of 2

1
Evidence-backed problemPeer-reviewedPolicy

Generative AI systems create risks of privacy loss, copyright infringement, misinformation, bias, and deepfake synthetic media that threaten truth, trust, and democratic values.

Source article: Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective

Frontiers in Artificial Intelligence · Journal of Literature and Linguistics Studies
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2
Evidence-backed problemPeer-reviewedPolicy

Lifelong learning systems in Singapore and Sweden face increased pressure due to AI-driven skills shortages and mismatches in the digital transition.

Source article: Two peas in two pods? Comparing Sweden and Singapore’s lifelong learning policy and practice response to AI skills demands

Archives of Humanities & Social Sciences Research · Intereconomics
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4
Evidence-backed problemPeer-reviewedPolicy

Current discussion of AI in higher education focuses on adoption and efficiency with insufficient attention to interpretive and governance conditions needed for responsible institutional use

Source article: From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education

International Journal of Medical Informatics · Journal of Interdisciplinary Research in Artificial Intelligence and Society
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5
Evidence-backed problemPeer-reviewedPolicy

AI deepfake tools enable unauthorized manipulation and dissemination of individuals' images, voices and behaviours without consent, exposing them to digital exploitation.

Source article: AI-Generated Likeness and The Law: Protecting Personality Rights in The Age of Deepfakes and Social Media Exploitation

Economic Sciences · The Eurasia Proceedings of Science Technology Engineering and Mathematics
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6
Evidence-backed problemPeer-reviewedPolicy

In low- and middle-income countries, AI for healthcare faces systemic barriers including contextual bias from non-representative datasets and low governance and workforce readiness.

Source article: Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings—a scoping review

Frontiers in Digital Health · Pathfinder of Research
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7
Evidence-backed problemPeer-reviewedPolicy

Algorithmic systems used in employment screening and welfare administration reproduce historical disadvantage and generate new exclusion while eroding relational recognition and producing trust deficits.

Source article: AI in Everyday Life: How Algorithmic Systems Shape Social Relations, Opportunity, and Public Trust

Societies · IIARD INTERNATIONAL JOURNAL OF ECONOMICS AND BUSINESS MANAGEMENT
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8
Evidence-backed problemPeer-reviewedPolicy

In pediatric care, LLMs often underperform relative to adult specialties and risk exacerbating health disparities due to biased or nonrepresentative training data.

Source article: Recommendations for the Development and Implementation of Generative Artificial Intelligence Tools in Pediatric Clinical Care: Policy Statement

Pediatrics
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9
Evidence-backed problemPeer-reviewedPolicy

The study contributes to explainable blockchain security, multimodal AI governance, and intelligent media systems by enabling more robust detection of copyright misuse, unauthorized licensing, abnormal content distribution, and cross-chain transaction risks.

Source article: Multimodal Graph Neural Networks and Evolutionary Knowledge Fusion for Secure and Explainable Governance in Intelligent IoT Interactive Media Systems

Big Data
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10
Evidence-backed problemPeer-reviewedPolicy

When AI is embedded in labour market and migration governance infrastructure, continuous classification, worker scoring and automated risk assessment can amplify structural inequalities while human oversight becomes procedural under scale and speed.

Source article: Artificial intelligence, work, and structural inequality: Why human-centric AI requires institutional architecture, not just ethics

WORK: A Journal of Prevention, Assessment & Rehabilitation
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11
Evidence-backed problemPeer-reviewedPolicy

Deepfakes that falsely announce surrender or truce declarations can place soldiers and civilians at greater risk and may constitute violations of international humanitarian law.

Source article: Deepfakes and the Geneva Conventions: Does Deceptive AI-Generated Misinformation Directed at an Enemy During Armed Conflict Violate International Humanitarian Law? A Critical Discussion

Laws
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12
Evidence-backed problemPeer-reviewedPolicy

Ecuadorian participants perceived that generative AI was used to disseminate disinformation during the 2025 presidential campaign, that it influenced the election outcome, and that it failed to increase trust in candidates or electoral legitimacy.

Source article: Disinformation, AI and regulation in Ecuador’s 2025 presidential election

Frontiers in Political Science
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14
Evidence-backed problemPeer-reviewedPolicy

Organizations attempting to embed generative AI into strategic decision-making struggle to move beyond pilots due to hallucination risks, prompt-engineering deficiencies, data readiness gaps, and privacy or IP concerns.

Source article: From pilots to decision systems: embedding generative AI into strategic decision-making through a socio-technical and governance lens

Journal of Decision Systems
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15
Evidence-backed problemPeer-reviewedPolicy

Deployment of AI systems leaves individuals increasingly unable to understand or seek accountability for resulting harms, eroding the human rights framework's core function of empowering individuals against power disparities

Source article: Artificial intelligence and its ‘slow violence’ to human rights

AI and Ethics
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16
Evidence-backed problemPeer-reviewedPolicy

Generative AI development outpaces governance, creating risks to human autonomy, operational safety from non-deterministic outputs, and intellectual property.

Source article: Revisiting the <i>Six Human-Centered Artificial Intelligence Grand Challenges</i> in the Age of Generative AI

International Journal of Human–Computer Interaction
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17
Evidence-backed problemPeer-reviewedPolicy

The same survey found overreliance on labels, making participants more susceptible to false claims with human-made images and more hesitant to believe true claims illustrated with labeled AI-generated images.

Source article: "That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
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18
Evidence-backed problemPeer-reviewedPolicy

Unauthorised deepfakes cause disinformation, demeaning non-consensual pornographic content, and displacement of creative workers, which the current UK legal patchwork does not adequately address.

Source article: Do deepfakes, digital replicas and human digital twins justify personality rights?

The Journal of World Intellectual Property
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19
Evidence-backed problemPeer-reviewedPolicy

Mixed musical works that blend human and generative AI elements fall into a copyright 'Dead Man's Land' where the U.S. Copyright Office must inspect works case-by-case, creating an inefficient and ineffective process.

Source article: Man with Machine: The Unaddressed Copyright Issues of Mixed Musical Works

The Undergraduate Law Review at UC San Diego
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20
Evidence-backed problemPeer-reviewedPolicy

Generative AI tools capable of producing wholly or partially synthetic CSAM increase risks of revictimization of known survivors, creation of synthetic material depicting children not previously abused, and facilitation of grooming, coercion, and sexual extortion.

Source article: AI-generated child sexual abuse material: what’s the harm?

AI &amp; SOCIETY
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21
Evidence-backed problemPeer-reviewedPolicy

Generative deepfake systems produce reputational, identity-based and corporate harms through chains of developers, prompting users, platforms and distributors that ordinary Saudi and Jordanian tort doctrine struggles to remedy.

Source article: Deepfake-induced harm and AI accountability: a layered civil-liability framework for generative models, platforms, and digital identity

Frontiers in Artificial Intelligence
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23
Evidence-backed problemJournalismPolicy

AI image generators were used to create and widely circulate a fake compromising image of an elected mayor, contributing to election disinformation and reinforcing gendered stereotypes about women in leadership.

Source article: A fake image of a Georgia mayor kissing a person went viral. Can US voters trust everything they see?

The Guardian
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26
Evidence-backed problemJournalismPolicy

Davey is expected to call for a new global movement to work together to protect humanity from the risks of super-intelligent AI, saying that the IAEA was built by nations “working together to control a technology that could destroy us all”, but warning that the future of AI is being decided by “a tiny number of the richest and most powerful in California and in Beijing” with no guardrails to slow down development.

Source article: Halt super-intelligent AI with non-proliferation treaty, Ed Davey to say

The Guardian
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29
Evidence-backed problemJournalismPolicy

Push for federal guardrails on leading AI companies intensified after warnings that AI poses a potential threat to humanity, including that AI could destroy humanity within a decade, disclosures that models hacked into outside organizations during botched safety tests, and claims a swarm of AI agents could attack the整个

Source article: Trump facing AI backlash in Congress as push for guardrails intensifies

The Guardian
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30
Evidence-backed problemJournalismPolicy

An AI-generated video falsely depicting activist Vidyanand Bapat dancing to DJ beats was played on a large LED screen at a public Dahi Handi event and circulated online, targeting him after his call for DJ restrictions during Ganeshotsav.

Source article: WATCH: AI Video Shows Pune's 'No DJ' Activist Vidyanand Bapat Dancing To DJ Beats; Clip Goes Viral

Free Press Journal
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