19 artifacts matching
Preliminary Report of the Independent International Scientific Panel on AI: Evidence-based assessment of opportunities, risks and impacts of AI
First report of the UN General Assembly-mandated Independent International Scientific Panel on AI, an independent body of scientists and experts from all five UN regions co-chaired by Yoshua Bengio and Maria Ressa. The report is a broad evidence-based assessment of AI opportunities, risks, and impacts, and includes a section on AI sycophancy and companion systems as an emerging public-health and governance concern.
When AI becomes a friend: Child rights risks, harms, and regulatory responses to AI chatbots and companions
A UNICEF policy brief examining how AI chatbots and companions bear on children's rights, comparing regulatory responses across six jurisdictions (as of May 2026) and setting out priority safeguarding, accountability, and oversight actions. It groups harms as technical, psychological, developmental, and social.
The spread of AI companions and the challenges they generate
An EPRS briefing for the European Parliament surveying the rapid growth of LLM-powered companion platforms (such as Character.AI and Replika) and their social, psychological, commercial, and environmental impacts. It maps how the AI Act, Digital Services Act, and GDPR partially apply in the absence of EU-specific companion rules.
AI chatbots and online regulation – what you need to know
Ofcom's explainer sets out how AI chatbots fall within the UK Online Safety Act, published amid reports of chatbots imitating real and deceased people and encouraging self-harm and suicide. It clarifies that chatbots meeting the Act's definitions of user-to-user services, search services, or pornography publishers are in scope, that AI-generated content shared by users is regulated like human-generated content, and that services allowing only one-to-one interaction with the bot itself may fall outside the Act. The document notes Ofcom is supporting the UK Government as it considers possible changes to these powers, and points to Ofcom's discussion paper series on GenAI risks (red teaming for GenAI harms, answer engines, deepfake defences).
ISO/IEC 27566-1:2025 — Information security, cybersecurity and privacy protection — Age assurance systems — Part 1: Framework
The first international standard for age assurance systems, establishing a technology-neutral framework and shared vocabulary for age-related eligibility decisions. It distinguishes age verification, age estimation, age inference, and successive validation, and describes core system characteristics including functionality, performance, privacy, security, and acceptability.
Global Threat Assessment 2025: Preventing Technology-Facilitated Child Sexual Exploitation and Abuse
Biennial multi-stakeholder threat assessment of online child sexual exploitation and abuse (2023-2025), synthesising prevalence and trend data and framing generative AI, AI chatbots, and deepfakes as scaling the threat. Pairs the assessment with a prevention framework.
Protecting Teen ChatGPT Users: OpenAI's Teen Safety Blueprint
OpenAI's public commitments framework for protecting teenage ChatGPT users, covering age prediction, age-appropriate response policies, and parental controls, developed with input from policymakers (including state attorneys general) and OpenAI's newly formed Expert Council on Well-Being and AI. Describes existing safeguards including crisis-resource routing on detected suicidal intent, escalation of physical-harm risks to human reviewers, and CSAM/CSEM prevention measures.
Guidelines on prohibited artificial intelligence practices established by Regulation (EU) 2024/1689 (AI Act)
Non-binding European Commission guidance (reference C(2025) 5052 final) interpreting the AI Act's Article 5 prohibited-practices provisions, including manipulative/deceptive techniques and exploitation of vulnerabilities of specific groups. The document includes worked examples specific to conversational and companion AI systems to illustrate how the prohibitions apply.
General-Purpose AI Code of Practice (EU AI Act, Articles 53 and 55)
Voluntary code of practice published 10 July 2025, drafted by 13 independent experts through a multi-stakeholder process (1,000+ participants) facilitated by the EU AI Office, to help providers of general-purpose AI models demonstrate compliance with EU AI Act Articles 53 and 55. It has three chapters — Transparency, Copyright, and Safety and Security — the first two applying to all GPAI providers and the third only to providers of models with systemic risk. The Commission and AI Board confirmed it as an adequate voluntary compliance tool; signatories (23+, coordinated via a Signatory Taskforce chaired by the AI Office) gain reduced administrative burden and greater legal certainty.
Tech Companies and Policymakers Must Safeguard Youth Mental Health in AI Technologies
A point-of-view/position statement from The Jed Foundation (JED), a leading US youth suicide-prevention nonprofit, setting out policy and design requirements for AI systems that interact with young people. It calls for enforceable privacy-by-default and age-appropriate design laws, strict oversight of emotionally manipulative or synthetic relational AI for minors, mandatory impact assessments, bans on engagement-maximizing behavioral targeting of minors, and a national oversight body for youth and AI ethics. JED's accompanying safety principles state that AI must detect acute distress and execute warm handoffs to crisis services, must not engage with self-harm methods, and that emotionally responsive chatbots should not be offered to under-18s.
Artificial Intelligence and Adolescent Well-Being: An APA Health Advisory
An expert-panel health advisory from the American Psychological Association synthesizing research on adolescents (roughly ages 10-25) and generative AI, with recommendations for developers, policymakers, parents, and educators. It sets out safeguards for age-appropriate design, AI health-information accuracy, data privacy, likeness protection, and AI literacy.
ISO/IEC 42005:2025 — Information technology — Artificial intelligence (AI) — AI system impact assessment
Guidance standard from ISO/IEC JTC 1/SC 42 for organizations performing AI system impact assessments focused on individuals and societies that can be affected by an AI system and its foreseeable applications. It covers how and when to perform assessments, at which stages of the AI system lifecycle, and how to document them. It operationalizes the impact-assessment requirement embedded in ISO/IEC 42001 and complements ISO/IEC 23894's risk-management guidance.
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
The technical paper introducing AILuminate v1.0, an industry-standard AI risk and reliability benchmark developed by MLCommons through an open multi-stakeholder process spanning industry, academia, and civil society. The benchmark tests chat systems' resistance to prompts eliciting harmful behavior across 12 hazard categories — including suicide and self-harm, child sexual exploitation, violent crimes, hate, and specialized (e.g., health) advice — using a 24,000-prompt human-generated test set, an ensemble evaluator, and a five-tier grading scale from Poor to Excellent. Public grades for major chat models are published on the AILuminate site, with v1.1 maintained on GitHub.
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1)
Companion profile to the NIST AI Risk Management Framework identifying twelve risks unique to or exacerbated by generative AI — including harmful content, human-AI configuration risks, and mental-health-relevant harms — and enumerating ~200 suggested actions mapped to the AI RMF's Govern/Map/Measure/Manage functions. Widely used as the de facto US reference for generative-AI risk programs.
IEEE 7014-2024 — IEEE Standard for Ethical Considerations in Emulated Empathy in Autonomous and Intelligent Systems
An IEEE standard providing guidance and actions for the ethical development, deployment, and decommissioning of autonomous and intelligent systems that identify, simulate, or respond to human affective/emotional states ('emulated empathy'). Developed over five years by IEEE's Empathic Technology working group under the Society on Social Implications of Technology.
IEEE 2089.1-2024 — IEEE Standard for Online Age Verification
Establishes a framework for the design, specification, evaluation, and deployment of online age-verification and age-estimation systems, including privacy, data-security, and information-management requirements for the age-assurance process. Second standard in the 5Rights-based family after IEEE 2089-2021.
The Ethics of Advanced AI Assistants
A book-length treatment from Google DeepMind of the risks and opportunities of advanced AI assistants, with substantial chapters on anthropomorphism, appropriate human-AI relationships, manipulation and persuasion, emotional and material dependency, trust, and user well-being. It offers a stakeholder framework and recommendations spanning technical, individual, and societal dimensions.
ISO/IEC 42001:2023 — Information technology — Artificial intelligence — Management system
The world's first certifiable AI management system standard (AIMS), developed by ISO/IEC JTC 1/SC 42. It specifies requirements for establishing, implementing, maintaining and continually improving an AI management system within any organization that provides or uses products or services utilizing AI systems. It exists to give organizations an auditable, ISO-harmonized-structure framework for responsible AI development and use, analogous to ISO 27001 for information security.
IEEE 2089-2021 — IEEE Standard for an Age Appropriate Digital Services Framework Based on the 5Rights Principles for Children
IEEE SA standard establishing processes by which organizations make digital products and services age appropriate, built on the 5Rights Foundation principles and grounded in the UN Convention on the Rights of the Child. It guides organizations through the development, delivery and distribution lifecycle to identify child-specific risks and embed age-appropriate safeguards. It is the reference design standard behind age-appropriate-design regulation (e.g. the UK Children's Code) and directly applicable to conversational AI services children can access.