Full Paper
Papers should be 2 to 9 pages (excluding references and appendices) using the NeurIPS 2026 workshop style, or 2 to 8 pages using the ICML 2026 style.
Machine Learning/CORE Unranked
AI4GOOD Workshop 2026
Trustworthy AI for Good (AI4GOOD) Workshop @ ICML 2026
The AI4GOOD workshop at NeurIPS 2026 and ICML 2026 brings together researchers from AI safety, AI for social good, and AI policy/governance to bridge technical advances in trustworthy AI with real-world societal impact. It focuses on how AI systems affect public institutions, civic discourse, and information integrity, with an emphasis on scalable social benefit and cooperative multi-agent systems.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Position Paper
Accepted as in scope; no checklist required.
Survey Paper
Accepted as in scope; no checklist required.
Research areas in scope
01
General Track
Trustworthy AI models: evaluation, auditing, and red-teaming of models for harmful behaviors and failure modes; safety monitoring after deployment; and alignment and robustness methodsAI for social good: methods, evidence standards, and evaluation frameworks for demonstrating real-world benefit and avoiding unintended harms at population scaleAI for information integrity: detection and mitigation of disinformation, manipulation, and influence operations; and building resilience of the information ecosystemAI for public institutions: accountable use of AI in government and civic settings, including transparency, documentation, procurement, and oversight practicesAI for civic discourse: AI systems that support public deliberation and civic engagement while preserving legitimacy and avoiding undue influence
02
Multi-Agent Track
Collusion and steganographic communication between agentsSecure interaction and delegation protocolsConfinement of strategic learned agentsCompositional failures of safety and compliance guaranteesAttacks that propagate across agent networksEvaluation and red-teaming of agent populationsOversight and incident response for deployed multi-agent systems
03
Special Theme
Cooperative AI: multi-agent coordination, negotiation, and conflict resolution; and mechanisms for trust, commitment, and cooperation among AI systems and between AI and humans
Policies worth checking twice
- Submissions are non-archival by default, with an option to publish in proceedings after acceptance (poll later)
- All submissions undergo double-blind review via OpenReview with full anonymization
- Papers under review at other conferences or journals are allowed, but authors must ensure compliance with those venues' policies
- Authors may submit to multiple workshops, but must confirm other workshops' policies
- No exceptions to the OpenReview submission deadline
- Travel support available for scholars from under-represented communities
- Cooperative AI theme papers eligible for special travel support and top paper prize
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026