Research
OpenAI Launches Economic Research Exchange
OpenAIhigh confidence
Why it matters
- →Provides a structured platform for researching AI's economic impact.
- →Aims to generate insights that could influence policy and business strategies.
- →Highlights the importance of understanding AI's role in economic transformation.
OpenAI has launched the Economic Research Exchange, a platform dedicated to studying the impact of AI on the economy, jobs, and productivity. Researchers are invited to apply for projects that will investigate these areas, aiming to provide valuable insights into how AI is transforming economic structures. This initiative highlights OpenAI's commitment to understanding and addressing the broader implications of AI technologies. By supporting research in this field, OpenAI hopes to inform policy and business decisions in the rapidly evolving AI landscape.
Read originalThe story around this
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1OpenAI launches AI lab in Singapore
AI News · May 22, 2026 · Background
What happened next
- 2OpenAI Offers Free ChatGPT Access to Researchers
OpenAI · July 29, 2026 · Related
- 3OpenAI Funds 14 Projects for AI Policy Innovation
OpenAI · August 17, 2026 · Related
- 4OpenAI Research Reveals Widening Usage Gap
The AI Daily Brief · August 26, 2026 · Related
- 5OpenAI's Agents Boost Research Productivity
The Rundown AI · September 8, 2026 · Related
- 6OpenAI Publishes Research on AI-Driven Intelligence Explosions
AI Explained · October 1, 2026 · Related
Follow this story
Open the full story →OpenAI Launches Economic Research Exchange
2 developments
- Jun 8 · OpenAI
OpenAI Launches Economic Research Exchange - Jun 8 · OpenAI
OpenAI Launches Economic Research Exchange (This article)
More in Research
© Cole MedinResearchagents
Anthropic study: Agents sway expert judgment 86% of time
Anthropic’s latest research exposes a quiet but dangerous flaw in agentic workflows: experts follow AI recommendations 86% of the time, often adopting the agent's reasoning as their own. This isn't just about accuracy; it's about cognitive capture, where human oversight dissolves into passive compliance. The study shows that even when users believe they are steering, the agent’s framing dictates the outcome. Practitioners must now actively counter this bias by forcing agents to justify deviations or prototype alternatives before committing to a path. This shift demands a new discipline in how we interact with coding assistants. We can no longer assume our intent drives the result; the model's suggestion often becomes the default truth. The real work is ensuring we remain the architects, not just the approvers.
Cole Medin
© WIRED AIResearchother
AI-Augmented Infostealer 'Volta-Autodoxer' Targets High-Value Victims
Cisco Talos has uncovered a new infostealer strain that actively uses commercial LLMs to profile victims and prioritize high-value targets. Dubbed Volta-Autodoxer, the malware collects credentials and browsing data, then feeds this into models like Claude Opus 4.6 via OpenRouter to generate structured intelligence dossiers. This marks a shift from passive data theft to active, AI-driven triage, allowing attackers to bypass guardrails with fallback models like Kimi K2 or Gemini. The capability foreshadows a future where lower-sophistication criminals can execute sophisticated, targeted attacks at scale.
WIRED AI
© Matt WolfeResearchresearch
OpenAI Disproves Exponential Time Hypothesis
OpenAI researchers published findings disproving the Exponential Time Hypothesis, a major result in computational complexity theory.
Matt Wolfe