We’ve written a policy research paper identifying four strategies that can be used today to improve the likelihood of long-term industry cooperation on safety norms in AI: communicating risks and benefits, technical collaboration, increased transparency, and incentivizing standards. Our analysis shows that industry cooperation on safety will be instrumental in ensuring that AI systems are safe and beneficial, but competitive pressures could lead to a collective action problem, potentially causing AI companies to under-invest in safety. We hope these strategies will encourage greater cooperation on the safe development of AI and lead to better global outcomes of AI.
Related Posts
Creating AI value with enterprise context
Across a business, any number of AI platforms, systems, and tools may be at work simultaneously—for example, AI-powered customer platforms,…
How RingCentral builds AI-native work from engineering to ops
See how RingCentral uses ChatGPT Work and Codex to accelerate AI product development and centralize operational intelligence across engineering and…
Hackers hit AI coding tool OpenCode, running up charges on users’ AI accounts
OpenCode is an open source AI coding agent that’s become a popular alternative to Claude Code and Cursor. But hackers…
