Source podcast
Nathan Labenz explores AI through expert interviews and discussions of its uses and consequences.
Author Garrison Lovely argues markets and lawsuits won't discipline AI labs: the risks go unpriced, a mass disaster would bankrupt a firm first, and he sees no one to blame for agents' Hugging Face hack. He wants test prosecutions.
Journalist Garrison Lovely argues AI lab workers' leverage is near its peak as labs try to automate AI research, so staying to form safety unions may beat quitting. He says he is no labor-law expert and points leavers to whistleblower help.
Author Garrison Lovely argues that China fast-follows the US frontier, so a US slowdown would slow both countries. He sees US credibility on AI risk as the main barrier to a deal, and concedes a deal might appeal less to the US.
Author Garrison Lovely proposes freezing frontier AI: no training run as large as the last, no RL from verifiable rewards, no recursive self-improvement, policed by auditors and chip checks. He admits the economic cost would be significant.
