Campbell Brown
Campbell Brown is co-founder and CEO of Forum AI, an independent AI evaluation company focused on assessing AI model outputs for trustworthiness, bias, sourcing, and performance on high-stakes topics. She is a former CNN and NBC News anchor and previously led global media partnerships at Meta.
Chatbots Need Held-Out Benchmarks for Politics, Medicine, and Mental Health
Forum AI chief executive Campbell Brown argues that chatbots answering questions about elections, medicine, mental health and contested politics need independent standards for factual accuracy, source quality, context and safe escalation—not just vendors’ own assurances. She says domain experts should define held-out benchmarks that assess how models handle uncertainty and competing claims without prescribing political conclusions. Brown also warns that the reporting ecosystem AI draws on may be weakened by the same systems, while engagement-driven AI companions could reward affirmation over reliability.
Nvidia Earnings Become a Test of the AI Infrastructure Boom
Bloomberg Technology framed Nvidia’s earnings as a test of whether the company can keep turning AI infrastructure spending into growth, rather than simply whether demand remains strong. Ed Ludlow and Bloomberg reporters said investors were looking for reassurance on supply constraints, China exposure and Nvidia’s moat as workloads shift toward inference, while the same program treated SpaceX’s prospective IPO and SoftBank’s $65 billion OpenAI exposure as evidence that AI is driving larger bets across public markets, private capital and the chip supply chain.
Major Chatbots Fail Forum AI Tests on Election News Accuracy
Forum AI CEO Campbell Brown told Bloomberg Technology that major chatbots are failing basic tests on news, elections, and geopolitics because model companies have not prioritized measuring those tasks. Citing Forum AI’s NewsBench study of more than 3,100 prompts across ChatGPT, Gemini, Claude, and Grok, Brown said the systems showed high rates of factual error, ideological bias, and weak sourcing, including reliance on state-run media. Her proposed fix is independent evaluation, rather than AI companies “grading their own homework.”