AI Chatbots Exhibit Status Quo Bias, Hindering Climate-Friendly Recommendations
A comprehensive study by the University of Waterloo has revealed that large language models (LLMs) exhibit a significant "status quo bias," consistently favoring existing, high-emission choices over climate-friendly alternatives. The research, which evaluated 11 prominent AI models across nearly 55,000 prompts, found that chatbots approved existing policies 70% of the time when asked whether a government or organization should proceed with a plan, but only endorsed novel climate interventions or regulatory changes 34% of the time. This bias was particularly pronounced in political and civic governance scenarios. In consumer contexts, LLMs were 4.1 times more likely to recommend electric vehicles to users who already owned one, and their recommendations for EVs lagged behind actual real-world adoption rates, even in countries with high EV sales like Norway. The study suggests that this inherent bias, stemming from LLMs being trained on historical data reflecting past human choices, could impede progress tow...
