Why do Experts Disagree on Existential Risk and P(doom)? A Survey of AI Experts
This addresses the problem of expert disagreement on AI existential risks for AI safety researchers and policymakers, providing the first systematic survey to inform communication and prioritization efforts.
The study surveyed 111 AI experts to understand their beliefs on existential risks from AI, finding that they cluster into two viewpoints—'AI as controllable tool' and 'AI as uncontrollable agent'—with 78% agreeing that technical researchers should be concerned about catastrophic risks, but only 21% were familiar with key concepts like instrumental convergence.
The development of artificial general intelligence (AGI) is likely to be one of humanity's most consequential technological advancements. Leading AI labs and scientists have called for the global prioritization of AI safety citing existential risks comparable to nuclear war. However, research on catastrophic risks and AI alignment is often met with skepticism, even by experts. Furthermore, online debate over the existential risk of AI has begun to turn tribal (e.g. name-calling such as "doomer" or "accelerationist"). Until now, no systematic study has explored the patterns of belief and the levels of familiarity with AI safety concepts among experts. I surveyed 111 AI experts on their familiarity with AI safety concepts, key objections to AI safety, and reactions to safety arguments. My findings reveal that AI experts cluster into two viewpoints -- an "AI as controllable tool" and an "AI as uncontrollable agent" perspective -- diverging in beliefs toward the importance of AI safety. While most experts (78%) agreed or strongly agreed that "technical AI researchers should be concerned about catastrophic risks", many were unfamiliar with specific AI safety concepts. For example, only 21% of surveyed experts had heard of "instrumental convergence," a fundamental concept in AI safety predicting that advanced AI systems will tend to pursue common sub-goals (such as self-preservation). The least concerned participants were the least familiar with concepts like this, suggesting that effective communication of AI safety should begin with establishing clear conceptual foundations in the field.