Longtermism is the ethical view that positively influencing the long-term future is one of the most important moral priorities of our time. Its starting point is a question of scale: if humanity survives for a long time, the number of people who could live in the future vastly exceeds the number alive today, so actions that affect whether and how that future unfolds could matter more than almost anything else we do. The term was coined by the philosophers Toby Ord and William MacAskill and was popularized through Ord’s work on existential risk, including his book The Precipice and his later essay “The Precipice Revisited,” in which he revisits his risk estimates.
In practice, longtermism focuses attention on reducing existential risks - events that could permanently end humanity’s potential - and on steering transformative technologies onto better trajectories. Artificial intelligence sits near the center of this concern, because advanced AI is seen by longtermists as both one of the largest potential sources of catastrophe and a lever that could shape the entire future. This reasoning is a major part of why AI safety attracts the funding and attention it does, and why some philanthropists and researchers treat it as a top global priority.
Longtermism is also genuinely contested. Critics argue that focusing on speculative far-future outcomes can divert resources from urgent present harms, that probability estimates about the distant future are unreliable, and that the framework can be used to rationalize almost any present sacrifice. The “AI as normal technology” view is in part a reaction against longtermist-flavored catastrophe forecasting. The debate is not merely academic: it directly shapes how governments and companies weigh near-term AI harms against long-term existential ones.
Why a general reader should care: whether decision-makers adopt a longtermist or a near-term lens determines which AI risks get prioritized, which in turn shapes regulation, research funding, and corporate strategy.