Attention is all we have: A conjectural theory of cognitive inequality
David Bessis argues that human cognitive inequality stems from differences in training attention, not innate ability. He proposes that mathematical insight, like meditation, is accessible to anyone who learns to direct their focus appropriately, framing intelligence as a trainable skill of attentional control.
Background
- David Bessis is a mathematician and author of *The Mathematical Experience*; he writes about cognition, learning, and how people think.
- "Attention is all we have" is a play on the famous AI paper "Attention Is All You Need" (2017), which introduced the Transformer architecture behind ChatGPT and similar LLMs — Bessis borrows its title to argue that human cognition, not just AI, runs on attention.
- The piece sketches a "conjectural theory of cognitive inequality": the idea that differences in intelligence or success stem less from raw IQ or knowledge, and more from how effectively people direct, sustain, and switch their attention.
- Bessis draws on his own experience learning math and teaching adults, and contrasts "school-style" learning (knowledge accumulation, testing) with "attention-style" learning (intense focus, pattern recognition, flow states).
- The essay is speculative and philosophical, not empirical; it belongs to a growing discourse that rethinks intelligence as a dynamic attentional skill rather than a fixed trait.