Mental Algorithms: How AI Changes the Cost of Thinking
The article explores how AI alters the cost of thinking rather than replacing human cognition, emphasizing that thinking quality is more about effort than intelligence. It breaks down thinking into structured (slow, deliberate) and fast (heuristic-based) processes, showing how AI reduces the time and energy required for tasks like decomposition, iteration, and satisficing. While AI accelerates reasoning and lowers barriers to acceptable solutions, human judgment remains critical for validation, abstraction, and handling edge cases.
- ▪AI reduces the mental effort required for structured thinking processes like decomposition, iteration, and hypothesis testing.
- ▪Fast thinking heuristics such as satisficing and anchoring are influenced by AI, which provides quick, fluent answers that can shape subsequent reasoning.
- ▪Human judgment remains essential for abstraction, systems thinking under pressure, and identifying domain-specific edge cases that AI may miss.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3923257) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } vladimir ivanov Posted on May 17 Mental Algorithms: How AI Changes the Cost of Thinking #ai #learning #productivity Most people assume the difference between good thinking and bad thinking is intelligence. It isn't. More often, it comes down to cost — how much mental effort it takes to arrive at a useful answer. Some answers require slow, deliberate reasoning. Others emerge almost instantly through pattern recognition or experience. Human thinking isn't a single process.
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