『Do You Solve Problems Fast Or Slow?』のカバーアート

Do You Solve Problems Fast Or Slow?

Do You Solve Problems Fast Or Slow?

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 Mathematician David Bessis claims we need system three thinking, a super-slow mode where you refuse to give up on wrong intuitions until you understand why they misfired. David Olney pushes back, arguing this is just what proper slow thinking looks like when you give it the time it needs. The hosts explore Kahneman’s fast and slow thinking framework, revealing why your quickest answers are probably just pattern matching from last Tuesday. Your brain serves up what worked before, which means the more you rely on speed, the less you adapt to what’s changed. Steve and David attempt to recreate Monty Python’s Argument Clinic with ChatGPT and discover AI is designed to be helpful, not challenging. Mark Schaefer raises the provocative question about what happens when AI becomes your customer, making purchasing decisions based on optimised data rather than human emotion. David posts a routine LinkedIn job update and old contacts emerge from the woodwork with congratulations. The hosts explore why good news triggers reconnection and whether you could deliberately use this pattern to get back on people’s radars. Edward de Bono’s 1982 Olivetti advertisement promises simple questions and simple answers, prefiguring Apple’s strategy by decades while being remarkably dull as advertising. Get ready to take notes. Talking About Marketing podcast episode notes with timecodes 01:15 Person This segment focusses on you, the person, because we believe business is personal.When Your Brain’s Fastest Answer is Yesterday’s Solution Mathematician David Bessis appeared on EconTalk arguing for what he calls “system three thinking,” a super-slow mode beyond Kahneman’s famous fast and slow framework. When mathematicians catch their intuition being wrong, Bessis suggests they don’t reject it. Instead, they explore it, unpacking why the intuition misfired, playing back and forth between gut feeling and formal logic until they agree. This process might take five minutes or fifty years. David Olney pushes back. He argues Bessis hasn’t created a new system, he’s just described what system two thinking actually requires when you give it proper attention. The real insight isn’t about speed categories but understanding what your brain is actually doing when you think fast. System one thinking is pattern matching. Your brain searches memory for what worked before and serves it up as the answer. The problem? The more you rely on quick thinking, the more you can only repeat yesterday, last Tuesday, six months ago. You become brilliant at applying solutions to problems that no longer exist in quite the same form. You lose the ability to spot when things have changed enough to need fresh thinking. The hosts explore when fast thinking serves you well. Steve recalls his radio days, where he needed a hundred responses available in a tenth of a second. That’s system one at its best, drawing on a deep well of experience. But those new responses? They came from time spent away from the microphone, when his brain could think at whatever pace it needed to generate something genuinely different. This matters for business operators who pride themselves on quick decisions. Your speed might be your biggest blind spot. Every time you solve a problem instantly, ask yourself whether you’re actually solving today’s problem or yesterday’s problem wearing different clothes. 14:15 Principles This segment focusses principles you can apply in your business today.When AI Becomes Your Customer Steve and David decide to have some fun with ChatGPT, attempting to recreate Monty Python’s famous Argument Clinic sketch. The exercise reveals something unexpected about how AI responds. When they try to get ChatGPT to simply contradict everything they say, it keeps trying to be helpful, to add value, to assist rather than argue. Even when explicitly instructed to argue, it wants to problem-solve. The hosts find this both amusing and revealing. AI tools are fundamentally designed to be agreeable and helpful. They’re not built for genuine disagreement or challenge. This creates an interesting blind spot when you’re using AI to test ideas or get feedback on your thinking. The conversation shifts to Mark Schaefer‘s provocative question about what happens when AI becomes your customer. If AI agents start making purchasing decisions on behalf of humans, searching for products, comparing options, and completing transactions without human involvement in each step, how does marketing change? Schaefer argues this represents a fundamental shift. You’re no longer persuading humans. You’re optimising for AI decision-making processes. The psychology of marketing becomes the logic of algorithms. Emotional appeals matter less than structured data. Brand storytelling competes with technical specifications and price comparisons. David raises the deeper concern. If AI is making decisions based on what worked before, searching patterns from ...
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