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ai-literacy
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Heuristic AI literacy is not a training problem Treat AI literacy as a durable mental-model shift, not an event — the judgement required to use AI well cannot be installed through a workshop. Pattern AI's most dangerous failure mode is confident wrongness AI's most dangerous failure is not silence but fluent, authoritative output that is wrong — making error detection a skilled, human task that cannot be deferred to the tool. Heuristic Users assume AI has access to information it does not have Users routinely overestimate the information AI has access to, treating it as if it were working from a complete picture; this overestimate compounds with AI fluency to produce misplaced trust. Heuristic Hire for durable AI judgement, not transient AI mechanics AI skills split into durable judgement — when to use AI, how to structure problems for it, how to verify output, where not to use it — and transient mechanics — specialist prompt engineering, bespoke pipelines platforms will absorb. Hire and train for the first, be sceptical of the second. Heuristic Leadership team AI fluency must be collective, not individual A single AI-fluent leader in an otherwise-unfluent team creates strategic blind spots rather than an advantage; fluency has to be built across the leadership team together, because uneven adoption at the top propagates as inconsistent AI strategy below. Heuristic Use a frontier LLM as a personal AI mentor Use a frontier LLM as a conversational partner for learning about AI itself — ask it about its capabilities, limitations and appropriate use cases while doing real work with it. The self-directed, contextualised learning this produces outperforms the structured training programmes it replaces. Heuristic Polish and volume no longer signal effort The signals that used to tell reviewers about work quality — volume, polish, comprehensiveness — correlated with effort because effort was scarce; with AI the correlation breaks, and the questions that still discriminate are about process.