Raiding the inarticulate since 2010

accelerated academy acceleration agency AI Algorithmic Authoritarianism and Digital Repression archer Archive Archiving artificial intelligence automation Becoming Who We Are Between Post-Capitalism and Techno-Fascism big data blogging capitalism ChatGPT claude Cognitive Triage: Practice, Culture and Strategies Communicative Escalation and Cultural Abundance: How Do We Cope? Corporate Culture, Elites and Their Self-Understandings craft creativity critical realism data science Defensive Elites Digital Capitalism and Digital Social Science Digital Distraction, Personal Agency and The Reflexive Imperative Digital Elections, Party Politics and Diplomacy digital elites Digital Inequalities Digital Social Science Digital Sociology digital sociology Digital Universities elites Fragile Movements and Their Politics Cultures generative AI higher education Interested labour Lacan Listening LLMs margaret archer Organising personal morphogenesis Philosophy of Technology platform capitalism platforms Post-Democracy, Depoliticisation and Technocracy post-truth psychoanalysis public engagement public sociology publishing Reading realism reflexivity scholarship sexuality Shadow Mobilization, Astroturfing and Manipulation Social Media Social Media for Academics social media for academics social ontology social theory sociology technology The Content Ecosystem The Intensification of Work theory The Political Economy of Digital Capitalism The Technological History of Digital Capitalism Thinking trump twitter Uncategorized work writing zizek

The GAI literacy divide increasingly opening up

Ethan Mollick has captured in a paragraph what I’ve spent thousands of words, arguably a whole book, trying to say:

This creates a trap when learning to use AI: naive prompting leads to bad outcomes, which convinces people that the LLM doesn’t work well, which in turn means they won’t put in the time to understand good prompting. This problem is compounded by the fact that I find that most people only use the free versions of LLMs, rather than the much more powerful GPT-4 or Gemini Advanced. The gap between what experienced AI users know AI can do and what inexperienced users assume is a real and growing one. I think a lot of people would be surprised about what the true capabilities of even existing AI systems are, and, as a result, will be less prepared for what future models can do.

https://www.oneusefulthing.org/p/captains-log-the-irreducible-weirdness