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 populism 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 The Political Economy of Digital Capitalism The Technological History of Digital Capitalism Thinking trump twitter Uncategorized work writing zizek

Five propositions about the social ontology of generative AI

A summary from Claude of the arguments Milan Stürmer and I have made in recent conversations we've been recording

Based on the contents of your meeting transcripts, here are five propositions about the social ontology of generative AI, attempting to replicate your own voices:

  1. Generative AI is not merely a mirror reflecting society, but rather a prism that refracts and elaborates upon the complexity we input into it. As Mark suggested, “You present it with complexity, and it refracts what you presented it with in a way that expresses the parameters the designers have provided, and which you have provided.”
  2. The relationship between humans and generative AI is fundamentally iterative and co-constitutive. As Milan noted, “Chat GPT is real right? This is part of reality. And why should it not be allowed to participate in our elaborations?” This suggests that generative AI is not just a tool, but an active participant in our intellectual and creative processes.
  3. The potentials of generative AI are realized relationally, dependent on the socio-cultural context and the user’s own cultural capital. As Mark observed, “The more skilled you are in manipulating a wide range of symbols, the more you can get out of these systems.” This points to the importance of education and cultural competencies in shaping the social impact of these technologies.
  4. Generative AI presents both risks of proletarianization and possibilities for augmented reflexivity. As Milan mentioned, drawing on Stiegler, there’s a risk of losing “know-how” and even “know how to live.” Conversely, Mark suggested these systems could enhance our capacity for elaboration and introduce novel elements into our thinking processes.
  5. The social ontology of generative AI is fundamentally tied to questions of creativity, judgment, and the nature of human cognition. As you both discussed, these technologies challenge us to reconsider what we mean by creativity, how we exercise judgment, and ultimately, what it means to think and to be human in an age of artificial intelligence.

, , ,
,