The Selfish (AI) Model (crocccante-engineering.vercel.app)

This piece reframes LLMs as "selfish models": not biological organisms but high-speed vehicles for memes. Drawing on Dawkins' idea of the selfish gene and his coinage of "meme," it argues that modern models (GPT, Claude, Gemini, LLaMA) internalize and compress cultural patterns—linguistic motifs, reasoning shortcuts, stylistic quirks and ideological biases—into billions of parameters. Trained on trillions of words, models don’t invent from scratch; they statistically remix the most persistent fragments of our culture, surfacing the memes that best replicate in prompts and outputs. That framing matters because it shifts how we think about model behavior, risk and governance: LLMs can amplify, accelerate and iterate cultural ideas far faster than human-only transmission, creating feedback loops that select for memetic fitness rather than truth or ethics. Practically, this highlights why dataset curation, evaluation of emergent selection pressures, adversarial memetics, and alignment strategies are critical—models will preferentially reproduce patterns that survive training and deployment. Seeing AI as a new substrate for meme evolution clarifies both its creative power and its potential to propagate biases and viral ideas, underscoring the need for deliberate stewardship of the memepool we build into these systems.