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We should absolutely use the lessons we learned about how the web unfolded to inform our predictions about AI. Our naivete back in 1996 could be forgiven. Not
by gdulli 6mo ago
We should absolutely use the lessons we learned about how the web unfolded to inform our predictions about AI.
Our naivete back in 1996 could be forgiven. Not applying the lessons since then and anticipating how subsequent technologies will be captured and used against us is irresponsible.
- MattDamonSpace 6mo agoOkay so give me an application of a web lesson
- cal_dent 6mo agoThe only relevant lesson is that predictions are likely to be more wrong than right tbh
- gdulli 6mo agoThe enshittification we're bathing in every day is the lesson that matters.
- salawat 6mo agoAnything built to democratize, will inevitably be centralized, scaled until it's scaler's lack of care to chase maximum profit becomes a massive problem, and regulated until it is de-democratized. Example: Finance, file-sharing, recorders, AI vs. libraries, SaaS vs. Software libraries/standalone deployments. >If investors are involved, kiss any altruistic intent goodbye. Bait-&-switch->enshittification is a matter of when, not if. >Solutions are not the goal of work in the United States. Attracting capital, and leaving someone else holding the bag is. Dot coms, 2008, end of ZIRP. >You cannot fix the system from within. (Or as Einstein said, problems cannot be solved by thinking on the same level that created them) FLOSS is architecturally unsound as evidenced by the existence of AI models, and the relative impossibility to seemingly maintain development efforts without eventual corporate co-option. GPL, AGPL have managed to carve out some minimal system stacks for the public, but with AI companies, the time has come where the System (the judiciary of the U.S. at least, is signalling that Copyright only exists if a corporate actor's legal team is sufficiently funded to argue it does. Altruism, as noble as it is; cannot persist forever without nourishment. If you can't recognize these things, this is more indicative of a problem to observe than a lack of data to learn from.