Yes, there is an economic incentive to the election of Trump by those at the commanding heights of Silicon Valley power. But to reduce it purely to materialism is missing a strong part of the story, namely about AI's own operation as an ideological apparatus which encourages power consolidation.

Artificial intelligence is a threat to educational institutions – as deeply flawed as these may be – not because it's some incredible technological achievement that's more powerful that the human mind (hahahahahahahahahahahahahahaha); but because it is the manifestation of a series of reactionary political beliefs. AI is inextricably bound up in ideologies and practices that seek to undermine unions, exploit labor, re-inscribe racial and economic hierarchies, and centralize control – of knowledge and knowing ("intelligence" in all its various military and eugenicist histories) – in the hands of a few giant technology corporations. (Folks, that's fascism.)

Today I hope to persuade you that the same thing that happened to aviation is happening with the Internet. Here we are, fifty years into the computer revolution, at what feels like our moment of greatest progress. The outlines of the future are clear, and oh boy is it futuristic.

But we're running into physical and economic barriers that aren't worth crossing.

We're starting to see that putting everything online has real and troubling social costs.

And the devices we use are becoming 'good enough', to the point where we can focus on making them cheaper, more efficient, and accessible to everyone.

So despite appearances, despite the feeling that things are accelerating and changing faster than ever, I want to make the shocking prediction that the Internet of 2060 is going to look recognizably the same as the Internet today.

Unless we screw it up.

And I want to convince you that this is the best possible news for you as designers, and for us as people.

In a recent earnings call Sundar Pichai claimed that at Google now 25% of Code is AI generated (“and then reviewed and accepted by engineers”). In the AI boosterism parts of the web (so basically X and LinkedIn) this number was celebrated: Even Google does AI code generation. So if your whole startup is just ChatGPT in a trenchcoat, you’re basically at the industry standard, right?

Let’s not be cynical here and point at Google’s not exactly stellar recent track record when it comes to great products and software, but let’s ask us where that number comes from and what it means.

I went to the UX Brighton conference yesterday.

The quality of the presentations was really good this year, probably the best yet. Usually there are one or two stand-out speakers (like Tom Kerwin last year), but this year, the standard felt very high to me.

But…

The theme of the conference was UX and “AI”, and I’ve never been more disappointed by what wasn’t said at a conference.

As OpenAI and Meta introduce LLM-driven searchbots, I'd like to once again remind people that neither LLMs nor chatbots are good technology for information access. [...]

If someone uses an LLM as a replacement for search, and the output they get is correct, this is just by chance. Furthermore, a system that is right 95% of the time is arguably more dangerous tthan one that is right 50% of the time. People will be more likely to trust the output, and likely less able to fact check the 5%.

But even if the chatbots on offer were built around something other than LLMs, something that could reliably get the right answer, they'd still be a terrible technology for information access.

Dans une récente mise à jour de ses conditions d’utilisation, Steam précise que les « gamers achètent une licence et non le jeu lui-même. » La manœuvre est destinée à se mettre en conformité avec les dispositions d’une nouvelle loi californienne contre la publicité mensongère. Le tableau ravive le débat sur la notion de propriété numérique à l’ère des abonnements qui tuent les copies physiques.

“we found no evidence of formal reasoning in language models …. Their behavior is better explained by sophisticated pattern matching—so fragile, in fact, that changing names can alter results by ~10%!”

Maybe someday Altman’s ideas about AI will prove out, but for now, his approach is textbook Silicon Valley mythmaking.

But research is showing that AI generation may be even more resource-intensive than originally thought. Imagine that you want to ask an AI program to write up a 100-word email for you. You get an almost instant response, but what you don’t see are the intensive computing resources that went into creating that email. At the AI data center, generating just two of those emails could use as much energy as a full charge on the latest iPhone. And according to a Pew Research Center study, that 100-word email could use up a whole bottle of water for the cooling that’s needed at data centers.