This past Monday NewsGuard, a journalism rating platform that also analyzes and identifies AI-driven misinformation, announced it had identified hundreds of junk news sites powered by generative AI. The focus of NewsGuard’s release was how major brands were funding these spam sites through the indifference of programmatic advertising, but what I found interesting was how low that number was – 250 or so sites. I’d have guessed they’d find tens of thousands of these bottom feeders – but maybe I’m just too cynical about the state of news on the open web. I have a hunch my cynicism will be rewarded in due time, once the costs of AI decline and the inevitable economic incentives that have always driven hucksters kick in.
Given 250 is a manageable number for a mere mortal, I decided to ask the good folks at NewsGuard, where I’m an advisor, for a copy of their listings. Nothing like a tour through the post-apocalyptic hellscape of our AI future, right?
I recently caught up with a pal who happens to be working at the center of the AI storm. This person is one of the very few folks in this industry whose point of view I explicitly trust: They’ve been working in the space for decades, and possess both a seasoned eye for product as well as the extraordinary gift of interpretation.
This gave me a chance to ask one of my biggest “stupid questions” about how we all might use chatbots. When I first grokked LLM-driven tools like ChatGPT, it struck me that one of its most valuable uses would be to focus its abilities on a bounded data set. For example, I’d love to ask a chatbot like Google Bard to ingest the entire corpus of Searchblog posts, then answer questions I might have about, say, the topics I’ve written about the most. (I’ve been writing here for 20 years, and I’ve forgotten more of it than I care to admit). This of course only scratches the surface of what I’d want from a tool like Bard when combined with a data set like the Searchblog archives, but it’s a start.
Not since the iPhone, in the mid aughts. No, not since the rise of the browser and the original web, in the early nineties. No, not since the introduction of the PC, in the 1980s. Ah hell, honestly, not since the Gutenberg printing press in the 15th century – or, fuck it, let’s just go there: Not since the invention of language, which as far as we know marked the moment when homo sapiens first branched from its primate cousins.
That’s how big a deal AI is, according to academics, politicians, and a rapt technology and capital ecosystem starved for The Next Big Thing.
A few weeks ago I was genuinely thunderstruck. My co-editor atP&G Signal (thanks Stan!) introduced me to a new company – one that promised to give consumers control over their personal data in new and innovative ways. At first I was skeptical – I’d seen quite a few “personal data lockers” come and go over the past decade or so. I even invested in one way back in 2012. Alas, that didn’t work out.
For as long as I can remember, I’ve been writing –over andover andover – about how the Internet’s central problem is the lack of leverage that consumers have over the data they co-create with the hundreds of apps, sites, and platforms they use. But data lockers never got any traction – most were confusing to install and run, and they all suffered from a lack of tangible consumer benefits. Sure, having a copy of all my personal data sounds great, but in the end, what can it do for me? Up till now, the answer was not much.