In a nutshell, this explains why Apple is “behind” with AI, but actually isn’t.
It’s remarkable the consistency with which this pattern repeats, yet even people who consider themselves Apple enthusiasts don’t see it. Tech competitors “race ahead” with an iteration of some technology, while Apple seemingly languishes. Apple is doomed. Then Apple comes out “late” with their version of it, and the initial peanut gallery reception pronounces it too little, too late.
Then within a couple of years, Apple’s version is the gold standard and the others -those cutting-edge innovators- race to catch up, because “first” is often also “half-baked.”
In the news this week, it was exposed that RFK Jr’s “Make America Healthy Again” report was evidently an AI-produced document, replete with hallucinations, most notably in the bibliography, and of course it was. This is what happens when the current cohort of AI models are uncritically used to produce a desired result, without any understanding of how profoundly bad these AI models are. When I read about this in the news, I decided to experiment with it myself. Using MS Copilot -in commercial release as part of MS Word- I picked a subject and asked for a report taking a specific, dubious position on it, with citations and a bibliography. After it dutifully produced the report, I started checking the bibliography, and one after another, failed to find the research papers that Copilot used to back the position taken. I didn’t check all the references, so it’s possible some citations were real, but finding several that weren’t was sufficient to bin the whole thing. It’s bad enough when humans intentionally produce false and misleading information, but when a stock office product will do it for you with no disclaimers or warnings, should that product really be on the market? I also once asked ChatGPT to write a story about green eggs and ham, in the style of Dr. Seuss. It then plaigerized the actual Seuss story, almost verbatim, in a clear abuse of copyright law. This is the stuff that Apple is supposedly trailing behind.
So the report here that Apple is developing AI but, unlike their “cutting edge” competitors, not releasing something that produces unreliable garbage, suggests that no, they’re not behind. They’re just repeating the same pattern again of carefully producing something of high quality and reliability, and in a form that is intuitively useful, rather than a gimmicky demonstration that they can do a thing, whether it’s useful or not. Eventually they’ll release something that consistently produces reliable information, and likely does so while respecting copyright and other intellectual property rights. The test will be that not only will it be unlikely to hallucinate in ways that mislead or embarrass its honest users, it will actually disappoint those with more nefarious intent. When asked to produce a report with dubious or false conclusions, it won’t comply like a sociopathic sycophant. It will respond by telling the user that the reliable data not only doesn’t support the requested position, but actually refutes it. Hopefully this will be a feature that Apple uses to market their AI when it’s released.
P.S. As a corollary, the other thing that Apple is likely concerned with (perhaps uniquely so) is AI model collapse. This is the feedback loop where AI training data is scooped up from sources that include AI-produced hallucinations, not only increasing the likelihood that the bad data will be repeated, but reducing any ability for the AI model to discern good data from bad. Collapse occurs when the model is so poisoned with bad data that even superficial users find the model to be consistently wrong and useless. Effectively every query becomes an unamusing version of that game where you playfully ask for “wrong answers only.” Presumably the best way to combat that is to train the AI as you would a human student: start by giving it information sources known to be reliable, and eventually train it to discern those sources on its own. That takes more time. You can’t just dump the entire internet into it and tell it that the patterns repeated the most are most likely correct.
P.P.S. I just repeated the above experiment in Pages, using Apple’s link to Chat GPT. It also produced hallucinated references. I just chased down the first citation in the bibliography it created. Searching for the cited article didn’t turn up anything. I did find the cited journal, went to it and searched for the cited title, got nothing. Searched for the authors, got nothing. Finally, I browsed to find the issue supposedly containing the referenced article, and that article does not exist. So Apple gets demerits for subbing in ChatGPT in their uncharacteristic worry that they not be perceived as being “late.” This part does not fit their usual pattern, with the exception perhaps of their hastened switch to Apple Maps, based largely at first on third-party map data. In the long run, their divorce from Google maps was important, as location services was rapidly becoming a core OS function, not just a sat nav driving convenience that can adequately be left to third party apps. The race to use AI is perhaps analog, but the hopefully temporary inclusion of ChatGPT’s garbage should be as embarrassing as those early Apple Maps with bridges that went underwater, etc.
