The AI trust crisis 14th December 2023 Dropbox added some new AI features. In the past couple of days these have attracted a firestorm of criticism. Benj Edwards rounds it up in Dropbox spooks users with new AI features that send data to OpenAI when used. The key issue here is that people are worried that their private files on Dropbox are being passed to OpenAI to use as training data for their models—a claim that is strenuously denied by Dropbox. As far as I can tell, Dropbox built some sensible features—summarize on demand, “chat with your data” via Retrieval Augmented Generation—and did a moderately OK job of communicating how they work... but when it comes to data privacy and AI, a “moderately OK job” is a failing grade. Especially if you hold as much of people’s private data as Dropbox does! Two details in particular seem really important. Dropbox have an AI principles document which includes this: Customer trust and the privacy of their data are our foundation. We will not use customer data to train AI models without consent. They also have a checkbox in their settings that looks like this: Update: Some time between me publishing this article and four hours later, that link stopped working. I took that screenshot on my own account. It’s toggled “on”—but I never turned it on myself. Does that mean I’m marked as “consenting” to having my data used to train AI models? I don’t think so: I think this is a combination of confusing wording and the eternal vagueness of what the term “consent” means in a world where everyone agrees to the terms and conditions of everything without reading them. But a LOT of people have come to the conclusion that this means their private data—which they pay Dropbox to protect—is now being funneled into the OpenAI training abyss. People don’t believe OpenAI # Here’s copy from that Dropbox preference box, talking about their “third-party partners”—in this case OpenAI: Your data is never used to train their internal models, and is deleted from third-party servers within 30 days. It’s increasing clear to me like people simply don’t believe OpenAI when they’re told that data won’t be used for training. What’s really going on here is something deeper then: AI is facing a crisis of trust. I quipped on Twitter: “OpenAI are training on every piece of data they see, even when they say they aren’t” is the new “Facebook are showing you ads based on overhearing everything you say through your phone’s microphone” Here’s what I meant by that. Facebook don’t spy on you through your microphone # Have you heard the one about Facebook spying on you through your phone’s microphone and showing you ads based on what you’re talking about? This theory has been floating around for years. From a technical perspective it should be easy to disprove: Mobile phone operating systems don’t allow apps to invisibly access the microphone. Privacy researchers can audit communications between devices and Facebook to confirm if this is happening. Running high quality voice recognition like this at scale is extremely expensive—I had a conversation with a friend who works on server-based machine learning at Apple a few years ago who found the entire idea laughable. The non-technical reasons are even stronger: Facebook say they aren’t doing this. The risk to their reputation if they are caught in a lie is astronomical. As with many conspiracy theories, too many people would have to be “in the loop” and not blow the whistle. Facebook don’t need to do this: there are much, much cheaper and more effective ways to target ads at you than spying through your microphone. These methods have been working incredibly well for years. Facebook gets to show us thousands of ads a year. 99% of those don’t correlate in the slightest to anything we have said out loud. If you keep rolling the dice long enough, eventually a coincidence will strike. Here’s the thing though: none of these arguments matter. If you’ve ever experienced Facebook showing you an ad for something that you were talking about out-loud about moments earlier, you’ve already dismissed everything I just said. You have personally experienced anecdotal evidence which overrides all of my arguments here.

One consistent theme I’ve seen in conversations about this issue is that people are much more comfortable trusting their data to local models that run on their own devices than models hosted in the cloud. The good news is that local models are consistently both increasing in quality and shrinking in size.

York points to a 1946 U.S. Supreme Court decision, Marsh v. Alabama, which held that private entities can become sufficiently large and public to require them to be subject to the same Constitutional constraints as government entities. Though York says this ruling has “not as of this writing been applied to the quasi-public spaces of the internet”

even if YouTube were treated as an extension of government due to its size and required to retain every non-criminal video uploaded to its service, it would make as much of a political statement elsewhere, if not more. In France and Germany, it — like any other company — must comply with laws that require the removal of hate speech, laws which in the U.S. would be unconstitutional

Several European countries have banned Google Analytics because it is impossible for their citizens to be protected against surveillance by American intelligence agencies.

TikTok has downplayed the seriousness of its platform by framing it as an entertainment venue. As with other platforms, disinformation on TikTok spreads and multiplies. These factors may have an effect on how people vote. But the sudden alarm over yet-unproved allegations of algorithmic meddling in TikTok to boost Chinese interests is laughable to those of us who have been at the mercy of American-created algorithms despite living elsewhere. American state actors have also taken advantage of the popularity of social networks in ways not dissimilar from political adversaries.

what York notes is how aligned platforms are with the biases of upper-class white Americans; not coincidentally, the boards and executive teams of these companies are dominated by people matching that description.

It should not be so easy to point to similarities in egregious behaviour; corruption of legal processes should not be so common. I worry that regulators in China and the U.S. will spend so much time negotiating which of them gets to treat the internet as their domain while the rest of us get steamrolled by policies that maximize their self-preferencing.

to ensure a clear set of values projected into the world. One way to achieve that is to prefer protocols over platforms.

Yes, the country’s light touch approach to regulation and generous support of its tech industry has brought the world many of its most popular products and services. But it should not be assumed that we must rely on these companies built in the context of middle- and upper-class America.