Something I've started to see happen but never mentioned is the effect automated detection has on systems: As detection becomes more automated (previously authored algorithms, now with large AI models), there's less cash available for individual case workers, and more trust at the managerial level on automatic detection. This leads to false positives turning into major frustrations since it's hard to get in touch with a person to resolve the issue. When dealing with businesses it's frustrating, but as these get more used in law enforcement, this could be life ruining.
For instance - I got flagged as illegal reviews on Amazon years ago and spent months trying to make my case to a human. Every year or so I try to raise the issue again to leave reviews, but it gets nowhere. Imagine this happening for a serious criminal issue, with the years long back log on some courts, this could ruin someones life.
More automatic detection can work (and honestly, it's inevitable) but it's got to acknowledge that false positives will happen and allocate enough people to resolve those issues. As it stands right now, these detection systems get built and immediately human case workers get laid off, there's this assumption that detection systems REPLACE humans, but it should be that they augment and focus human case workers so you can do more with less - the human aspect needs to be included in the budgeting.
But the incentives aren't there, and the people making the decisions aren't the ones working the actual cases so they aren't confronted with the problem. For them, the question is why save $1m when you could save $2m? With large AI models making it easier and more effective to build automated detection I expect this problem to get significantly worse over the next years.
Update this to a world where every corner of your life is controlled by a platform monopoly that doesn't even provide the most bare-bones customer service and yeah, this is going to get a lot worse before it gets better.
No need for presumption here: OpenAI is quite transparent about the fact that they retain data for 30 days and have employees and third-party contractors look at it.
https://platform.openai.com/docs/models/how-we-use-your-data
> To help identify abuse, API data may be retained for up to 30 days, after which it will be deleted (unless otherwise required by law).
https://openai.com/enterprise-privacy/
> Our access to API business data stored on our systems is limited to (1) authorized employees that require access for engineering support, investigating potential platform abuse, and legal compliance and (2) specialized third-party contractors who are bound by confidentiality and security obligations, solely to review for abuse and misuse.
And how. I'd lean towards no. Where we're headed feels like XKEYSCORE on steroids. I'd love to take the positive, optimistic bent on this, but when you look at where we've been combined with the behavior of the people in charge of these systems (to be clear, not the researchers or engineers, but c-suite), hope of a neutral, privacy-first future seems limited.
Meanwhile, the anti anti-establishment Republican Party since 2016 who cried about big tech turned out to be the biggest pro-establishment fans, giving Elmo an office in a white house and Zucc bending a knee to avoid prosecution.
With these new systems, Id rather have smart people who only work in US defensive forces because of a sense of duty (considering they could get paid much more in the private sector) in charge.
If what you say is true, there would have been more than one honorable person to step up and say "hey, wait a minute." In the case of XKEYSCORE, there was precisely one, and he's basically been marooned in Russia for over a decade (and funny enough, XKEYSCORE still exists and is likely still utilized in the exact same way [1]).
Never underestimate the effect the threat of character destruction—and by extension, loss of income—will have on even the most honorable person's psyche. In situations involving matters like these, it's always far more likely that the "pressure" will be ratcheted up until the compliance (read: keep your mouth shut) rate is 100%.
[1] https://documents.pclob.gov/prod/Documents/OversightReport/e...
It's not a search if we don't find anything, and it's not a seizure if we charge the money with the crime. These are court approved arguments, so they must be correct interpretations.
Point is: modern bureaucrats have proven that they are absolutely willing to abuse power, even in the best of times when there is no real domestic political strife.
Then Green seems to immediately forget the point they just made, and proceed to talk about PCC as if it were something other than just another technical guarantee. PCC only helps to increase confidence that the software running on the server is the software Apple intended to be there. It doesn't give me any guarantees about where else my data might be transferred from there, or whether Apple will only use it for purposes I'm okay with. PCC makes Apple less vulnerable to hacks, but doesn't make them any more transparent or accountable. In fact, to the extent that some hackers hack for pro-social purposes like exposing corporate abuse, increased security also serves as a better shield against accountability. Of course, I'm not suggesting that we should do away with security to achieve transparency. I am, however, suggesting that transparency, moreso than security, is the major unaddressed problem here. I'd even go so far as to say that the woeful state of security is enabled in no small part by lack of transparency. If we want AI to serve society, then we must reverse the extreme information imbalance we currently inhabit wherein every detail of each person's life is exposed to the service provider, but the service provider is a complete black-box to the user. You want good corporate actors? Don't let them operate invisibly. You want ethical tech? Don't let it operate invisibly.
(Edit: formatting)
I think Apple recently changed their stance on this. Now, they say that "source code for certain security-critical PCC components are available under a limited-use license." Of course, would have loved it if the whole thing was open source. ;)
https://github.com/apple/security-pcc/
> The goal of this system is to make it hard for both attackers and Apple employees to exfiltrate data from these devices.
I think Apple is claiming more than that. They are saying 1/ they don't keep any user data (data only gets processed during inference), 2/ no privileged runtime access, so their support engineers can't see user data, and 3/ they make binaries and parts of the source code available to security researchers to validate 1/ and 2/.
You can find Apple PCC's five requirements here: https://security.apple.com/documentation/private-cloud-compu...
Note: Not affiliated with Apple. We read through the PCC security guide to see what an equivalent solution would look like in open source. If anyone is interested in this topic, please hit me up at ozgun @ ubicloud . com.
Yes. I made that point a few weeks ago. The legal concept of principal and agent applies.
Running all content through an AI in the cloud to check for crimethink[1] is becoming a reality. Currently proposed:
- "Child Sexual Abuse Material", which is a growing category that now includes AI-generated images in the US and may soon extend to Japanese animation.
- Threats against important individuals. This may be extended to include what used to be considered political speech in the US.
- Threats against the government. Already illegal in many countries. Bear in mind that Trump likes to accuse people of "treason" for things other than making war against the United States.
- "Grooming" of minors, which is vague enough to cover most interactions.
- Discussing drugs, sex, guns, gay activity, etc. Variously prohibited in some countries.
- Organizing protests or labor unions. Prohibited in China and already searched for.
Note that talking around the issue or jargon won't evade censorship. LLMs can deal with that. Run some ebonics or leetspeak through an LLM and ask it to translate it to standard English. Translation will succeed. The LLM has probably seen more of that dialect than most people.
"If you want a vision of the future, imagine a boot stepping on a face, forever" - Orwell
Your point is worth reiterating.
> This future worries me because it doesn’t really matter what technical choices we make around privacy. It does not matter if your model is running locally, or if it uses trusted cloud hardware — once a sufficiently-powerful general-purpose agent has been deployed on your phone, the only question that remains is who is given access to talk to it. Will it be only you? Or will we prioritize the government’s interest in monitoring its citizens over various fuddy-duddy notions of individual privacy.
I do think there are interesting policy questions there. I mean it could hypothetically be mandated that the government must be given access to the agent (in the sense that we and these companies exist in jurisdictions that can pass arbitrary laws; let’s skip the boring and locale specific discussion of whether you think your local government would pass such a law).
But, on a technical level—it seems like it ought to be possible to run an agent locally, on a system with full disk encryption, and not allow anyone who doesn’t have access to the system to talk with it, right? So on a technical level I don’t see how this is any different from where we were previously. I mean you could also run a bunch of regex’s from the 80’s to find whether or not somebody has, whatever, communist pamphlets on their computers.
There’s always been a question of whether the government should be able to demand access to your computer. I guess it is good to keep in mind that if they are demanding access to an AI agent that ran on your computer, they are basically asking for a lossy record of your entire hard drive.
We're already there. AI or not doesn't affect the fact that smartphones gather, store, and transmit a great deal of information about their users and their users' actions and interests.
Anyway the idea of what’s a reasonable search in the US has been whittled away to almost nothing, right? “The dog smelled weed on your hard drive.” - A cop, probably.
But while not revealing user input, it would still reveal the outputs of the model to the company. And yeah, as the article mentions, unfortunately this kind of thing (MPC or fully-homomorphic encryption) probably won't be feasible for the most powerful ML models.
I wrote about Apple's Private Cloud Compute last year; for the foreseeable future, I still think server-side Confidential Computing is the most practical way to do processing without huge privacy risks: https://www.anjuna.io/blog/apple-is-using-secure-enclaves-to...
An app I'm building uses LLMs to process messages. I don’t want the unencrypted message to hit my server - and ideally I wouldn’t have the ability to decrypt it. But I can’t communicate directly from client -> LLM Service without leaking the API key.
There is a way you can do that right now: the OpenAI WebRTC API introduced the idea of an "ephemeral key": https://platform.openai.com/docs/guides/realtime-webrtc
This provides a way for your server to create a limited-time API key for a user which their browser can then use to talk to OpenAI's API directly without proxying through you.
I love this idea, but I want it for way more than just the WebRTC API, and I'd like it for other API providers too.
My ideal version would be a way to create an ephemeral API key that's only allowed to talk to a specific model with a specific pre-baked system prompt (and maybe tool configuration and suchlike) and that only works for a limited time and has a limited token budget.
1. E2E encryption does work
2. But phones can send plaintext back to the cloud to get help doing AI things
3. And we tend not to know because it’s all “assisstance”
But the solution like anything is pricing. I mean yet again (uber, Airbnb) billions of dollars of VC money is used as subsidy so my photos can get OCR’d.
If phones said “hey for a dollar fifty I can work out what the road sign says behind your dogs head in 32 photos your mum sent you last week” I think we woukd see a different threat landscape
This is - again - unsustainable cash spending distorting markets and common sense. If the market was “we can OCR and analyse these insurance claims” the. Things like privacy and encryption would be first class requirements and harder to sell and build.
By spending a billion they can sell services to people without regulators to ask awkward questions and then they hope step 3. Profit.
I short not even AI can spot patterns in encrypted data, it’s only when plaintext gets sent around in the hope of profit do we see a threat. That’s seems a simple fix if not an easy one
I see "AI" tools being used even more in the future to permanently tie people to monthly recurring billing services for things like icloud, microsoft's personal grade of office365, google workspace, etc. You'll pay $15 a month forever, and the amount of your data and dependency on the cloud based provider will mean that you have no viable path to ever stop paying it without significant disruption to your life.
> Apple can’t rely on every device possessing enough power to perform inference locally. This means inference will be outsourced to a remote cloud machine.
If you go look at Apple's site https://www.apple.com/apple-intelligence/ and scroll down, you get:
Apple Intelligence is compatible with these devices. iPhone 16 A18 iPhone 16 Plus A18 iPhone 16 Pro Max A18 Pro iPhone 16 Pro A18 Pro iPhone 15 Pro Max A17 Pro iPhone 15 Pro A17 Pro iPad Pro M1 and later iPad Air M1 and later iPad mini A17 Pro MacBook Air M1 and later MacBook Pro M1 and later iMac M1 and later Mac mini M1 and later Mac Studio M1 Max and later Mac Pro M2 Ultra
If you don't have one of those devices, Apple did the obvious thing and disabled features on devices that don't have the hardware to do it.
While Apple has this whole private server architecture, they're not sending iMessages off device for summarization, that's happening on device.
Doing this encrypted is very slow: without hardware acceleration or special tricks, running the circuit is 1 million times slower than unencrypted, or about 1ms for a single gate. (https://www.jeremykun.com/2024/05/04/fhe-overview/)
When you think about all the individual logic gates involved in just a matrix multiplication, and scale it up to a diffusion model or large transformer, it gets infeasible very quickly.
For some numbers, a ResNet-20 inference can be done in CKKS in like 5 minutes on CPU. With custom changes to the architecture you can get less than one minute, and in my view HW acceleration will improve that by another factor of 10-100 at least, so I'd expect 1s inference of these (still small) networks within the next year or two.
LLMs, however, are still going to be unreasonably slow for a long time.
First,
> Prior to 2011, most cloud-connected devices simply uploaded their data in plaintext.
> Around 2011 our approach to data storage began to evolve. […] began to roll out default end-to-end encryption […] This technology changed the way that keys are managed, to ensure that servers would never see the plaintext content of your messages.
"changed the way that keys are managed" is at a confused contradiction with "uploaded their data in plaintext". If you're going from TLS → E2EE, then yeah, "changed the way keys are managed" miiight make sense, though that's not how I'd phrase it. Then later,
> On the one hand they can (1) send plaintext off to a server, in the process resurrecting many of the earlier vulnerabilities that end-to-end encryption sought to close. Or else (2) they can limit their processing to whatever can be performed on the device itself.
We're still confusing "transmit plaintext" with plaintext being available to the server; the clear option of "use TLS" is omitted. It doesn't really undermine the argument — the server would still have access to the data, and could thus maliciously train AI on it — but it is surprising for a "cryptographer".
> For example, imagine that Apple keeps its promise to deliver messages securely, but then your (Apple) phone goes ahead and uploads (the plaintext) message content to a different set of servers where Apple really can decrypt it. Apple is absolutely using end-to-end encryption in the dullest technical sense… yet is the statement above really accurate? Is Apple keeping its broader promise that it “can’t decrypt the data”?
No, no reasonable person would believe that (though I am sure that if the scenario ever came to be, Apple, or whoever, would likely argue "yes") since it would utterly scuttle the term "E2EE". If you say "Our product supports X", and then have to caveat away 100% of what makes X X, then it's just grift, plain and simple. (Now, whether grift sees regulatory action … well.)
> Now imagine that some other member of the group — not you, but one of your idiot friends — decides to turn on some service that uploads (your) received plaintext messages to WhatsApp.
> In general, what we’re asking here is a question about informed consent.
I would sort of agree, but corporations will expose the consent here to the "friend", and then argue that because the friend consented to your data being uploaded, it is fine. An argument for privacy regulations.
(I don't think you have to go through all this … work. Just upload the user's data. They'll complain, for a bit, but the market has already consolidated into at least an ologopoly, users have shown that, for the most part, they're going to keep using the product rather than leave, or else I'll be ending this comment with a free "2025 will be the Year of the Linux Desktop". What's gonna happen, regulation to ensure a free market remains free¹? Please. Cf. MS Recall, currently in the "complain" phase, but give it time, and we'll reach the "we heard your concerns, and we value your input and take your feedback with the utmost respect ram it down their throats" stage.)
(¹free as in "dictated by the laws of supply & demand", not laissez-faire which is where the US will be headed for the next 4.)
(and … 2011? I'd've said 2013 is when we found out the 4A meant way less than we thought it did, leading to the rise in massive adoption of TLS. Less so E2EE.)
>With Advanced Data Protection enabled, Apple doesn't have the encryption keys needed to help you recover your end-to-end encrypted data.
Apple doesn't have the keys. Somebody else might. Somebody other than you. Also, I think they meant to say decryption keys, although they're probably just dumbing down terminology for the masses.
>If you ever lose access to your account, you’ll need to use one of your account recovery methods
"You'll need to use." Not "there is no way except to use."
>Note: Your account recovery methods are never shared with or known to Apple.
"shared with or known to Apple." Not "shared with or known to anyone else."
The encryption is there, I believe that. I just don't know how many copies of the keys there are. If the only key is with me, it would be super easy for Apple to just say that. I believe that they have said that in the past, but the wording has now changed to this hyper-specific "Apple does not have the key" stuff.
IMHO, Apple's PCC is a step in the right direction in terms of general AI privacy nightmares where they are at today. It's not a perfect system, since it's not fully transparent and auditable, and I do not like their new opt-out photo scanning feature running on PCC, but there really is a lot to be inspired by it.
My startup is going down this path ourselves, building on top of AWS Nitro and Nvidia Confidential Compute to provide end to end encryption from the AI user to the model running on the enclave side of an H100. It's not very widely known that you can do this with H100s but I really want to see this more in the next few years.
Are you speaking of this functionality? https://developer.nvidia.com/blog/confidential-computing-on-... (and am I just failing to find the relevant AWS docs?)
We work with Edgeless Systems who manages the GPU enclave on Azure that we speak to from our AWS Nitro instance. While not ideal, the power of enclaves and the attestation verification process, we at least know that we're not leaking privacy by going with a third party GPU enclave provider.
From my perspective, Apple's behavior indicates that what they want to maximize is their own control, and their position as the gatekeeper others must pay in order to get access to you.
No, no one was. I despair
1960s: “I BETTER NOT SAY THAT OR THE GOVERNMENT WILL WIRETAP MY HOUSE”
2020s: “HEY WIRETAP, DO YOU HAVE A RECIPE FOR PANCAKES?”
...today. There's no real reason we can't get acceptable speeds in the near future.
Or … IDK, maybe you don't. Recent Android phones are now capable of prompting the user to actively cool them off because the ~bloat~ software is consuming too much compute/power. What basically translates to "help I'm dying" is an amusing message, but also a depressing state of affairs.
¹compare to a laptop, or worse for the phone, a desktop. The comparative cooling surface area is multiple times larger. And both have fans, desktops can be liquid cooled — it's not mere chance that they're faster, and phone form factor literally presents challenges. Even with an infinite battery, or a USB capable, you can't dissipate 60 W into a human hand.
Thus, AI training on your data breaks this, because it's another party.
You now don't have encryption."
Thanks for coming to my blah blah blah
2. Can the user access their data at rest?
Those two things are entirely orthogonal.
I don't think you can extrapolate a trend from a few apps having bugs in their export code. Google Takeout is also notoriously buggy and they don't use E2E encryption. A more likely explanation is companies of all kinds don't care that much about export functionality, due to the incentives involved.