Careers of the Future: Anti-Tracking Makeup Artist

Facial recognition will be coming to retailers. They will track shoppers, linking their face and other biometric information to purchases, to how they move around the store, to doing market research on whether they prefer to buy their beer from cardboard cutouts wearing bikinis or one-pieces, or whether they prefer the suit to be printed on the cardboard or have actual cloth tied over it (early studies show that in the latter case, 12-year-old boys will peek and be disappointed that the suit is still printed underneath, often saying ‘dang’ or ‘crapola’ as they walk away). Retailers will do this without permission, and it’s not clear how it will shape the future of not just commerce, but fashion as well.

One thing it might do is open the market for makeup artists, makeup, and facial appliances to mask against facial recognition. Of course, there will be makeup-applying robots to automate the process, but citizens will want to choose from human-designed patterns.

It may also result in more men growing out facial hair, causing a large dent to the market for shaving cream and razors. Still, one door closes and another opens, thanks to some insanely shoddy door-hanging work the universe had done while drunk during the photon epoch. Cosmology aside, the beards will be groomed and dyed according to the latest fashion trends. While these augmentations will again be performed by robots, the designers might as well be humans. The question remains whether those are feasible remedies for privacy from in-store tracking.

Others will move to online shopping, where we are tracked, but not so physically. An alternative will be an increase in in-store surrogate shoppers (equipped with VR-ready camera setups to feed real-time VR views so you can shop from afar). The surrogate may be tracked, but if the store doesn’t know who they are buying for, it won’t help them.

Stores could try to implement no-surrogacy policies, or lobby for surrogacy disclosure laws, but it’s unclear how effective either would be. If makeup and appliances are effective, stores may implement no-recognition no-shop policies, but it’s not clear those would be legal. If you genuinely did not have a recognized face, and weren’t masking, their denial of service could be a liability.

One issue is that stores believe it is impractical to have people opt-in to recognition. Many people carry small computers equipped with radio transmitters, which could easily be extended to broadcast (or handshake) to announce their willingness to be facially tracked. With the Internet of Things becoming a topic of interest, it is likely such technology will be added to these personal mobile computers anyway.

In any case, I look forward to the near future when it will be commonplace to see average people in public who look like something Picasso painted.


Big Data on Small Computers

US motto, e pluribus unum, on the back of a dime
Shows US motto (e pluribus unum) on the reverse of a US dime.

One of the great emerging fields of computing is the use of big data and machine learning. This is a process whereby large datasets actually teach computers to do things like translate text, interpret human speech, categorize images, and so on. The problem with this is, so far, it requires large amounts of data and a lot of computing power.

The paradigm is largely opposed to the types of computing people would prefer to do and use. We would rather not send our voice data out to the Internet or have the Internet always listening or watching us to get these benefits of machine learning. But while the advances in technology will allow for us to crunch the data on smaller devices, it will be difficult to have the corpus of data needed for training and use.

It remains to be seen whether smaller datasets or synthesized datasets (where a large dataset is somehow compressed or distilled into the important parts) will emerge. So how do we get big data in our relatively small computers?

It is likely that the problem will provoke the emergence of more distributed systems, something many have wanted and waited for. Distributed systems or collaborative computing allows your computer(s) to participate in computing larger datasets. Projects like the Search for Extra-Terrestrial Intelligence (SETI) have used such distributed computing for over a decade.

The main challenge will be finding ways to break up data to send to the distributed system that protect privacy. That is, if you send the whole voice capture to the distributed system (as you do, AFAIK, with cloud services like Apple’s Siri), you risk the same privacy issues as with the cloud model.

Instead, it should be possible to break up inputs (video or audio) and send portions (possibly with some redundancy, depending on e.g., if word breaks can be determined locally) to several systems and let them each return only a partial recognition of the whole.

It also remains to be seen whether this piecemeal approach will be as functional as the whole-system approach in all cases. While this splitting undoubtedly takes place in whole-systems like Siri, the reassembly and final processing surely takes place over the whole input. That final step may not be easily managed over a distributed system, at least not while protecting privacy.

Consider asking, “what is the time in Rome?” which might be processed as slightly off, due to pronunciation, “what is the dime in Rome?” In a whole-system approach it’s likely easier to infer dime → time at some late step, rather than if each hands back a partial result and the final recipient has less knowledge of how it was made. In a question case like that, the final text is likely targeted to a search engine, which will correct (though it could take the question literally and say, “It is the €0.10 coin.”).

For situations where the voice command lends insufficient context for local correction, it could be a greater challenge.

The good news is that it does look like it’s possible for us to have these distributed systems replace proprietary cloud solutions. The questions are when and how they will emerge, and where they might be weaker.


About the Privacy Argument Against Autocars

Image of an overgrown field with the remnants of a car visible (back wheels, steering column).
By Ben Salter (Flickr: ben_salter)

One of the arguments against self-driving vehicles is the privacy argument. Won’t you be tracked? Won’t police be able to stop the car? What if the navigation is hacked? And so on.

The problem with this argument is that it avoids the fact that we have the same problem already in many other facets of our lives. The issues are only more obvious and accute when you’re talking about putting your life into the cyberhands of an algorithm.

Society has a real need to confront the security and privacy issues much more directly than it has done. Autocars may raise the issue to higher prominence, which may help us strike a new balance sooner. In that, it could be a feature. But how we ultimately deal with the erosion of barriers to privacy and security is still unsolved.

It will need to be solved even if we stuck to manual cars, of course. But it also needs to be solved with televisions that watch you, phones that listen to you (for voice control), and similar services. It needs to be solved when the day comes that your phone tells a restaurant you’re allergic to something. And so on.

There is a balance to be struck between providing information and retaining privacy. And we have yet to strike it in most cases. Our political world is full of dark money, where donors choose not to reveal themselves while attacking others. Our tax code is full of subtle blind alleys where large companies and the very rich hide their money.

What you buy is tracked, which is one of the reasons that some companies are shunning NFC-based payments like ApplePay. ApplePay would reduce the information they receive when you buy something.

And, of course, online you leave your digital footprints as you jump from reading Eight Exercises that Your Ancestors would Laugh Their Asses Off at You for Doing to ordering food online to reading this blog.

Point is, we’re already being tracked through all manner of invasive tools both in meatspace and in cyberspace. One more meatspace tracking measure does not seem to raise itself in priority above balancing them all correctly and comprehensively.

Even your goods are tracked as they are shipped to you. And you like that. It lets you know when your stuff will get home.

Done right, instead of waiting on someone running late for a meeting, you could see that they’re stuck waiting for an autocar. Done wrong, you might have a surprise party ruined because the birthday human sees that everyone’s at their house. Or couples might catch each other cheating. Or stalkers and criminals will hack the system and use it for evil means.

But the good news is that there are real enough non-totalitarian harms to giving up privacy to make strong arguments for laws and technical designs that let us retain privacy, even in autocars. The balance is yet to be struck, but the reasons are there for it. It may not even be a world we find comfortable, it may be less private than we would like. But there’s no indication it will be as bad as the tracking that’s already going on today.


Privacy is Security

Without privacy, there is no such thing as security.  You can call systems and laws that do not account for privacy secure, but they are not.

One of the most vital aspects of securing any system is protecting it from internal attacks; that is, attacks due to the corruption of its actors.  Most systems ignore these threats, and they are all the more vulnerable for it.  If a system can be taken down by a lone actor that has privileged access, it is not secure.  Likewise, if your data can be leaked to Wikileaks by a lone actor, it’s not secure.

Simultaneously, the act of properly securing against such things removes the ability for a system to behave in an anti-human fashion.  This is because the abuse of authority that allows for harming people (eg, a private prison system that needs more prisoners and has the ability to get them through legislation) becomes impossible.  The same protections on privacy that thwart leaking also preclude deal-making that creates malformed laws or rules.

The level of conspiracy required to actually attack a secure system always requires that those that would be harmed give voluntary, informed consent.  They will almost never do so.

The systems that exist today are not secure, and most of the time that is by design: the parties that have ultimate responsibility for overseeing security are too enamored with their abilities to manipulate the systems for their own naive interests (which are actually against their true interests) to order proper security measures.

We will begin to see truly secure systems emerge in the next waves of web applications; distributed applications require a separation of concerns to function properly, and, when coupled with next-generation authentication, they move toward privacy (is security).


No Immunity

The latest in the war on privacy is the attempt by the President and Congress to collude on an update to FISA that includes a provision intended to grant immunity from civil suits against telecommunications companies for the part they may have played in illegal wiretaps.

While in a perfect world such an idiotic attempt to stifle a basic right of redress for violation of rights would not occur, this is not a perfect world. On the other hand, and indeed more importantly, rest assured that this provision is in fact nude. Amendment Four makes that undeniably clear in its language: shall not be violated.

No mention of convenience to the executive or other such weasling applies. Amendment Four is an intrepid piece of law that must persist if a union is to exist at all. One merely wishes that the so-called legislators of this nation and the so-called executive of the government might occasion themselves to understand the law rather than limiting themselves to defecating in it while grinning like a three-month-old who has soiled himself immediately after a fresh change.