The Balance of Identity

This happened some time ago. I’m not sure when. The balance tipped.

It used to be that identity was asserted based on something you knew, something you had, or something you are. Online identity was centered on the individual. “Two factor” was another layer based on the same fundamentals.

Recently, more than a billion unique email addresses and passwords were posted to a hacking forum. Ideal for credential stuffing attacks by malicious hackers. The data was decrypted, the protective hashing removed. The breach was made up of 12 files and 87 gigabytes of plain text.

As a matter of fact, corporations and hackers have more of your identity than you do. They have more control over your identity data than you do. They can extend your identity into the world in more ways than you can. They can suck out the bits that you thought were yours alone.

The balance has shifted. Whatever it was that we thought made up our identity is now mostly in the possession of others. And not just the past, the present and the future as well.

Perhaps there’s some impression that people make upon the world that isn’t stored digitally in some corporation’s database. Maybe there’s some pattern that we repeat that isn’t used in a predictive behavior modeling program designed to increase sales.

Can it shift back the other way? What force would be strong enough to move it that way? Where would that force come from?

One or Two Things I Know About the Future…

There’s a concept known as “technical debt.” It’s the idea that choosing easy, patchwork solutions instead of better, more integrated approaches that would take longer. The easy fixes work until they don’t, and then a large-scale expensive fix is required to clean up all the patches. The current technology culture has accumulated a kind of debt based on a set of unquestionable assumptions. The culture of “move fast and break things,” doesn’t have time to think about what it’s doing in advance.

But if you look carefully, you can see that there are a number of these buried assumptions that are starting to surface as fundamental problems. They’re starting to create cracks in the great edifices of the technology giants.

  1. User metrics don’t capture intention. Tons of user interaction data is collected through web sites, but we still don’t know what it means. There’s a gap. The systems capture to click, but the intention that caused the click isn’t contained in the click data. That gap reappears when an analyst attempts to interpret the interaction data.
  2. Crowd sourcing has very limited utility. If you’ve ever tried to make sense of a product or restaurant review with thousands of user reviews, you know that some people like it and others don’t. Almost any form of music has die-hard fans. In the end, you end up know less than when you started reading the reviews.
  3. Algorithms aren’t neutral. They encode prejudices.
  4. Artificial intelligence is poorly named. It’s neither artificial, nor intelligence. The hype is that it is, or will be, smarter than the smartest person. For instance, it can beat smart people at some specific types of games. Technologists don’t seem to understand the poverty of the language they use to discuss these systems. They do, however, understand that their projects are being funded under a basic misunderstanding of what they’re doing—a misunderstanding that works to their advantage.
  5. It’s become perfectly clear that the sharing economy and the gig economy is simply a method of shifting risk and expense to the worker to the benefit of the corporation.
  6. Personal data isn’t as helpful as corporations think it is. They collect tons of data about people they don’t need and don’t use. The big data industry has convinced them that more data is better. The problem is that they keep losing data to hackers and there doesn’t seem to be any real penalty. Data breaches are constantly in the news. At some point, corporations will have to be fined per leak, per person.The incentives have to change such that keeping the least amount of personal data in the normal state of things.
  7. Real-time social media owned by corporations are not neutral platforms. Their business model is to sell advertising against a high-volume stream of posts. It’s just like television. Flame wars and trolling are good for business. More conflict generates more volume in the stream. What these companies perceive as neutrality is really more of an amorality. More conflict is good regardless of its source. Evil triumphing over Good was a ratings bonanza!
  8. Consumers are already over-served by technology. This has been true for a while. The latest hand-held computing device adds features and power, but the real improvement is only marginal. There aren’t any big new consumer technical innovations because we’re already over-served by the current ones. A real examination of how users use personal computing devices would show what a small percentage of their capability is used.
  9. Bots outnumber humans on the network. Soon bots will be able to mimic human behavior better than humans do. It’s a variation on the old saying, “once you can fake sincerity, you’ve got it made.”
  10. Technologists and journalists like to make fun of politicians. CEOs of tech companies get called up in front of committees and get asked stupid questions. That’s the cue for journalists and libertarians to say that politicians shouldn’t regulate technology because they don’t understand it. The truth is that no one understands technology—not the CEOs, not the programmers and certainly not the journalists. Regulations are created because harm has been done. Politicians understand when harm has been done to their constituency. Technologists move fast and break things, “harm” is just part of the process. Regulations are protections from harm.

We’ve reached a point of inversion. As the graffiti says, “In the future, everyone will want to be anonymous for fifteen minutes.” Momentum will continue to take us down the road we’re on, but the hollow sound of technology’s promises will be heard for what they are. We’ve recovered from the shock of the new, and it turns out that 90% of it is crap we can live without. A counterculture is emerging.

On Thinking About Hell

Here’s another poem from Bertolt Brecht, written during his exile in the City of Angels.

On Thinking About Hell

On thinking about Hell, I gather my brother Shelley found it was a place much like the city of London. I who live in Los Angeles and not in London find, on thinking about Hell, that it must be still more like Los Angeles.

In Hell too there are, I’ve no doubt, these luxuriant gardens with flowers as big as trees, which of course wither unhesitantly if not nourished with very expensive water. And fruit markets with great heaps of fruit, albeit having neither smell nor taste. And endless processions of cars lighter than their own shadows, faster than mad thoughts, gleaming vehicles in which jolly-looking people come from nowhere and are nowhere bound. And houses, built for happy people, therefore standing empty even when lived in.

The houses of Hell, too, are not all ugly. But the fear of being thrown on the street wears down the inhabitants of the villas no less than the inhabitants of the shanty towns.

Surveillance Keiretsu

I stumbled across some near-term plans for the Amazon Corporation. It’s funny to think that they started as an online bookstore. Now it’s hard to say exactly what they are. They’ve purchased other companies, branched off into space exploration and are even pioneering delivery by drone.

I think everyone will agree that the new set of services they’re working on will move online commerce to a whole new level. The last mile problem has been there since the beginning. An order can be placed at the speed of light and the large national distribution networks get the goods quite close to where the customer lives very quickly. But getting packages from a local distribution warehouse to a specific residence ends up being the most expensive part of the distribution process.

Even if the packages arrive on schedule and are placed on the doorstep, they are often stolen by criminals cruising neighborhoods. These crooks trail delivery vans and pick off packages that look like they might have resale value on the black market. Customers are always complaining about stolen packages.

This is why Amazon bought Ring, the home security company. Ring puts video cameras on your front door and around your property. If a thief approaches, intending to steal a package, the video cameras capture an image of the person’s face. Recently Ring customers within particular neighborhoods have started sharing these photos. “Watch out for this guy, he’s stealing packages.” Often the photos are also shared with the local police.

Here’s where Amazon can really add value through its network of companies and infrastructure services. Imagine a future with even faster delivery and free of package thieves. By combining drone delivery and Ring’s home surveillance technology, you’ll never lose another package.

Here’s a typical scenario. The customer places an order. The item is picked and packed, and moved into the distribution chain. The package arrives at a local distribution center and is assigned to a drone for home delivery. The drone races to your house and places the package on the designated receiving location. What this? A thief sees the delivery, waits until the drone is out of sight, then moves in to steal the package. Here’s where Ring’s network-connected cameras kick in. The cameras are watching the receiving area—having been notified by the drone that a delivery was imminent. The images of the thief are sent to the Amazon Cloud for processing. The photo of the thief is compared to the family of consumers occupying the house. If there’s no match, the algorithm goes through the extended family, work colleagues and friends. It looks through address books and photo albums to see if there’s any possible match. Given what’s coming next, Amazon doesn’t want to make a mistake.

It looks like there’s no match. This person is stealing your package. The image is now compared to outstanding arrest warrants and neighborhood watch photos. Based on several year’s worth of video footage, the algorithm produces a list of people who have no regular pattern of activity in your neighborhood to determine if this person has been casing the neighborhood. All the while, Amazon’s facial recognition systems are attempting to identify the individual. As a courtesy, Amazon shares the information with the Immigration and Customs Enforcement agency (ICE) to determine whether enforcement action should be coordinated.

At the same time, Amazon’s drones working in the area are alerted to the theft and they begin to gather into a swarm. The swarm tracks the thief as he tries to make his escape. Since Ring cameras are installed in almost every home in the neighborhood, it’s straightforward to track his route. The thief’s location is transmitted to the drone swarm and the cameras on the drones make an identification and lock in and begin tracking the thief. Amazon echo nodes in neighborhood homes notify residents via Alexa to shelter in place while the action is executed.

We’re Watching.

Ideally, the drone swarm will want to take action before the thief enters a vehicle. Even if full identification hasn’t been completed, the drone swarm will move in to herd the thief toward a designated location that has been communicated to local police. Since the police can’t always immediately respond to this kind of incident, the drone swarm is equipped to keep the “suspect” in the designated location for up to 12 hours.

If the thief has abandoned the package, and it appears undamaged, a drone will break off from the swarm and re-deliver it to your home. Damaged packages are taken by drone back to the local distribution warehouse and a request for a replacement item is automatically generated.

Once the police arrive on the scene, all video and audio evidence, along with any background profile data, is transmitted. Generally this results in an open-and-shut case when delivered to the District Attorney’s office. A permanent record is created in Amazon’s central data warehouse to make sure once this person has served their time in prison they receive heightened surveillance on release and for the rest of their lives.

Recidivism is the tendency of a convicted criminal to reoffend. Using the vast resources of the Amazon family of companies, we can often deter a person from reoffending by foregrounding the surveillance apparatus at a key moment prior to a criminal act. Sometimes all it takes is a reminder that someone is watching, and that any criminal act will be swiftly and surely punished.

That’s the future, but here’s some things Amazon is working on today…

Adding Face Recognition to Your Front Door

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