(Roughly) Daily

There’s a depressing sort of symmetry in the fact that our modern paradigms of privacy were developed in response to the proliferation of photography and their exploitation by tabloids. The seminal 1890 Harvard Law Review article The Right to Privacy—which every essay about data privacy is contractually obligated to cite—argued that the right of an individual to object to the publication of photographs ought to be considered part of a general ‘right to be let alone’.

30 years on, privacy is still largely conceived of as an individual thing, wherein we get to make solo decisions about when we want to be left alone and when we’re comfortable being trespassed upon. This principle undergirds the notice-and-consent model of data management, which you might also know as the pavlovian response to click “I agree” on any popup and login screen with little regard for the forty pages of legalese you might be agreeing to.

The thing is, the right to be left alone makes perfect sense when you’re managing information relationships between individuals, where there are generally pretty clear social norms around what constitutes a boundary violation. Reasonable people can and do disagree as to the level of privacy they expect, but if I invite you into my home and you snoop through my bedside table and read my diary, there isn’t much ambiguity about that being an invasion.

But in the age of ✨ networked computing ✨, this individual model of privacy just doesn’t scale anymore. There are too many exponentially intersecting relationships for any of us to keep in our head. It’s no longer just about what we tell a friend or the tax collector or even a journalist. It’s the digital footprint that we often unknowingly leave in our wake every time we interact with something online, and how all of those websites and apps and their shadowy partners talk to each other behind our backs. It’s the cameras in malls tracking our location and sometimes emotions, and it’s the license plate readers compiling a log of our movements.

At a time when governments and companies are increasingly investing in surveillance mechanisms under the guise of security and transparency, that scale is only going to keep growing. Our individual comfort about whether we are left alone is no longer the only, or even the most salient part of the story, and we need to think about privacy as a public good and a collective value.

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I like thinking about privacy as being collective, because it feels like a more true reflection of the fact that our lives are made up of relationships, and information about our lives is social and contextual by nature. The fact that I have a sister also indicates that my sister has at least one sibling: me. If I took a DNA test through 23andme I’m not just disclosing information about me but also about everyone that I’m related to, none of whom are able to give consent. The privacy implications for familial DNA are pretty broad: this information might be used to sell or withhold products and services, expose family secrets, or implicate a future as-yet-unborn relative in a crime. I could email 23andme and ask them to delete my records, and they might eventually comply in a month or three. But my present and future relatives wouldn’t be able to do that, or even know that their privacy had been compromised at all.

Even with data that’s less fraught than our genome, our decisions about what we expose to the world have externalities for the people around us. I might think nothing of posting a photo of going out with my friends and mentioning the name of the bar, but I’ve just exposed our physical location to the internet. If one of my friends has had to deal with a stalker in their past, I could’ve put their physical safety at risk. Even if I’m careful to make the post friends-only, the people I trust are not the same as the people my friends trust. In an individual model of privacy, we are only as private as our least private friend.

Amidst the global pandemic, this might sound not dissimilar to public health. When I decide whether to wear a mask in public, that’s partially about how much the mask will protect me from airborne droplets. But it’s also—perhaps more significantly—about protecting everyone else from me.

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Data collection isn’t always bad, but it is always risky. Sometimes that’s due to shoddy design and programming or lazy security practices. But even the best engineers often fail to build risk-free systems, by the very nature of systems.

Systems are easier to attack than they are to defend. If you want to defend a system, you have to make sure every part of it is perfectly implemented to guard against any possible vulnerabilities. Oftentimes, trying to defend a system means adding additional components, which just ends up creating more potential weak points. Whereas if you want to attack, all you have to do is find the one weakness that the systems designer missed. (Or, to paraphrase the IRA, you only have to be lucky once.)

This is true of all systems, digital or analog, but the thing that makes computer systems particularly vulnerable is that the same weaknesses can be deployed across millions of devices, in our phones and laptops and watches and toasters and refrigerators and doorbells. When a vulnerability is discovered in one system, an entire class of devices around the world is instantly a potential target, but we still have to go fix them one by one.

This is how the Equifax data leak happened. Equifax used a piece of open source software that had a security flaw in it, the people who work on that software found it and fixed it, and instead of diligently updating their systems Equifax hit the snooze button for four months and let hackers steal hundreds of millions of customer records. And while Equifax is definitely guilty of aforementioned lazy security practices, this incident also illustrates how fragile computer systems are. From the moment this bug was discovered, every server in the world that ran that software was at risk.

What’s worse, in many cases people weren’t even aware that their data was stored with Equifax. If you’re an adult who has had a job or a phone bill or interacted with a bank in the last seven years, your identifying information is collected by Equifax whether you like it or not. The only way to opt out would have been to be among the small percentage of overwhelmingly young, poor, and racialized people who have no credit histories, which significantly limits the scope of their ability to participate in the economy. How do you notice-and-consent your way out of that?

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There unfortunately isn’t one weird trick to save democracy, but that doesn’t mean there aren’t lessons we can learn from history to figure out how to protect privacy as a public good. The scale and ubiquity of computers may be unprecedented, but so is the scale of our collective knowledge…

Read the full piece (and you should) for Jenny Zhang‘s (@phirephoenix) compelling case that we should treat– and protect– privacy as a public good, and explanation of how we might do that: “Left alone, together.” TotH to Sentiers.

[image above: source]

* Edward Snowden

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As we think about each other, we might recall that it was on this date in 1939 that the first government appropriation was made to the support the construction of the Harvard Mark I computer.

Designer Howard Aiken had enlisted IBM as a partner in 1937; company chairman Thomas Watson Sr. personally approved the project and its funding. It was completed in 1944 (and put to work on a set war-related tasks, including calculations– overseen by John von Neumann— for the Manhattan Project). 

The Mark I was the industry’s largest electromechanical calculator… and it was large: 51 feet long, 8 feet high, and 2 feet deep; it weighed about 9,445 pounds  The basic calculating units had to be synchronized and powered mechanically, so they were operated by a 50-foot (15 m) drive shaft coupled to a 5 horsepower electric motor, which served as the main power source and system clock. It could do 3 additions or subtractions in a second; a multiplication took 6 seconds; a division took 15.3 seconds; and a logarithm or a trigonometric function took over a minute… ridiculously slow by today’s standards, but a huge advance in its time.

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