Nissenbaum et al.’s attempt to fi gure out when people DO and DON’T sense a privacy violation. ✦ Also a reaction against US notice-and-consent law, which posits “if they signed o ff on it in any way whatever, it’s not a privacy violation.” Which is… how shall I put this?… garbage. ✦ Book: Privacy in Context, by Nissenbaum. ✦ It’s a heavy read (though fairly short). Nissenbaum is an ethicist, and ethicists write the way zambonis clear ice rinks: carefully, thoroughly, and very very slowly. ✦ It’s also HUGELY in fl uential, at least in privacy and ethics scholarship. (Bit less so in industry, but you’ll see it mentioned.) ✦ It’s more useful than its (sorry!) rather pedantic style might suggest.
want bright-line privacy rules: this is always okay, that is always not. ✦ Nissenbaum: “Sorry. It’s not that simple.” ✦ Because we don’t always react to things in proportion to the actual risks. ✦ Sometimes we FREAK ALL THE WAY OUT about stu ff that, considered carefully, isn’t all that major or scary. ✦ Sometimes we let really horrible privacy-destroying stu ff slide. ✦ WHYYYYYYYYYYYYY? asked Nissenbaum. ✦ Why is this, in both directions? ✦ And what is it that we actually respond to, if it’s not the risk level? ✦ And what should we be able to expect by way of privacy protection?
✦ Nissenbaum: it’s our right to live in a world where our expectations about information fl ow are (for the most part) respected. ✦ Simple as that. ✦ Consider using this idea to prioritize your campus data report and your communicative artifact. Lean into situations where your expectations weren’t respected!
is appropriate, and breaks when it’s not. ✦ Who decides what’s appropriate? We all do. ✦ We all have expectations about when it’s okay to share information, or have other people share information about us. ✦ Our appropriateness decisions are conditioned by SOCIAL NORMS. These norms change over time. ✦ They’re also conditioned by WHAT WE ACTUALLY UNDERSTAND about information fl ows, and I really wish CI theorists gave more time to this. ✦ Both social and individual information- fl ow norms depend on SPECIFIC SOCIAL CONTEXTS. ✦ Basic example: It’s okay for me to discuss your work in this course with you. That’s appropriate. Complaining about it on my public Twitter, using your name? OH HECK NO. Utterly inappropriate! ✦ But it’s the same information! So it’s the context that matters.
of privacy equate it to secrecy. Contextual integrity doesn’t! ✦ Information doesn’t have to be totally secret to be private in some way. ✦ Some equate it to compliance with applicable law. Contextual integrity doesn’t! ✦ An information fl ow can be legal and still violate contextual integrity. ✦ Some think privacy means individuals’ control over their data. Contextual integrity doesn’t! ✦ You might not be in control of a given information fl ow, but that doesn’t mean it bothers you. (If I discuss your group’s project with another member of your group, does that violate your privacy? I’m guessing not… even if you don’t even know it’s happening.) ✦ Or you could have control, make a mistake with it, and still feel your privacy was violated. (Has an online service ever done you dirty?)
violation are reacting to one (or more) of fi ve aspects of a data-sharing transaction: ✦ DATA SUBJECT: who is this data about? ✦ DATA SENDER: who’s sharing the data? ✦ DATA RECIPIENT: who’s receiving the data? ✦ INFORMATION TYPE: (exactly what you think it is) ✦ TRANSMISSION PRINCIPLE (hold that thought; I’ll get to it) ✦ WRITE THESE DOWN, PLEASE. ✦ You’ll want them as you work through your campus data report. ✦ Now I’ll explain them, with examples. ✦ Especially that last one. It’s a bit tricky.
one person may not be at all okay to share about another. ✦ Example: Children. In the US, there are more legal restrictions on collecting and sharing data about children than about adults. ✦ The rationale being that children are more vulnerable than adults, less autonomous, and less able to protect themselves ✦ Example: Folks with limited cognitive capacity ✦ For whatever reason (age, some disabilities, both) ✦ Again, the rationale is that sharing data about vulnerable people who don’t understand what’s going on well enough to object is Not Okay.
you, even if they got it in a reasonable way. ✦ Example: attorney-client privilege ✦ If you’re paying a lawyer, they need to keep their mouth shut about what you tell them except for what they must disclose to get the legal work done that you’re paying them for. ✦ Example: HIPAA, US health-records privacy law ✦ Heavily regulates what HEALTH PROFESSIONALS can share (also when and under what circumstances) ✦ Doesn’t actually regulate anybody else who gets their paws on your health data! Got a Fitbit? DUMP IT. Period-tracking app? DELETE IT. Don’t buy that health-tracking smartwatch, okay? All of these can rat you out (and actually have ratted people out). HIPAA doesn’t care.
data shared with them. ✦ Example: FERPA, US educational-record law. It’s complicated, but for example: ✦ If you’re my advisee, I am allowed to see what courses you’ve taken and what grades you’ve earned. (I need to know to do my job!) But I can’t go tell your boss; FERPA will smack me down. Bad recipient! ✦ Not my advisee? Your course choices and grades are none of my business, unless you actually tell me about them (which is your right) OR I have a solid, education-related reason I need to know. ✦ (For example: I help assess undergraduates for the Phi Beta Kappa honor society. I see transcripts, including grades, for students under consideration. FERPA is fi ne with this.) ✦ Without such a reason, FERPA does not consider me an acceptable data recipient.
data is more sensitive than other data. ✦ Example: personal identi fi ers ✦ Such as (US) social-security numbers, credit-card numbers, passport and other ID numbers, and so on. ✦ They’re sensitive because if they leak, somebody can do you a whole lot of harm with them. ✦ Example: health data, again ✦ In the fi rst phase of Data Doubles, we found that a lot of our respondents had trouble coming up with information types that they considered sensitive enough to restrict campus access to. ✦ There was a notable exception: data about mental-health treatment or other counseling. Keep that private! several said.
information fl ow?” ✦ Some variant on “don’t randomly blab it!” is a really common transmission principle. ✦ Example: encryption in web browsers ✦ Web browsers are BUILT for information fl ow! That’s their whole reason for existing! ✦ Data subject is presumptively fi ne (or, breaches and errors and doxers aside, the info wouldn’t be on the web in the fi rst place), data sender and recipient are fi ne, information type is fi ne… ✦ … but the entire world doesn’t need to be able to peek in on what I’m sur fi ng. Especially if it involves my credit union or my doctor or my boss. And early web browsers didn’t have any way to prevent that! ✦ They do now. (Up to a point. We’ll talk about it.)
Two ways, I think. ✦ One: when you learn about something that you consider a privacy violation, use the Five Parameters to dig into what feels wrong about it. ✦ Would you be okay if it was a di ff erent information type? If they asked you fi rst (transmission principle)? If it wasn’t going to That Person or That Company or Those Cops or That University O ffi ce? ✦ Two: in your campus-data report, evaluate everything you fi nd out about information fl ows against the Five Parameters. If something’s not right, explain precisely why not!
a particular information fl ow are broadly accepted, but still kind of bad? ✦ An example to think about: video surveillance of public spaces, especially when combined with facial-recognition technology. ✦ Strict contextual-integrity theory says “meh, it’s the norm, let it go.” Not an ideal answer! ✦ This totally happens. Adtech is a great example! Repeated studies now indicating that once people understand how adtech tracking works and where the data goes, they HATE it. But it’s still considered normal! ✦ Nissenbaum: take a step back and consider the reasons this information fl ow exists, and the ethics binding the collecting/sharing parties. ✦ MA/LIS folks: this is where our ethics codes around privacy, equitable service, and putting patrons over vendors kick in.
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