e-flux Futures

I dabbled in a little hopeful data futurism for DIS magazine's contribution to e-flux 56th Venice biennaleSTYLES AND CUSTOMS IN THE 2020S. As part of the journal’s ‘super community’ theme, in which “people comprise the planetary computer backend,” DIS crowdsourced predictions for the 2020s. Rather than be pessimistic about the way things are going and put forth predictions for a dystopic 2020, I offered a few hopeful outlooks of constructive solutions for technologies I think raise interesting near-term concerns.

Fortunately, the FTC modernizes the definition of antitrust to address both vertical and horizontal monopolies across markets, thus breaking up Google into three hundred companies. Commercial personalization gets its Snowden moment when a BlueKai data broker whistleblower outlines the extent of the industry’s manipulative, exploitative, and discriminatory targeting practices. Internet of Things companies form a self-regulating body and sign a common Code of Conduct charter outlining what they will not do with customers’ data.

Read more from the rest of the DIS contributors.

Dada Data and the Internet of Paternalistic Things

This piece of speculative fiction exploring a possible data-driven future first appeared in Internet Monitor project's second annual report, Internet Monitor 2014: Reflections on the Digital World. Check it out for more from my Berkman colleagues on the interplay between technological platforms and policy; growing tensions between protecting personal privacy and using big data for social good; the implications of digital communications tools for public discourse and collective action; and current debates around the future of Internet governance.

Mother.

Mother.

My stupid refrigerator thinks I’m pregnant.

I reached for my favorite IPA, but the refrigerator wouldn’t let me take one from the biometrically authenticated alcohol bin. 

Our latest auto-delivery from peaPod included pickles, orange juice, and prenatal vitamins. We never have orange juice in the house before because I find it too acidic. What machine-learning magic produced this produce? 

And I noticed the other day that my water target had changed on my Vessyl, and I wasn’t sure why. I figured I must have just been particularly dehydrated. 

I guess I should have seen it coming. Our Fountain tracking toilet noticed when I got off hormonal birth control and got an IUD instead. But I thought our toilet data was only shared between Nest and our doctors? What tipped off our Samsung fridge? 

I got a Now notification that I was ovulating a few weeks ago. I didn’t even know it had been tracking my cycle, let alone by basal body temperature through my wearable iRing. I certainly hadn’t turned that feature on. We’re not even trying to have a baby right now. Or maybe my Aria scale picked up on some subtle change in my body fat? 

Or maybe it was ComWarner? All our appliances are hooked up through one @HomeHub. I didn’t think twice about it because it just worked—every time we upgraded the dishwasher, the thermostat. Could it be that the @HomeHub is sharing data between the toilet and our refrigerator? 

I went into our @HomeHub interface. It showed a bunch of usage graphs (we’ve been watching a “below average” amount of TV lately), but I couldn’t find anything that looked like a pregnancy notification. Where was this bogus conception data coming from? 

My iWatch pinged me. The lights in the room dimmed, and a connected aromatherapy candle lit up. The heart monitor on my bra alerted me that my heart rate and breathing was irregular, and that I should stop for some meditative breathing. I sat down on my posture-tracking floor pillow, and tried to sink in.

But I couldn’t keep my mind from wandering. Was it something in the water? Something in my Snap-Texts with Kathryn? If it was true, why hadn’t my doctor called yet? Could I actually be pregnant? 

I turned on the TVTab to distract me, but I was bombarded with sponsored ads for “What to Expect When You’re Expecting 9.0” and domain squatter sites that search for a unique baby name. 

I searched for similar incidents on the Quorums: “pregnancy Samsung refrigerator,” “pregnancy Fountain toilet.” Nothing. I really wanted to talk to someone, but I couldn’t call Google because they don’t have customer service for @HomeHub products. I tried ComWarner. After waiting for 37 minutes to speak with a representative, I was told that the he couldn’t give out any personal data correlations over the phone. What bureaucratic bullshit! 

It can’t be true. Russell has been away in Addis Ababa on business for the three weeks. And I’ve still got the IUD. We aren’t even trying yet. This would have to be a bio-correlative immaculate conception. 

I tapped Russell on his iWatch three times, our signal to call me when he is done with his meeting. I was freaking out. 

I could have really used that beer. But the fridge still wouldn’t let me take it. What if I am really pregnant? I opened up Taskr to see if could get an old fashioned birth control test delivered, but price was three times as expensive as it normally would be. I considered CVS, but I thought better of it since you can’t go in there anymore without a loyalty card. It was far, but I skipped the self-driving Uber shuttle and walked the extra mile to the place that accepts crypto, where I wouldn’t be tracked. I think. And that’s when I got the notification that my funding interview for my new project the following morning had been canceled. 

 

Read more in the Berkman Center’s Internet Monitor 2014: Reflections on the Digital World.

Mapping the Data Ecosystem

This first appeared in Internet Monitor project's second annual report, Internet Monitor 2014: Reflections on the Digital World. Check it out for more from my Berkman colleagues on the interplay between technological platforms and policy; growing tensions between protecting personal privacy and using big data for social good; the implications of digital communications tools for public discourse and collective action; and current debates around the future of Internet governance.

 

What would it take to map the Internet? Not just the links, connecting the web of sites to each other, or some map of the network of networks. That’s hard enough in itself. 

What if we were to map the flows of data around the Internet? Not just delivering packets, but what those packets contain, where they propagate, how they are passed on, and to what ends they are used. 

Between our browser history, cookies, social platforms, sensors, brokers, and beyond, there are myriad parties with economic interests in our data. How those parties interconnect and trade in our data is, for the most part, opaque to us. 

The data ecosystem mirrors the structure of the Internet. No single body has dominion or a totalizing view over the flows of information. That also means that no one body is accountable for quality or keeping track of data as it changes hands and contexts. 

Data-driven companies like Facebook, Google, Acxiom, and others are building out their proprietary walled gardens of data. They are doing everything they can to control for privacy and security while also keeping control over their greatest assets. Still, they aren’t held accountable for the ads individuals purchase and target on their platforms, or for tertiary uses of data once it leaves their kingdom. 

Complexity obscures causality. So many variables are fed into the algorithm and spit back out on a personalized, transient platform that no one can tell you exactly why you saw one post over another one in the feed or that retargeted ad over this one. We conjure up plausible explanations and grasp at folk theories that engineers offer up to explain their outputs. 

We have given data so much authority without any of the accountability we need to have confidence in its legitimacy to govern our lives. 

As everything, refrigerators and crockpots included, expand the Internet and the ecosystem of data that runs on top of it, everything will leave a data trail. Going forward we have to assume that what can be codified and digitized will become data. What matters is how that data will be used, now and in the future. 

The potential harms are hard to pin down, primarily because we won’t know when they are happening. We can’t investigate discrimination that replaces pre-digital prejudice markers like race and sex with proxies correlated from behavioral data. And we run into invisible walls based on statistical assumptions that anticipate our needs but get us wrong if we fall outside the curve. It’s nearly impossible to catch these slights and even harder to develop normative stances on grounds we cannot see. 

Before we can start to discuss normative judgments about the appropriate uses of data, we have to understand the extent of what is technically possible. We cannot hope to regulate the misuse of data without means to hold all interconnected parties accountable for the uses and flows of data.

We need to map these relationships and data patterns. Who are the parties involved? How are they collecting, cleansing, inferring and interpreting data? To what ends is the data being used? 

Linked Data is one technical solution to this problem. Standards make data flows both machine readable and human legible. Policies that travel as metadata are another approach to distributed accountability. We can also hold some of the largest brokers and users of data to higher standards of ethics. But markets of users won’t move against these systems until we have a better map of the ecosystem. 

 

Read more in the Berkman Center’s Internet Monitor 2014: Reflections on the Digital World.

Living with Data so far...

It's been a couple weeks now and my Living with Data series for Al Jazeera is off and running. Here are some links to the posts so far:

This series explores how our data is tracked, collected, and used online, and features your voices. Do you have any questions about how your personal data is being used? Curious to learn more about your daily encounters with algorithms? I'm always looking for personal stories about our personal data. Email The Decoder at thedecoder@aljazeera.net, tweet me @smwat, or submit your issue or question via the form here. Screen shots and links are helpful clues.

Living with Data and The Decoder launch!

I'm really excited to share that I launched a new series this week with Al Jazeera America, based on my Berkman lunch talk last April about personal data stories. It's called Living with Data.

Launching Living with Data, my new series for Al Jazeera America.

The series consists of two parts: articles about the uses of data all around us, and a regular column—The Decoder—that looks into reader-submitted questions about personal data and algorithmic encounters. I go into the goals and inspiration for the series here: Introducing the Living With Data series

Check out the first in The Decoder series: Stalked by Socks. The Decoder follows a familiar advice or explainer column format. Here's a preview:

Last fall I became seriously creeped out when I was stalked by a pair of socks. I’d looked at them at an online retailer and then they followed me all over the internet, even after I bought a pair from L.L. Bean. And not just ads from the retailer I looked at, the same socks from other retailers also popped up. And different socks, too—new socks that I had not found in my own search for the ideal pair of cotton ragg footwear. I tried to outwit my pursuers and occasionally looked at an item online that I had no real interest in, things like a crossbow and camo clothes from Cabelas. Or motorcycle equipment from a Harley shop. Sure enough, these things began stalking me, too. The whole thing is unsettling. What’s going on? And why don’t these companies respect that I’ve already bought the socks?
— Ebba, Martha’s Vineyard, MA

Read more from Stalked by Socks.

I’m really excited to work with Al Jazeera on this project, given their dedication to being “with the people — we tell real stories.”

But I need your help! This series starts with you. Share your personal stories, your questions and your encounters with data.

Do you have screen captures of weird ads or algorithmic flukes? What were you doing, what caught your attention, and what’s your best guess for what’s going on? For example, what sites were you visiting just before the strange ad showed up? Submit with your name (you’ll be anonymous if you prefer), email address and phone number so I can follow up with you for details. 

Email The Decoder at thedecoder@aljazeera.net, tweet me @smwat, or submit via the form here. Screen shots and links are helpful clues! 

I am indebted to all my friends and family who helped me get this off the ground with their feedback, brainstorming, connections, and support. Thank you!