In the New York Review of Books!

I’m happy to report that my book was reviewed in the New York Review of Books along with Ariel Ezrachi and Maurice E. Stucke’s Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy, by Sue Halpern.

The review is entitled They Have, Right Now, Another You and in it she calls my book “insightful and disturbing.” So I’m happy.

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Using Data Science to do Good: A Conversation

This is a guest post by Roger Stanev and Chris French. Roger Stanev is a data scientist and lecturer at the University of Washington. His work focuses on ethical and epistemic issues concerning the nature and application of statistical modeling and inference, and relationship between science and democracy. Chris French is a data science enthusiast, and an advocate for social justice. He’s worked on the history of statistics and probability, and writes science fiction in his spare time.

Calling Data Scientists, Data Science Enthusiasts, and Advocates for Civic Liberties and Social Justice. Please join us for an information and preliminary discussion about how Data Science can be used to do Good!

Throughout Seattle/Tacoma, the state of Washington and the other forty-nine states in America, many non-profit organizations promote causes that are vital to the health, safety and humanity of our friends, families and communities. For the next several years, these social and civic groups will need all the help they can get to resist the increase of fear and hatred – of racism, sexism, xenophobia and bigotry – in our country.

Data Scientists have a unique skill set. They are trained to transform vague and difficult questions – typically questions about human behavior – into empirical, solvable problems.

So here is the question we want to have a conversation about: How can Data Scientists & IT Professionals use their expertise to help answer the current human questions which social and policy-based organizations are currently struggling to address?

What problems will minority and other vulnerable communities face in the coming years? What resources, tools and activities are currently being employed to address these questions? What can data science do, if anything, to help address these questions? Do data scientists or computer professionals have an obligation to assist in promoting social justice? What can we, as data scientists, do to help add and expand the digital tool-belt for these non-profit organizations?

If you’d like to join the conversation, RSVP to

Saturday, January 14
11am to 1pm @ King County Library (Lake Forest)
17171 Bothell Way NE, Lake Forest Park, WA 98155

Saturday, January 21
11am to 1pm @ Tacoma Public Library
1102 Tacoma Ave S, Tacoma, WA 98402

Saturday, January 28
1 to 3pm @ Seattle Public Library (Capitol Hill)
425 Harvard Ave E, Seattle, WA 98102

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Box Cutter Stats

Yesterday I heard a segment on WNYC on the effort to decriminalize box cutters in New York State. I guess it’s up to Governor Cuomo to sign it into law.

During the segment we hear a Latino man who tells his story: he was found by cops to be in possession of a box cutter and spent 10 days in Rikers. He works in construction and having a box cutter is literally a requirement for his job. His point was that the law made it too easy for people with box cutters to end up unfairly in jail.

It made me wonder, who actually gets arrested for possession of box cutters? I’d really like to know. I’m guessing it’s not a random selection of “people with box cutters.” Indeed I’m pretty sure this is almost never a primary reason to arrest a white person at all, man or woman. It likely only happens to people after being stopped and frisked for no particular good reason, and that’s much more likely to happen to minority men. I could be wrong but I’d like to see those stats.

It’s part of a larger statistical question that I think we should tackle: what is the racial discrepancy in arrest rates for other crimes, versus the population that actually commits those other crimes? I know for pot possession it’s extremely biased against blacks:marijuana_use_rate_by_race_yearmarijuana_arrest_rates_by_race_year

On the other end of the spectrum, I’d guess murder arrests are pretty equally distributed by race relative to the murdering population. But there’s all kinds of crimes in between, and I’d like some idea of how racially biased the arrests all are. In the case of box cutters, I’m guessing the bias is even stronger than for pot possession.

If w had this data, a statistician could mock up a way to “account for” racial biases in police practices for a given crime record, like we do in polling or any other kind of statistical analysis.

Not that it’s easy to collect; this is honestly some of the most difficult “ground truth” data you can imagine, almost as hard as money in politics. Still, it’s interesting to think about.

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Five Stages of Trump-related Grief

Denial. This happened to all of us at first, even people who voted for him. We couldn’t believe it, we were living through cognitive dissonance. We’d wake up in the morning wondering why they were referring to inane tweets on NPR, suddenly realize at lunch time that the Consumer Financial Protection Bureau will probably never do anything significant again. Binge-watching West Wing helped me sustain this stage. They were so damn patriotic and good. Their integrity and well-meaning-ness were leaking onto everything, and although they didn’t have gay marriage, they were progressing towards it, not backing down from it.

Anger. This stage hit me a few days after the election, in spite of my West Wing strategy. It was a rainy, cold day, and everyone I saw on the street looked absolutely pissed. People were bumping into each other more than usual, partly because of the umbrella traffic, partly on purpose. It was dumb rage, as anger always is. Nobody understood what the point was of being there, they just wanted to get home, to eat muffins, to smoke a damn cigarette. I came very close to picking up smoking that day.

Bargaining. For many people, this stage is still happening. I want to snap them out of it, out of the idea that the recounts will work or that the electoral college system will be changed or that electoral college delegates will refuse to do their job. It’s not gonna happen people, and Jill Stein can please stop. And it’s not that I don’t want to recount stuff – why not? – it’s just that the dying hope that it will change the outcome is sad to witness.

Depression. The problem with calling it depression is that people who are realistic, rather than overly optimistic, seem depressed. I’ve got to admit, I was much more prepared for this than most New Yorkers I know. I think it’s because I’ve been in war mode since joining Occupy in 2011. I never thought Hillary would win, that she was a good candidate, or that people’s resentment and anger had been properly addressed. I’ve basically been here, poised for this moment, since Obama introduced HAMP as a shitty and insufficient way to address the financial crisis back in 2009. So you can call it depression, I just call it reality.

Acceptance. And by acceptance I do not mean “normalization.” By acceptance I mean it’s time to move forward, to build things and communities and organizations that will protect the most vulnerable in post-fact America. That could mean giving money, but it should also mean being an activist and coming up with good ideas, like these churches offering sanctuary to undocumented migrants. It also might mean occupying the democratic party – or for that matter, some other party – and reimagining it for the future. Acceptance is not passive, not in this case. Acceptance means accepting our roles as activists and getting shit done.

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In NYTimes’ Room for Debate

This morning I’m in the New York Times, having written a short opinion piece on the following Facebook-centered theme:

How to Stop the Spread of Fake News

My actual opinion is entitled Social Media Companies Like Facebook Need to Hire Human Editors.


Tell me what you think!

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Miami Book Festival

I had a great time this weekend in Miami, attending the delightful Miami Book Festival with other longlisters (and winners!) of the National Book Award. We each read for about 5 minutes. Here’s a picture of me perched on the edge of the stage Saturday afternoon, getting ready to read, with many cool non-fiction writers:



Before my reading the wonderful Karan Mahajan brought me to a graffiti art area called Wynwood Wall and we were amazed by spray painted walls:


I was supposed to go to a party after that but I made a detour to South Beach, hanging out with the amazing Jonathan Rabb at the Clevelander:



After about 3 mojitos and many many performance artists I fell asleep at about 8pm.

Conclusion: I’m not cool enough for cool things like Miami, but I had a great time.

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Facebook should hire me to audit their algorithm

There’s lots of post-election talk that Facebook played a large part in the election, despite Zuckerberg’s denials. Here are some the various theories going around:

  1. People shared fake news on their walls, and sometimes Facebook’s “trending algorithm” also messed up and shared fake news. This fake news was created by Russia or by Eastern European teenagers and it distracts and confuses people and goes viral.
  2. Political advertisements had deep influence through Facebook, and it worked for Trump even better than it worked for Clinton.
  3. The echo chamber effect, called the “filter bubble,” made people hyper-partisan and the election became all about personality and conspiracy theories instead of actual policy stances. This has been confirmed by a recent experiment on swapping feeds.

If you ask me, I think “all of the above” is probably most accurate. The filter bubble effect is the underlying problem, and at its most extreme you see fake news and conspiracy theories, and a lot of middle ground of just plain misleading, decontextualized headlines that have a cumulative effect on your brain.

Here’s a theory I have about what’s happening and how we can stop it. I will call it “engagement proxy madness.”

It starts with human weakness. People might claim they want “real news” but they are actually very likely to click on garbage gossip rags with pictures of Kardashians or “like” memes that appeal to their already held beliefs.

From the perspective of Facebook, clicks and likes are proxies for interest. Since we click on crap so much, Facebook (and the rest of the online ecosystem) interprets that as a deep interest in crap, even if it’s actually simply exposing a weakness we wish we didn’t have.

Imagine you’re trying to cut down on sugar, because you’re pre-diabetic, but there are M&M’s literally everywhere you look, and every time you stress-eat an M&M, invisible nerds exclaim, “Aha! She actually wants M&M’s!” That’s what I’m talking about, but where you replace M&M’s with listicles.

This human weakness now combines with technological laziness. Since Facebook doesn’t have the interest, commercially or otherwise, to dig in deeper to what people really want in a longer-term sense, our Facebook environments eventually get filled with the media equivalent of junk food.

Also, since Facebook dominates the media advertising world, it creates feedback loops in which newspapers are stuck in the loop of creating junky clickbait stories so they can beg for crumbs of advertising revenue.

This is really a very old story, about how imperfect proxies, combined with influential models, lead to distortions that undermine the original goal. And here the goal was, originally, pretty good: to give people a Facebook feed filled with stuff they’d actually like to see. Instead they’re subjected to immature rants and conspiracy theories.


Of course, maybe I’m wrong. I have very little evidence that the above story is true beyond my experience of Facebook, which is increasingly echo chamber-y, and my observation of hyper-partisanship overall. It’s possible this was entirely caused by something else. I have an open mind if there were evidence that Facebook’s influence on this system is minor.

Unfortunately, Facebook’s data is private and so I cannot audit their algorithm for the effect as an interested observer. That’s why I’d like to be brought in as an outside auditor. The first step in addressing this problem is measuring it.

I already have a company, called ORCAA, which is set up for exactly this: auditing algorithms and quantitatively measuring effects. I’d love Facebook to be my first client.

As for how to address this problem if we conclude there is one: we improve the proxies.

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