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Panicked about Kids’ Addiction to Tech? Here are two things you could do

Flickr: Jan Hoffman

(This was originally posted on NewCo Shift)

Ever since key Apple investors challenged the company to address kids’ phone addiction, I’ve gotten a stream of calls asking me to comment on the topic. Mostly, I want to scream. I wrote extensively about the unhelpful narrative of “addiction” in my book It’s Complicated: The Social Lives of Networked Teens. At the time, the primary concern was social media. Today, it’s the phone, but the same story still stands: young people are using technology to communicate with their friends non-stop at a point in their life when everything is about sociality and understanding your place in the social world.

As much as I want to yell at all of the parents around me to chill out, I’m painfully and acutely aware of how ineffective this is. Parents don’t like to see that they’re part of the problem or that their efforts to protect and help their children might backfire. (If you want to experience my frustration in full color, watch the Black Mirror episode called “Arkangel” (trailer here).)

Lately, I’ve been trying to find smaller interventions that can make a huge different, tools that parents can use to address the problems they panic about. So let me offer two approaches for “addiction” that work at different ages.

Parenting the Small People: Verbalizing Tech Use

In the early years, children learn values and norms by watching their parents and other caregivers. They emulate our language and our facial expressions, our quirky habits and our tastes. There’s nothing more satisfying and horrifying than listening to your child repeat something you say all too often. Guess what? They also get their cues about technology from people around them. A child would need to be alone in the woods to miss that people love their phones. From the time that they’re born, people are shoving phones in their faces to take pictures, turning to their phones to escape, and obsessively talking on their phones while ignoring them. Of course they want the attention that they see the phone as taking away. And of course they want the device to be special to them.

So, here’s what I recommend to parents of small people: Verbalize what you’re doing with your phone. Whenever you pick up your phone (or other technologies) in front of your kids, say what you’re doing. And involve them in the process if they’d like.

  • “Mama’s trying to figure out how long it will take to get to Bobby’s house. Want to look at the map with me?”
  • “Daddy’s checking out the weather. Do you want to see what it says?”
  • “Mom wants to take a picture of you. Is that OK?
  • “Papa needs a break and wants to read the headlines of the New York Times. Do you want me to read them to you?”
  • “Mommy got a text message from Mama and needs to respond. Should I tell her something from you too?”

The funny thing about verbalizing what you’re doing is that you’ll check yourself about your decisions to grab that phone. Somehow, it’s a lot less comfy saying: “Mom’s going to check work email because she can’t stop looking in case something important happens.” Once you begin saying out loud every time you look at technology, you also realize how much you’re looking at technology. And what you’re normalizing for your kids. It’s like looking at a mirror and realizing what they’re learning. So check yourself and check what you have standardized. Are you cool with the values and norms you’ve set?

Parenting the Mid-Size People: Household Contracts

I can’t tell you how many parents have told me that they have a rule in their house that their kids can’t use technology until X, where X could be “after dinner” or “after homework is done” or any other markers. And yet, consistently, I ask them if they put away their phones during dinner or until after they’ve bathed and they look at me like I’m an alien. Teenagers loathe hypocrisy. It’s the biggest thing that I’ve seen to undermine trust between a parent and a child. And boy do they have a lot to say about their parents’ addiction to their phones. Oy vay.

So if you want to curb the usage of your child’s technology use, here’s what I propose: Create a household contract. This is a contract that sets the boundaries for everyone in the house — parents and kids.

Ask your teenage or tween child to write the first draft of the contract, stipulating what they think is appropriate as the rules for everyone in the house, what they’re willing to trade-off to get technology privileges and what they think that parents should trade-off. Ask them to list the consequences of not abiding by the household rules for everyone in the house. (As a parent, you can think through or sketch the terms you think are fair, but you should not present them first.). Ask your child to pitch to you what the household rules should be. You will most likely be shocked that they’re stricter and more structured than you expected. And then start the negotiation process. You may want to argue that you should have the right to look at the phone when it’s ringing in case it’s grandma calling, but then your daughter should have the right to look at her phone to see if her best friend is looking. That kind of thing. Work through the process, but have your child lead it rather than you dictate it. And then write up those rules and hang them up in the house as a contract that can be renegotiated at different types.

Parenting Past Addiction

Many people have unhealthy habits and dynamics in their life. Some are rooted in physical addiction. Others are habitual or psychological crutches. But across that spectrum, most people are aware of when something that they’re doing isn’t healthy. They may not be able to stop. Or they may not want to stop. Untangling that is part of the challenge. When you feel as though your child has an unhealthy relationship with technology (or anything else in their life), you need to start by asking if they see this the same way you do. When parents feel as though what their child is doing is unhealthy for them, but the child does not, the intervention has to be quite different than when the child is also concerned about the issue. There are plenty of teens out there that know their psychological desire to talk non-stop with their friends for fear of missing out is putting them in a bad place. Help them through that process and work through what strategies they can develop and learn to cope. Helping them build those coping skills long term will help them a lot more than just putting rules into place.

When there is a disconnect between parent and child’s views on a situation, the best thing a parent can do is try to understand why the disconnect exists.Is it about pleasure seeking? Is it about fear of missing out? Is it about the emotional bond of friendship? Is it about a parent’s priorities being at odds with a child’s priorities? What comes next is fundamentally about values in parenting. Some parents believe that they are the masters of the house and their demands rule the day. Others acquiesce to their children’s desires with no push back. The majority of the parents are in-between. But at the end of the day, parenting is about helping children navigate the world and support them to develop agency in a healthy manner. So I would strongly recommend that parents focus their energies on negotiating a path through that allows children to be bought-in and aware of why boundaries are being set. That requires communication and energy, not a new technology to police boundaries for you. More often than not, the latter sends the wrong message and backfires, not unlike the Black Mirror episode I mentioned earlier.

Good luck parents — parenting is a non-stop adventure filled with both joy and anxiety.

Beyond the Rhetoric of Algorithmic Solutionism

(This was originally posted on Medium)

If you ever hear that implementing algorithmic decision-making tools to enable social services or other high stakes government decision-making will increase efficiency or reduce the cost to taxpayers, know that you’re being lied to. When implemented ethically, these systems cost more. And they should.

Whether we’re talking about judicial decision making (e.g., “risk assessment scoring”) or modeling who is at risk for homelessness, algorithmic systems don’t simply cost money to implement. They cost money to maintain. They cost money to audit. They cost money to evolve with the domain that they’re designed to serve. They cost money to train their users to use the data responsiblyAbove all, they make visible the brutal pain points and root causes in existing systems that require an increase of services.

Otherwise, all that these systems are doing is helping divert taxpayer money from direct services, to lining the pockets of for-profit entities under the illusion of helping people. Worse, they’re helping usher in a diversion of liability because time and time again, those in powerful positions blame the algorithms.

This doesn’t mean that these tools can’t be used responsibly. They can. And they should. The insights that large-scale data analysis can offer is inspiring. The opportunity to help people by understanding the complex interplay of contextual information is invigorating. Any social scientist with a heart desperately wants to understand how to relieve inequality and create a more fair and equitable system. So of course there’s a desire to jump in and try to make sense of the data out there to make a difference in people’s lives. But to treat data analysis as a savior to a broken system is woefully naive.

Doing so obfuscates the financial incentives of those who are building these services, the deterministic rhetoric that they use to justify their implementation, the opacity that results from having non-technical actors try to understand technical jiu-jitsu, and the stark reality of how technology is used as a political bludgeoning tool. Even more frustratingly, what data analysis does well is open up opportunities for experimentation and deeper explorationBut in a zero-sum context, that means that the resources to do something about the information that is learned is siphoned off to the technology. And, worse, because the technology is supposed to save money, there is no budget for using that data to actually help people. Instead,technology becomes a mirage. Not because the technology is inherently bad, but because of how it is deployed and used.

READ THIS BOOK!

Next week, a new book that shows the true cost of these systems is being published. Virginia Eubanks’ book“Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor” is a deeply researched accounting of how algorithmic tools are integrated into services for welfare, homelessness, and child protection. Eubanks goes deep with the people and families who are targets of these systems, telling their stories and experiences in rich detail. Further, drawing on interviews with social services clients and service providers alongside the information provided by technology vendors and government officials, Eubanks offers a clear portrait of just how algorithmic systems actually play out on the ground, despite all of the hope that goes into their implementation.

Eubanks eschews the term “ethnography” because she argues that this book is immersive journalism, not ethnography. Yet, from my perspective as a scholar and a reader, this is the best ethnography I’ve read in yearsAutomating Inequality” does exactly what a good ethnography should do — it offers a compelling account of the cultural logics surrounding a particular dynamic, and invites the reader to truly grok what’s at stake through the eyes of a diverse array of relevant people. Eubanks brings you into the world of technologically mediated social services and helps you see what this really looks like on the ground. She showcases the frustration and anxiety that these implementations produce; the ways in which both social services recipientsand taxpayers are screwed by the false promises of these technologiesShe makes visible the politics and the stakes, the costs and the hope. Above all, she brings the reader into the stark and troubling reality of what it really means to be poor in America today.

“Automating Inequality” is on par with Barbara Ehrenreich’s “Nickel and Dimed” or Matthew Desmond’s “Evicted. It’s rigorously researched, phenomenally accessible, and utterly humbling. While there are a lot of important books that touch on the costs and consequences of technology through case studies and well-reasoned logic, this book is the first one that I’ve read that really pulls you into the world of algorithmic decision-making and inequality, like a good ethnography should.

I don’t know how Eubanks chose her title, but one of the subtle things about her choice is that she’s (unintentionally?) offering a fantastic backronym for AI. Rather than thinking of AI as “artificial intelligence,” Eubanks effectively builds the case for how we should think that AI often means “automating inequality” in practice.

This book should be mandatory for anyone who works in social services, government, or the technology sector because it forces you to really think about what algorithmic decision-making tools are doing to our public sector, and the costs that this has on the people that are supposedly being served. It’s also essential reading for taxpayers and voters who need to understand why technology is not the panacea that it’s often purported to be. Or rather, how capitalizing on the benefits of technology will require serious investment and a deep commitment to improving the quality of social services, rather than a tax cut.

Please please please read this book. It’s too important not to.

Data & Society will also be hosting Virginia Eubanks to talk about her book on January 17th at 4PM ET. She will be in conversation with Julia Angwin and Alondra Nelson. The event is sold out, but it will be livestreamed online. Please feel free to join us there!

The Radicalization of Utopian Dreams

Amazon Fulfillment Center, CC Scottish Government

The following is a transcript of my lightning talk at The People’s Disruption: Platform Co-Ops for Global Challenges— held at The New School. 


When you listen to people in tech talk about the future of labor, they will tell you that AI is taking over all of the jobs. What they gloss over is the gendered dynamics of the labor force. Many of the shortages in the workforce stem from labor that is culturally gendered “feminine” and seen as low-status. There’s no conception of how workforce dynamics in tech are also gendered.

Furthermore, anxieties about automation don’t tend to focus on work that is seen as the work of immigrants, even at a time when immigration is a hotly contested conversation. As a result, when we talk about automation as the major issue in the future of work, we lose track of the broader anxiety about identities that’s shaping both technology and work.

Identities matter because they shape how people respond to the society around them. How do people whose identities have been destabilized respond to a culture where institutions and information intermediaries no longer have their back? When they can’t find their identity through their working environment?

Our current crisis around opioids offers one harrowing answer. Religious extremism offers another. Yet, we also need to consider how many people turn to activism, both healthy and destructive, as a way of finding meaning.

People often find themselves by engaging with others through collective action, but collective action isn’t always productive. Consider this in light of the broader conversation about media manipulationfor those who have grown up gaming, running a raid on America’s political establishment is thrilling. It’s exhilarating to game the media to say ridiculous things. Hacking the attention economy produces a rush. It doesn’t matter whether or not you memed the president into being if you believe you did. It doesn’t even matter if your comrades were foreign agents with a much darker agenda.

For a lot of folks in tech, being a part of tech has been a way of grounding themselves. Many who built the social media infrastructure that we know today grew up with the utopian idealism of people like John Perry Barlow. HisDeclaration of Independence of Cyberspace is now of drinking age, but today’s reality is a lot more sober. Cybernaut geeks imagined building a new world rooted in a different value structure. They wanted to resist the financialized logic of Wall Street, but ended up contributing to the latest evolution of financialized capitalism. They wanted to create a public that was more broadly accessible, but ended up enabling a new wave of corrosive populism to take hold.

They wanted to disrupt the status quo, but weren’t at all prepared for what it would mean when they controlled the infrastructure underlying democracy, the economy, the media, and communication.

Google Plex CC Sebastian Gamboa

You’re at this event today because you also want a new world, a sociotechnical reality that is more cooperative and equitable in nature. You see Silicon Valley as emblematic of corrosive neoliberalism and libertarianism run amok. I get it. But I can’t help but think of how social media was birthed out of idealism that got reworked by economic and political interests, by the stark realities of what people did with technology vs. what its designers hoped they would do.So many of the people that I knew in the early days of tech wanted what you want.

The early adopters of social technologies — and many of those sites’ creators — were self-identified and marginalized geeks, freaks, and queers. Early social tech was built by those who felt like outsiders in a society that valued suave masculinities. Geeks like me who flocked to the Bay felt disenfranchised and vulnerable and turned to technology to build solidarity and feel less alone. In doing so, we helped construct a form of geek masculinity that gave many geeky men in particular a sense of pride that made them feel empowered through their work and play.

But as many of you know, power corrupts. And the same geek masculinities that were once rejuvenating have spiraled out of control. Today, we’re watching as diversity becomes a wedge issue that can be used to radicalize disaffected young men in tech. The gendered nature of tech is getting ugly.

A decade ago, academics that I adore were celebrating participatory culture as emancipatory, noting that technology allowed people to engage with culture in unprecedented ways. Radical leftists were celebrating the possibilities of decentralized technologies as a form of resisting corporate power. Smart mobs were being touted as the mechanism by which authoritarian regimes could come crashing down.

Now, even the most hardened tech geek is quietly asking:

What hath we wrought?

Screen capture courtesy of Ethan Zuckerman

We’ve seen massively decentralized networks coordinating and mobilizing on both for-profit and not-for-profit platforms, challenging the status quo. But the movements that they’re so strategically building are shaped by tribalistic and hate-oriented values. There are many people coordinating online who are willing to share tactic without sharing end goal, yet their tactical moves collectively achieve a form of societal gaslighting that causes unbearable pain.Tech wasn’t designed to enable this, but it did so none-the-less.

Geophysics Hackathon, CC Matt

This room is filled with people who hold dear many progressive values, who see the tech sector as the new establishment, and who are pushing for a more equitable future. I share your values and desires. You rightfully want a more fair and just society. And you rage against the machine. But I also want you to know that I saw similar desires among the early developers of social media as they worked to eject the dot-com MBA culture from Silicon Valley, as they worked to resist the 1980s Wall Street culture, as they tried to operate differently than their parents.. I saw idealism corrupted, good intentions go awry, and malignant forces capitalize on weaknesses within the system.

So as you relish each other’s presence today and tomorrow, I have a favor to ask. Don’t simply focus on what would be ideal or critique the status quo.Genuinely examine how what you’re seeking could also be corrupted and abused. I believe, more than anything, that deep empathy and self-reflection is critical for us to build a healthier future.

Too often, it’s easier to rally people to tear down what we hate than it is to build a sustainable future. And yet, at this moment in time in particular, we desperately need builders. We need you.

Your Data is Being Manipulated

Excerpt from “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” Sergey Brin and Larry Page (April 1998)

What follows is the crib from my keynote at the 2017 Strata Data Conference in New York City. Full video can be found here. 


In 1998, two graduate students at Stanford decided to try to “fix” the problems with major search engines. Sergey Brin and Larry Page wrote a paper describing how their PageRank algorithm could eliminate the plethora of “junk results.” Their idea, which we all now know as the foundation of Google, was critical. But it didn’t stop people from trying to mess with their system. In fact, the rise of Google only increased the sophistication of those invested in search engine optimization.


“google bombing” — diverting search engine rankings to subversive commentary about public figure

Fast forward to 2003, when the sitting Pennsylvania senator Rick Santorum publicly compared homosexuality to bestiality and pedophilia. Needless to say, the LGBT community was outraged. Journalist Dan Savage called on his readers to find a way to “memorialize the scandal.” One of his fans created a website to associate Santorum’s name with anal sex. To the senator’s horror, countless members of the public jumped in to link to that website in an effort to influence search engines. This form of crowdsourced SEO is commonly referred to as “Google bombing,” and it’s a form of media manipulation intended to mess with data and the information landscape.


Media Manipulation and Disinformation Online (cover), March 2017. Illustration by Jim Cooke

Media manipulation is not new. As many adversarial actors know, the boundaries between propaganda and social media marketing are often fuzzy.Furthermore, any company that uses public signals to inform aspects of its product — from Likes to Comments to Reviews — knows full well that any system you create will be gamed for fun, profit, politics, ideology, and power.Even Congress is now grappling with that reality. But I’m not here to tell you what has always been happening or even what is currently happening — I’m here to help you understand what’s about to happen.


At this moment, AI is at the center of every business conversation. Companies, governments, and researchers are obsessed with data. Not surprisingly, so are adversarial actors. We are currently seeing an evolution in how data is being manipulated. If we believe that data can and should be used to inform people and fuel technology, we need to start building the infrastructure necessary to limit the corruption and abuse of that data — and grapple with how biased and problematic data might work its way into technology and, through that, into the foundations of our society.

In short, I think we need to reconsider what security looks like in a data-driven world.

Shutterstock by goir

Part 1: Gaming the System

Like search engines, social media introduced a whole new target for manipulation. This attracted all sorts of people, from social media marketers to state actors. Messing with Twitter’s trending topics or Facebook’s news feed became a hobby for many. For $5, anyone could easily buy followers, likes, and comments on almost every major site. The economic and political incentives are obvious, but alongside these powerful actors, there are also a whole host of people with less-than-obvious intentions coordinating attacks on these systems.


Piechart example of Rick-Rolling

For example, when a distributed network of people decided to help propel Rick Astley to the top of the charts 20 years after his song “Never Gonna Give You Up” first came out, they weren’t trying to help him make a profit (although they did). Like other memes created through networks on sites like 4chan, rickrolling was for kicks. Butthrough this practice, lots of people learned how to make content “go viral” or otherwise mess with systems. In other words, they learned to hack the attention economy. And, in doing so, they’ve developed strategic practices of manipulation that can and do have serious consequences.


A story like “#Pizzagate” doesn’t happen accidentally — it was produced by a wide network of folks looking to toy with the information ecosystem. They created a cross-platform network of fake accounts known as“sock puppets” which they use to subtly influence journalists and other powerful actors to pay attention to strategically produced questions, blog posts, and YouTube videos. The goal with a story like that isn’t to convince journalists that it’s true, but to get them to foolishly use their amplification channels to negate it. This produces a Boomerang effect,” whereby those who don’t trust the media believe that there must be merit to the conspiracy, prompting some to “self-investigate.”


Hydrargyrum CC BY-SA 2.0

Then there’s the universe of content designed to “open the Overton window” — or increase the range of topics that are acceptable to discuss in public. Journalists are tricked into spreading problematic frames. Moreover,recommendation engines can be used to encourage those who are open to problematic frames to go deeper. Researcher Joan Donovan studies white supremacy; after work, she can’t open Amazon, Netflix, or YouTube without being recommended to consume neo-Nazi music, videos, and branded objectsRadical trolls also know how to leverage this infrastructure to cause trouble. Without tripping any of Twitter’s protective mechanisms, the well-known troll weev managed to use the company’s ad infrastructure to amplify white supremacist ideas to those focused on social justice, causing outrage and anger.

By and large, these games have been fairly manual attacks of algorithmic systems, but as we all know, that’s been changing. And it’s about to change again.


Part 2: Vulnerable Training Sets

Training a machine learning system requires data. Lots of it. While there are some standard corpuses, computer science researchers, startups, and big companies are increasingly hungry for new — and different — data.

Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study, June 29, 2017

The first problem is that all data is biased, most notably and recognizably by reflecting the biases of humans and of society in general. Take, for example, the popular ImageNet dataset. Because humans categorize by shape faster than they categorize by color, you end up with some weird artifacts in that data.


(a) and (c) demonstrate ads for two indvidual’s names, (b) and (d) demonstrate that the advertising was suggesting criminal histories based on name type, not actual records

Things get even messier when you’re dealing with social prejudices. WhenLatanya Sweeney searched for her name on Google, she was surprised to be given ads inviting her to find out if she had a criminal record. As a curious computer scientist, she decided to run a range of common black and white names through the system to see which ads popped up. Unsurprisingly, onlyblack names produced ads for criminal justice products. This isn’t because Google knowingly treated the names differently, but because searchers were more likely to click on criminal justice ads when searching for black names.Google learned American racism and amplified it back at all of its users.

Addressing implicit and explicit cultural biases in data is going to be a huge challenge for everyone who is trying to build a system dependent on data classified by or about humans.


But there’s also a new challenge emerging. The same decentralized networks of people — and state actors — who have been messing with social media and search engines are increasingly eyeing the data that various companies use to train and improve their systems.

Consider, for example, the role of reddit and Twitter data as training data. Computer scientists have long pulled from the very generous APIs of these companies to train all sorts of models, trying to understand natural language, develop metadata around links, and track social patterns. They’ve trained models to detect depression, rank news, and engage in conversation. Ignoring the fact that this data is not representative in the first place, most engineers who use these APIs believe that it’s possible to clean the data and remove all problematic content. I can promise you it’s not.

No amount of excluding certain subreddits, removing of categories of tweets, or ignoring content with problematic words will prepare you for those who are hellbent on messing with you.

I’m watching countless actors experimenting with ways to mess with public data with an eye on major companies’ systems. They are trying to fly below the radar. If you don’t have a structure in place for strategically grappling with how those with an agenda might try to route around your best laid plans, you’re vulnerable. This isn’t about accidental or natural content. It’s not even about culturally biased dataThis is about strategically gamified content injected into systems by people who are trying to guess what you’ll do.


If you want to grasp what that means, consider the experiment Nicolas Papernot and his colleagues published last year. In order to understand the vulnerabilities of computer vision algorithms, they decided to alter images of stop signs so that they still resembled a stop sign to a human viewer even as the underlying neural network interpreted them as a yield sign. Think about what this means for autonomous vehicles. Will this technology be widely adopted if the classifier can be manipulated so easily?

Practical Black-Box Attacks against Machine, March 19, 2017. The images in the top row are altered to disrupt the neural network leading to the misinterpretation on the bottom row. The alterations are not visible to the human eye.

Right now, most successful data-injection attacks on machine learning modelsare happening in the world of research, but more and more, we are seeing people try to mess with mainstream systems. Just because they haven’t been particularly successful yet doesn’t mean that they aren’t learning and evolving their attempts.


Part 3: Building Technical Antibodies

Many companies spent decades not taking security vulnerabilities seriously, until breach after breach hit the news. Do we need to go through the same pain before we start building the tools to address this new vulnerability?

If you are building data-driven systems, you need to start thinking about how that data can be corrupted, by whom, and for what purpose.


In the tech industry, we have lost the culture of Test. Part of the blame rests on the shoulders of social media. Fifteen years ago, we got the bright idea to shift to a culture of the “perpetual beta.” We invited the public to be our quality assurance engineers. But internal QA wasn’t simply about finding bugs. It was about integrating adversarial thinking into the design and development process. And asking the public to find bugs in our systems doesn’t work well when some of those same people are trying to mess with our systems.Furthermore, there is currently no incentive — or path — for anyone to privately tell us where things go wrong. Only when journalists shame us by finding ways to trick our systems into advertising to neo-Nazis do we pay attention. Yet, far more maliciously intended actors are starting to play the long game in messing with our data. Why aren’t we trying to get ahead of this?


On the bright side, there’s an emergent world of researchers building adversarial thinking into the advanced development of machine learning systems.

Consider, for example, the research into generative adversarial networks (or GANs). For those unfamiliar with this line of work, the idea is that you have two unsupervised ML algorithms — one is trying to generate content for the other to evaluate. The first is trying to trick the second into accepting “wrong” information. This work is all about trying to find the boundaries of your model and the latent space of your data. We need to see a lot more R&D work like this — this is the research end of a culture of Test, with true adversarial thinking baked directly into the process of building models.


White Hat Hackers — those who hack for “the right reasons.” For instance, testing the security or vulnerabilities of a system (Image: CC Magicon, HU)

But these research efforts are not enough. We need to actively and intentionally build a culture of adversarial testing, auditing, and learning into our development practice. We need to build analytic approaches to assess the biases of any dataset we use. And we need to build tools to monitor how our systems evolve with as much effort as we build our models in the first place.My colleague Matt Goerzen argues that we also need to strategically invite white hat trolls to mess with our systems and help us understand our vulnerabilities.


The tech industry is no longer the passion play of a bunch of geeks trying to do cool shit in the world. It’s now the foundation of our democracy, economy, and information landscape.

We no longer have the luxury of only thinking about the world we want to build. We must also strategically think about how others want to manipulate our systems to do harm and cause chaos.

Data & Society’s Next Stage

In March 2013, in a flurry of days, I decided to start a research institute. I’d always dreamed of doing so, but it was really my amazing mentor and boss – Jennifer Chayes – who put the fire under my toosh. I’d been driving her crazy about the need to have more people deeply interrogating how data-driven technologies were intersecting with society. Microsoft Research didn’t have the structure to allow me to move fast (and break things). University infrastructure was even slower. There were a few amazing research centers and think tanks, but I wanted to see the efforts scale faster. And I wanted to build the structures to connect research and practices, convene conversations across sectors, and bring together a band of what I loved to call “misfit toys.”  So, with the support of Jennifer and Microsoft, I put pen to paper. And to my surprise, I got the green light to help start a wholly independent research institute.

I knew nothing about building an organization. I had never managed anyone, didn’t know squat about how to put together a budget, and couldn’t even create a check list of to-dos. So I called up people smarter than I to help learn how other organizations worked and figure out what I should learn to turn a crazy idea into reality. At first, I thought that I should just go and find someone to run the organization, but I was consistently told that I needed to do it myself, to prove that it could work. So I did. It was a crazy adventure. Not only did I learn a lot about fundraising, management, and budgeting, but I also learned all sorts of things about topics I didn’t even know I would learn to understand – architecture, human resources, audits, non-profit law. I screwed up plenty of things along the way, but most people were patient with me and helped me learn from my mistakes. I am forever grateful to all of the funders, organizations, practitioners, and researchers who took a chance on me.

Still, over the next four years, I never lost that nagging feeling that someone smarter and more capable than me should be running Data & Society. I felt like I was doing the organization a disservice by not focusing on research strategy and public engagement. So when I turned to the board and said, it’s time for an executive director to take over, everyone agreed. We sat down and mapped out what we needed – a strategic and capable leader who’s passionate about building a healthy and sustainable research organization to be impactful in the world. Luckily, we had hired exactly that person to drive program and strategy a year before when I was concerned that I was flailing at managing the fieldbuilding and outreach part of the organization.

I am overwhelmingly OMG ecstatically bouncing for joy to announce that Janet Haven has agreed to become Data & Society’s first executive director. You can read more about Janet through the formal organizational announcement here.  But since this is my blog and I’m telling my story, what I want to say is more personal. I was truly breaking when we hired Janet. I had taken off more than I could chew. I was hitting rock bottom and trying desperately to put on a strong face to support everyone else. As I see it, Janet came in, took one look at the duct tape upon which I’d built the organization and got to work with steel, concrete, and wood in her hands. She helped me see what could happen if we fixed this and that. And then she started helping me see new pathways for moving forward. Over the last 18 months, I’ve grown increasingly confident that what we’re doing makes sense and that we can build an organization that can last. I’ve also been in awe watching her enable others to shine.

I’m not leaving Data & Society. To the contrary, I’m actually taking on the role that my title – founder and president – signals. And I’m ecstatic. Over the last 4.5 years, I’ve learned what I’m good at and what I’m not, what excites me and what makes me want to stay in bed. I built Data & Society because I believe that it needs to exist in this world. But I also realize that I’m the classic founder – the crazy visionary that can kickstart insanity but who isn’t necessarily the right person to take an organization to the next stage. Lucky for me, Janet is. And together, I can’t wait to take Data & Society to the next level!

How “Demo-or-Die” Helped My Career

I left the Media Lab 15 years ago this week. At the time, I never would’ve predicted that I learned one of the most useful skills in my career there: demo-or-die.

(Me debugging an exhibit in 2002)

The culture of “demo-or-die” has been heavily critiqued over the years. In doing so, most folks focus on the words themselves. Sure, the “or-die” piece is definitely an exaggeration, but the important message there is the notion of pressure. But that’s not what most people focus on. They focus on the notion of a “demo.”

To the best that anyone can recall, the root of the term stems back from early days at the Media Lab, most likely because of Nicholas Negroponte’s dismissal of “publish-or-perish” in academia. So the idea was to focus not on writing words but producing artifacts. In mocking what it was that the Media Lab produced, many critics focused on the way in which the Lab had a tendency to create vaporware, performed to visitors through the demo. In 1987, Stewart Brand called this “handwaving.” The historian Molly Steenson has a more nuanced view so I can’t wait to read her upcoming book. But the mockery of the notion of a demo hasn’t died. Given this, it’s not surprising that the current Director (Joi Ito) has pushed people to stop talking about demoing and start thinking about deploying. Hence, “deploy-or-die.”

I would argue that what makes “demo-or-die” so powerful has absolutely nothing to do with the production of a demo. It has to do with the act of doing a demo. And that distinction is important because that’s where the skill development that I relish lies.

When I was at the Lab, we regularly received an onslaught of visitors. I was a part of the “Sociable Media Group,” run by Judith Donath. From our first day in the group, we were trained to be able to tell the story of the Media Lab, the mission of our group, and the goal of everyone’s research projects. Furthermore, we had to actually demo their quasi functioning code and pray that it wouldn’t fall apart in front of an important visitor. We were each assigned a day where we were “on call” to do demos to any surprise visitor. You could expect to have at least one visitor every day, not to mention hundreds of visitors on days that were officially sanctioned as “Sponsor Days.”

The motivations and interests of visitors ranged wildly. You’d have tour groups of VIP prospective students, dignitaries from foreign governments, Hollywood types, school teachers, engineers, and a whole host of different corporate actors. If you were lucky, you knew who was visiting ahead of time. But that was rare. Often, someone would walk in the door with someone else from the Lab and introduce you to someone for whom you’d have to drum up a demo in very short order with limited information. You’d have to quickly discern what this visitor was interested in, figure out which of the team’s research projects would be most likely to appeal, determine how to tell the story of that research in a way that connected to the visitor, and be prepared to field any questions that might emerge. And oy vay could the questions run the gamut.

I *hated* the culture of demo-or-die. I felt like a zoo animal on display for others’ benefit. I hated the emotional work that was needed to manage stupid questions, not to mention the requirement to smile and play nice even when being treated like shit by a visitor. I hated the disruptions and the stressful feeling when a demo collapsed. Drawing on my experience working in fast food, I developed a set of tricks for staying calm. Count how many times a visitor said a certain word. Nod politely while thinking about unicorns. Experiment with the wording of a particular demo to see if I could provoke a reaction. Etc.

When I left the Media Lab, I was ecstatic to never have to do another demo in my life. Except, that’s the funny thing about learning something important… you realize that you are forever changed by the experience.

I no longer produce demos, but as I developed in my career, I realized that “demo-or-die” wasn’t really about the demo itself. At the end of the day, the goal wasn’t to pitch the demo — it was to help the visitor change their perspective of the world through the lens of the demo. In trying to shift their thinking, we had to invite them to see the world differently. The demo was a prop. Everything about what I do as a researcher is rooted in the goal of using empirical work to help challenge people’s assumptions and generate new frames that people can work with. I have to understand where they’re coming from, appreciate their perspective, and then strategically engage them to shift their point of view. Like my days at the Media Lab, I don’t always succeed and it is indeed frustrating, especially because I don’t have a prop that I can rely on when everything goes wrong. But spending two years developing that muscle has been so essential for my work as an ethnographer, researcher, and public speaker.

I get why Joi reframed it as “deploy-or-die.” When it comes to actually building systems, impact is everything. But I really hope that the fundamental practice of “demo-or-die” isn’t gone. Those of us who build systems or generate knowledge day in and day out often have too little experience explaining ourselves to the wide array of folks who showed up to visit the Media Lab. It’s easy to explain what you do to people who share your ideas, values, and goals. It’s a lot harder to explain your contributions to those who live in other worlds. Impact isn’t just about deploying a system; it’s about understanding how that system or idea will be used. And that requires being able to explain your thinking to anyone at any moment. And that’s the skill that I learned from the “demo-or-die” culture.

Tech Culture Can Change

We need: Recognition, Repentance, Respect, and Reparation.

To be honest, what surprises me most about the current conversation about the inhospitable nature of tech for women is that people are surprised. To say that discrimination, harassment, and sexual innuendos are an open secret is an understatement. I don’t know a woman in tech who doesn’t have war stories. Yet, for whatever reason, we are now in a moment where people are paying attention. And for that, I am grateful.

Like many women in tech, I’ve developed strategies for coping. I’ve had to in order to stay in the field. I’ve tried to be “one of the guys,” pretending to blend into the background as sexist speech was jockeyed about in the hopes that I could just fit in. I’ve tried to be the kid sister, the freaky weirdo, the asexual geek, etc. I’ve even tried to use my sexuality to my advantage in the hopes that maybe I could recover some of the lost opportunity that I faced by being a woman. It took me years to realize that none of these strategies would make me feel like I belonged. Many even made me feel worse.

For years, I included Ani DiFranco lyrics in every snippet of code I wrote, as well as my signature. I’ve maintained a lyrics site since I was 18 because her words give me strength for coping with the onslaught of commentary and gross behavior. “Self-preservation is a full-time occupation.” I can’t tell you how often I’ve sat in a car during a conference or after a meeting singing along off-key at full volume with tears streaming down my face, just trying to keep my head together.

What’s at stake is not about a few bad actors. There’s also a range of behaviors getting lumped together, resulting in folks asking if inescapable sexual overtures are really that bad compared to assault. That’s an unproductive conversation because the fundamental problem is the normalization of atrocious behavior that makes room for a wide range of inappropriate actions. Fundamentally, the problem with systemic sexism is that it’s not the individual people who are the problem. It’s the culture. And navigating the culture is exhausting and disheartening. It’s the collection of particles of sand that quickly becomes a mountain that threatens to bury you.

It’s having to constantly stomach sexist comments with a smile, having to work twice as hard to be heard in a meeting, having to respond to people who ask if you’re on the panel because they needed a woman. It’s about going to conferences where deals are made in the sauna but being told that you have to go to the sauna with “the wives” (a pejoratively constructed use of the word). It’s about people assuming you’re sleeping with whoever said something nice about you. It’s being told “you’re kinda smart for a chick” when you volunteer to help a founder. It’s knowing that you’ll receive sexualized threats for commenting on certain topics as a blogger. It’s giving a talk at a conference and being objectified by the audience. It’s building whisper campaigns among women to indicate which guys to avoid. It’s using Dodgeball/Foursquare to know which parties not to attend based on who has checked in. It’s losing friends because you won’t work with a founder who you watched molest a woman at a party (and then watching Justin Timberlake portray that founder’s behavior as entertainment).

Lots of people in tech have said completely inappropriate things to women. I also recognize that many of those guys are trying to fit into the sexist norms of tech too, trying to replicate the culture that they see around them because they too are struggling for status. But that’s the problem. Once guys receive power and status within the sector, they don’t drop their inappropriate language. They don’t change their behavior or call out others on how insidious it is. They let the same dynamics fester as though it’s just part of the hazing ritual.

For women who succeed in tech, the barrage of sexism remains. It just changes shape as we get older.

On Friday night, after reading the NYTimes article on tech industry harassment, I was deeply sad. Not because the stories were shocking — frankly, those incidents are minor compared to some of what I’ve seen. I was upset because stories like this typically polarize and prompt efforts to focus on individuals rather than the culture. There’s an assumption that these are one-off incidents. They’re not.

I appreciate that Dave and Chris owned up to their role in contributing to a hostile culture. I know that it’s painful to hear that something you said or did hurt someone else when you didn’t intend that to be the case. I hope that they’re going through a tremendous amount of soul-searching and self-reflection. I appreciate Chris’ willingness to take to Medium to effectively say “I screwed up.” Ideally, they will both come out of this willing to make amends and right their wrongs.

Unfortunately, most people don’t actually respond productively when they’re called out. Shaming can often backfire.

One of the reasons that most people don’t speak up is that it’s far more common for guys who are called out on their misdeeds to respond the way that Marc Canter appeared to do, by justifying his behavior and demonizing the woman who accused him of sexualizing her. Given my own experiences with his sexist commentary, I decided to tweet out in solidarity by publicly sharing how he repeatedly asked me for a threesome with his wife early on in my career. At the time, I was young and I was genuinely scared of him; I spent a lot of time and emotional energy avoiding him, and struggled with how to navigate him at various conferences. I wasn’t the only one who faced his lewd comments, often framed as being sex-positive even when they were an abuse of power. My guess is that Marc has no idea how many women he’s made feel uncomfortable, ashamed, and scared. The question is whether or not he will admit that to himself, let alone to others.

I’m not interested in calling people out for sadistic pleasure. I want to see the change that most women in tech long for. At its core, the tech industry is idealistic and dreamy, imagining innovations that could change the world. Yet, when it comes to self-reflexivity, tech is just as regressive as many other male-dominated sectors. Still, I fully admit that I hold it to a higher standard in no small part because of the widespread commitment in tech to change the world for the better, however flawed that fantastical idealism is.

Given this, what I want from men in tech boils down to four Rs: Recognition. Repentance. Respect. Reparation.

Recognition. I want to see everyone — men and women — recognize how contributing to a culture of sexism takes us down an unhealthy path, not only making tech inhospitable for women but also undermining the quality of innovation and enabling the creation of tech that does societal harm. I want men in particular to reflect on how the small things that they do and say that they self-narrate as part of the game can do real and lasting harm, regardless of what they intended or what status level they have within the sector. I want those who witness the misdeeds of others to understand that they’re contributing to the problem.

Repentance. I want guys in tech — and especially those founders and funders who hold the keys to others’ opportunity — to take a moment and think about those that they’ve hurt in their path to success and actively, intentionally, and voluntarily apologize and ask for forgiveness. I want them to reach out to someone they said something inappropriate to, someone whose life they made difficult and say “I’m sorry.”

Respect. I want to see a culture of respect actively nurtured and encouraged alongside a culture of competition. Respect requires acknowledging others’ struggles, appreciating each others’ strengths and weaknesses, and helping each other through hard times. Many of the old-timers in tech are nervous that tech culture is being subsumed by financialization. Part of resisting this transformation is putting respect front and center. Long-term success requires thinking holistically about society, not just focusing on current capitalization.

Reparation. Every guy out there who wants to see tech thrive owes it to the field to actively seek out and mentor, support, fund, open doors for, and otherwise empower women and people of color. No excuses, no self-justifications, no sexualized bullshit. Just behavior change. Plain and simple. If our sector is about placing bets, let’s bet on a better world. And let’s solve for social equity.

I have a lot of respect for the women who are telling their stories, but we owe it to them to listen to the culture that they’re describing. Sadly, there are so many more stories that are not yet told. I realize that these stories are more powerful when people are named. My only hope is that those who are risking the backlash to name names will not suffer for doing so. Ideally, those who are named will not try to self-justify but acknowledge and accept that they’ve caused pain. I strongly believe that changing the norms is the only path forward. So while I want to see people held accountable, I especially want to see the industry work towards encouraging and supporting behavior change. At the end of the day, we will not solve the systemic culture of sexism by trying to weed out bad people, but we can work towards rendering bad behavior permanently unacceptable.

Failing to See, Fueling Hatred.

I was 19 years old when a some configuration of anonymous people came after me. They got access to my email and shared some of the most sensitive messages on an anonymous forum. This was after some of my girl friends received anonymous voice messages describing how they would be raped. And after the black and Latinx high school students I was mentoring were subject to targeted racist messages whenever they logged into the computer cluster we were all using. I was ostracized for raising all of this to the computer science department’s administration. A year later, when I applied for an internship at Sun Microsystems, an alum known for his connection to the anonymous server that was used actually said to me, “I thought that they managed to force you out of CS by now.”

Needless to say, this experience hurt like hell. But in trying to process it, I became obsessed not with my own feelings but with the logics that underpinned why some individual or group of white male students privileged enough to be at Brown University would do this. (In investigations, the abusers were narrowed down to a small group of white men in the department but it was never going to be clear who exactly did it and so I chose not to pursue the case even though law enforcement wanted me to.)

My first breakthrough came when I started studying bullying, when I started reading studies about why punitive approaches to meanness and cruelty backfire. It’s so easy to hate those who are hateful, so hard to be empathetic to where they’re coming from. This made me double down on an ethnographic mindset that requires that you step away from your assumptions and try to understand the perspective of people who think and act differently than you do. I’m realizing more and more how desperately this perspective is needed as I watch researchers and advocates, politicians and everyday people judge others from their vantage point without taking a moment to understand why a particular logic might unfold.

The Local Nature of Wealth

A few days ago, my networks were on fire with condescending comments referencing an article in The Guardian titled “Scraping by on six figures? Tech workers feel poor in Silicon Valley’s wealth bubble.” I watched as all sorts of reasonably educated, modestly but sustainably paid people mocked tech folks for expressing frustration about how their well-paid jobs did not allow them to have the sustainable lifestyle that they wanted. For most, Silicon Valley is at a distance, a far off land of imagination brought to you by the likes of David Fincher and HBO. Progressive values demand empathy for the poor and this often manifests as hatred for the rich. But what’s missing from this mindset is an understanding of the local perception of wealth, poverty, and status. And, more importantly, the political consequences of that local perception.

Think about it this way. I live in NYC where the median household income is somewhere around $55K. My network primarily makes above the median and yet they all complain that they don’t have enough money to achieve what they want in NYC, whether they’re making $55K, $70K, or $150K. Complaining about being not having enough money is ritualized alongside complaining about the rents. No one I know really groks that they’re making above the median income for the city (and, thus, that most people are much poorer than they are), let alone how absurd their complaints might sound to someone from a poorer country where a median income might be $1500 (e.g., India).

The reason for this is not simply that people living in NYC are spoiled, but that people’s understanding of prosperity is shaped by what they see around them. Historically, this has been understood through word-of-mouth and status markers. In modern times, those status markers are often connected to conspicuous consumption. “How could HE afford a new pair of Nikes!?!?”

The dynamics of comparison are made trickier by media. Even before yellow journalism, there has always been some version of Page Six or “Lifestyles of the Rich and Famous.” Stories of gluttonous and extravagant behaviors abound in ancient literature. Today, with Instagram and reality TV, the idea of haves and havenots is pervasive, shaping cultural ideas of privilege and suffering. Everyday people perform for the camera and read each other’s performances critically. And still, even as we watch rich people suffer depression or celebrities experience mental breakdowns, we don’t know how to walk in each other’s shoes. We collectively mock them for their privilege as a way to feel better for our own comparative struggles.

In other words, in a neoliberal society, we consistently compare ourselves to others in ways that make us feel as though we are less well off than we’d like. And we mock others who are more privileged who do the same. (And, horribly, we often blame others who are not for making bad decisions.)

The Messiness of Privilege

I grew up with identity politics, striving to make sense of intersectional politics and confused about what it meant to face oppression as a woman and privilege as a white person. I now live in a world of tech wealth while my family does not. I live with contradictions and I work on issues that make those contradictions visible to me on a regular basis. These days, I am surrounded by civil rights advocates and activists of all stripes. Folks who remind me to take my privilege seriously. And still, I struggle to be a good ally, to respond effectively to challenges to my actions. Because of my politics and ideals, I wake up each day determined to do better.

Yet, with my ethnographer’s hat on, I’m increasingly uncomfortable with how this dynamic is playing out. Not for me personally, but for affecting change. I’m nervous that the way that privilege is being framed and politicized is doing damage to progressive goals and ideals. In listening to white men who see themselves as “betas” or identify as NEETs (“Not in Education, Employment, or Training”) describe their hatred of feminists or social justice warriors, I hear the cost of this frame. They don’t see themselves as empowered or privileged and they rally against these frames. And they respond antagonistically in ways that further the divide, as progressives feel justified in calling them out as racist and misogynist. Hatred emerges on both sides and the disconnect produces condescension as everyone fails to hear where each other comes from, each holding onto their worldview that they are the disenfranchised, they are the oppressed. Power and wealth become othered and agency becomes understood through the lens of challenging what each believes to be the status quo.

It took me years to understand that the boys who tormented me in college didn’t feel powerful, didn’t see their antagonism as oppression. I was even louder and more brash back then than I am now. I walked into any given room performing confidence in ways that completely obscured my insecurities. I took up space, used my sexuality as a tool, and demanded attention. These were the survival skills that I had learned to harness as a ticket out. And these are the very same skills that have allowed me to succeed professionally and get access to tremendous privilege. I have paid a price for some of the games that I have played, but I can’t deny that I’ve gained a lot in the process. I have also come to understand that my survival strategies were completely infuriating to many geeky white boys that I encountered in tech. Many guys saw me as getting ahead because I was a token woman. I was accused of sleeping my way to the top on plenty of occasions. I wasn’t simply seen as an alpha — I was seen as the kind of girl that screwed boys over. And because I was working on diversity and inclusion projects in computer science to attract more women and minorities as the field, I was seen as being the architect of excluding white men. For so many geeky guys I met, CS was the place where they felt powerful and I stood for taking that away. I represented an oppressor to them even though I felt like it was they who were oppressing me.

Privilege is complicated. There is no static hierarchical structure of oppression. Intersectionality provides one tool for grappling with the interplay between different identity politics, but there’s no narrative for why beta white male geeks might feel excluded from these frames. There’s no framework for why white Christians might feel oppressed by rights-oriented activists. When we think about privilege, we talk about the historical nature of oppression, but we don’t account for the ways in which people’s experiences of privilege are local. We don’t account for the confounding nature of perception, except to argue that people need to wake up.

Grappling with Perception

We live in a complex interwoven society. In some ways, that’s intentional. After WWII, many politicians and activists wanted to make the world more interdependent, to enable globalization to prevent another world war. The stark reality is that we all depend on social, economic, and technical infrastructures that we can’t see and don’t appreciate. Sure, we can talk about how our food is affordable because we’re dependent on underpaid undocumented labor. We can take our medicine for granted because we fail to appreciate all of the regulatory processes that go into making sure that what we consume is safe. But we take lots of things for granted; it’s the only way to move through the day without constantly panicking about whether or not the building we’re in will collapse.

Without understanding the complex interplay of things, it’s hard not to feel resentful about certain things that we do see. But at the same time, it’s not possible to hold onto the complexity. I can appreciate why individuals are indignant when they feel as though they pay taxes for that money to be given away to foreigners through foreign aid and immigration programs. These people feel like they’re struggling, feel like they’re working hard, feel like they’re facing injustice. Still, it makes sense to me that people’s sense of prosperity is only as good as their feeling that they’re getting ahead. And when you’ve been earning $40/hour doing union work only to lose that job and feel like the only other option is a $25/hr job, the feeling is bad, no matter that this is more than most people make. There’s a reason that Silicon Valley engineers feel as though they’re struggling and it’s not because they’re comparing themselves to everyone in the world. It’s because the standard of living keeps dropping in front of them. It’s all relative.

It’s easy to say “tough shit” or “boo hoo hoo” or to point out that most people have it much worse. And, at some levels, this is true. But if we don’t account for how people feel, we’re not going to achieve a more just world — we’re going to stoke the fires of a new cultural war as society becomes increasingly polarized.

The disconnect between statistical data and perception is astounding. I can’t help but shake my head when I listen to folks talk about how life is better today than it ever has been in history. They point to increased lifespan, new types of medicine, decline in infant mortality, and decline in poverty around the world. And they shake their heads in dismay about how people don’t seem to get it, don’t seem to get that today is better than yesterday. But perception isn’t about statistics. It’s about a feeling of security, a confidence in one’s ecosystem, a belief that through personal effort and God’s will, each day will be better than the last. That’s not where the vast majority of people are at right now. To the contrary, they’re feeling massively insecure, as though their world is very precarious.

I am deeply concerned that the people whose values and ideals I share are achieving solidarity through righteous rhetoric that also produces condescending and antagonistic norms. I don’t fully understand my discomfort, but I’m scared that what I’m seeing around me is making things worse. And so I went back to some of Martin Luther King Jr.’s speeches for a bit of inspiration today and I started reflecting on his words. Let me leave this reflection with this quote:

The ultimate weakness of violence is that it is a descending spiral,
begetting the very thing it seeks to destroy.
Instead of diminishing evil, it multiplies it.
Through violence you may murder the liar,
but you cannot murder the lie, nor establish the truth.
Through violence you may murder the hater,
but you do not murder hate.
In fact, violence merely increases hate.
So it goes.
Returning violence for violence multiplies violence,
adding deeper darkness to a night already devoid of stars.
Darkness cannot drive out darkness:
only light can do that.
Hate cannot drive out hate: only love can do that.
— Dr. Martin Luther King, Jr.

Image from Flickr: Andy Doyle

Heads Up: Upcoming Parental Leave

There’s a joke out there that when you’re having your first child, you tell everyone personally and update your family and friends about every detail throughout the pregnancy. With Baby #2, there’s an abbreviated notice that goes out about the new addition, all focused on how Baby #1 is excited to have a new sibling. And with Baby #3, you forget to tell people.

I’m a living instantiation of that. If all goes well, I will have my third child in early March and I’ve apparently forgotten to tell anyone since folks are increasingly shocked when I indicate that I can’t help out with XYZ because of an upcoming parental leave. Oops. Sorry!

As noted when I gave a heads up with Baby #1 and Baby #2, I plan on taking parental leave in stride. I don’t know what I’m in for. Each child is different and each recovery is different. What I know for certain is that I don’t want to screw over collaborators or my other baby – Data & Society. As a result, I will be not taking on new commitments and I will be actively working to prioritize my collaborators and team over the next six months.

In the weeks following birth, my response rates may get sporadic and I will probably not respond to non-mission-critical email. I also won’t be scheduling meetings. Although I won’t go completely offline in March (mostly for my own sanity), but I am fairly certain that I will take an email sabbatical in July when my family takes some serious time off** to be with one another and travel.

A change in family configuration is fundamentally walking into the abyss. For as much as our culture around maternity leave focuses on planning, so much is unknown. After my first was born, I got a lot of work done in the first few weeks afterwards because he was sleeping all the time and then things got crazy just as I was supposedly going back to work. That was less true with #2, but with #2 I was going seriously stir crazy being home in the cold winter and so all I wanted was to go to lectures with him to get out of bed and soak up random ideas. Who knows what’s coming down the pike. I’m fortunate enough to have the flexibility to roll with it and I intend to do precisely that.

What’s tricky about being a parent in this ecosystem is that you’re kinda damned if you do, damned if you don’t. Women are pushed to go back to work immediately to prove that they’re serious about their work – or to take serious time off to prove that they’re serious about their kids. Male executives are increasingly publicly talking about taking time off, while they work from home.  The stark reality is that I love what I do. And I love my children. Life is always about balancing different commitments and passions within the constraints of reality (time, money, etc.).  And there’s nothing like a new child to make that balancing act visible.

So if you need something from me, let me know ASAP!  And please understand and respect that I will be navigating a lot of unknown and doing my best to achieve a state of balance in the upcoming months of uncertainty.

 

** July 2017 vacation. After a baby is born, the entire focus of a family is on adjustment. For the birthing parent, it’s also on recovery because babies kinda wreck your body no matter how they come out. Finding rhythms for sleep and food become key for survival. Folks talk about this time as precious because it can enable bonding. That hasn’t been my experience and so I’ve relished the opportunity with each new addition to schedule some full-family bonding time a few months after birth where we can do what our family likes best – travel and explore as a family. If all goes well in March, we hope to take a long vacation in mid-July where I intend to be completely offline and focused on family. More on that once we meet the new addition.

When Good Intentions Backfire

… And Why We Need a Hacker Mindset


I am surrounded by people who are driven by good intentions. Educators who want to inform students, who passionately believe that people can be empowered through knowledge. Activists who have committed their lives to addressing inequities, who believe that they have a moral responsibility to shine a spotlight on injustice. Journalists who believe their mission is to inform the public, who believe that objectivity is the cornerstone of their profession. I am in awe of their passion and commitment, their dedication and persistence.

Yet, I’m existentially struggling as I watch them fight for what is right. I havelearned that people who view themselves through the lens of good intentions cannot imagine that they could be a pawn in someone else’s game. They cannot imagine that the values and frames that they’ve dedicated their lives towards — free speech, media literacy, truth — could be manipulated or repurposed by others in ways that undermine their good intentions.

I find it frustrating to bear witness to good intentions getting manipulated,but it’s even harder to watch how those who are wedded to good intentions are often unwilling to acknowledge this, let alone start imagining how to develop the appropriate antibodies. Too many folks that I love dearly just want to double down on the approaches they’ve taken and the commitments they’ve made. On one hand, I get it — folks’ life-work and identities are caught up in these issues.

But this is where I think we’re going to get ourselves into loads of trouble.

The world is full of people with all sorts of intentions. Their practices and values, ideologies and belief systems collide in all sorts of complex way. Sometimes, the fight is about combating horrible intentions, but often it is not. In college, my roommate used to pound a mantra into my head whenever I would get spun up about something: Do not attribute to maliciousness what you can attribute to stupidity. I return to this statement a lot when I think about how to build resilience and challenge injustices, especially when things look so corrupt and horribly intended — or when people who should be allies see each other as combatants. But as I think about how we should resist manipulation and fight prejudice, I also think that it’s imperative to move away from simply relying on “good intentions.”

I don’t want to undermine those with good intentions, but I also don’t want good intentions to be a tool that can be used against people. So I want to think about how good intentions get embedded in various practices and the implications of how we view the different actors involved.

The Good Intentions of Media Literacy

When I penned my essay “Did Media Literacy Backfire?”, I wanted to ask those who were committed to media literacy to think about how their good intentions — situated in a broader cultural context — might not play out as they would like. Folks who critiqued my essay on media literacy pushed back in all sorts of ways, both online and off. Many made me think, but some also reminded me that my way of writing was off-putting. I was accused of using the question “Did media literacy backfire?” to stoke clicks.Some snarkily challenged my suggestion that media literacy was even meaningfully in existence, asked me to be specific about which instantiations I meant (because I used the phrase “standard implementations”), and otherwise pushed for the need to double down on “good” or “high quality” media literacy. The reality is that I’m a huge proponent of their good intentions — and have long shared them, but I wrote this piece because I’m worried that good intentions can backfire.

While I was researching youth culture, I never set out to understand what curricula teachers used in the classroom. I wasn’t there to assess the quality of the teachers or the efficacy of their formal educational approaches. I simply wanted to understand what students heard and how they incorporated the lessons they received into their lives. Although the teens that I met had a lot of choice words to offer about their teachers, I’ve always assumed that most teachers entered the profession with the best of intentions, even if their students couldn’t see that. But I spent my days listening to students’ frustrations and misperceptions of the messages teachers offered.

I’ve never met an educator who thinks that the process of educating is easy or formulaic. (Heck, this is why most educators roll their eyes when they hear talk of computerized systems that can educate better than teachers.) So why do we assume that well-intended classroom lessons — or even well-designed curricula — might not play out as we imagine? This isn’t simply about the efficacy of the lesson or the skill of the teacher, but the cultural context in which these conversations occur.

In many communities in which I’ve done research, the authority of teachers is often questioned. Nowhere is this more painfully visible than when well-intended highly educated (often white) teachers come to teach in poorer communities of color. Yet, how often are pedagogical interventions designed by researchers really taking into account the doubt that students and their parents have of these teachers? And how do we as educators and scholars grapple with how we might have made mistakes?

I’m not asking “Did Media Literacy Backfire?” to be a pain in the toosh, but to genuinely highlight how the ripple effects of good intentions may not play out as imagined on the ground for all sorts of reasons.

The Good Intentions of Engineers

From the outside, companies like Facebook and Google seem pretty evil to many people. They’re situated in a capitalist logic that many advocates and progressives despise. They’re opaque and they don’t engage the public in their decision-making processes, even when those decisions have huge implications for what people read and think. They’re extremely powerful and they’ve made a lot of people rich in an environment where financial inequality and instability is front and center. Primarily located in one small part of the country, they also seem like a monolithic beast.

As a result, it’s not surprising to me that many people assume that engineers and product designers have evil (or at least financially motivated) intentions. There’s an irony here because my experience is the opposite.Most product teams have painfully good intentions, shaped by utopic visions of how the ideal person would interact with the ideal system. Nothing is more painful than sitting through a product design session with design personae that have been plucked from a collection of clichés.

I’ve seen a lot of terribly naive product plans, with user experience mockups that lack any sense of how or why people might interact with a system in unexpected ways. I spent years tracking how people did unintended things with social media, such as the rise of “Fakesters,” or of teenagers who gamed Facebook’s system by inserting brand names into their posts, realizing that this would make their posts rise higher in the social network’s news feed. It has always boggled my mind how difficult it is for engineers and product designers to imagine how their systems would get gamed. I actually genuinely loved product work because I couldn’t help but think about how to break a system through unexpected social practices.

Most products and features that get released start with good intentions, but they too get munged by the system, framed by marketing plans, and manipulated by users. And then there’s the dance of chaos as companies seek to clean up PR messes (which often involves non-technical actors telling insane fictions about the product), patch bugs to prevent abuse, and throw bandaids on parts of the code that didn’t play out as intended. There’s a reason that no one can tell you exactly how Google’s search engine or Facebook’s news feed works. Sure, the PR folks will tell you that it’s proprietary code. But the ugly truth is that the code has been patched to smithereens to address countless types of manipulation and gamification(e.g., SEO to bots). It’s quaint to read the original “page rank” paper that Brin and Page wrote when they envisioned how a search engine could ideally work. That’s so not how the system works today.

The good intentions of engineers and product people, especially those embedded in large companies, are often doubted as sheen for a capitalist agenda. Yet, like many other well-intended actors, I often find that makers feel misunderstood and maligned, assumed to have evil thoughts. And I often think that when non-tech people start by assuming that they’re evil, we lose a significant opportunity to address problems.

The Good Intentions of Journalists

I’ve been harsh on journalists lately, mostly because I find it so infuriating that a profession that is dedicated to being a check to power could be so ill-equipped to be self-reflexive about its own practices.

Yet, I know that I’m being unfair. Their codes of conduct and idealistic visions of their profession help journalists and editors and publishers stay strong in an environment where they are accustomed to being attacked. It just kills me that the cultural of journalism makes those who have an important role to play unable to see how they can be manipulated at scale.

Sure, plenty of top-notch journalists are used to negotiating deception and avoidance. You gotta love a profession that persistently bangs its head against a wall of “no comment.” But journalism has grown up as an individual sport; a competition for leads and attention that can get fugly in the best of configurations. Time is rarely on a journalist’s side, just as nuance is rarely valued by editors. Trying to find “balance” in this ecosystem has always been a pipe dream, but objectivity is a shared hallucination that keeps well-intended journalists going.

Powerful actors have always tried to manipulate the news media, especially State actors. This is why the fourth estate is seen as so important in the American context. Yet, the game has changed, in part because of the distributed power of the masses. Social media marketers quickly figured out that manufacturing outrage and spectacle would give them a pathway to attention, attracting news media like bees to honey. Most folks rolled their eyes, watching as monied people played the same games as State actors. But what about the long tail? How do we grapple with the long tail? How should journalists respond to those who are hacking the attention economy?

I am genuinely struggling to figure out how journalists, editors, and news media should respond in an environment in which they are getting gamed.What I do know from 12-steps is that the first step is to admit that you have a problem. And we aren’t there yet. And sadly, that means that good intentions are getting gamed.

Developing the Hacker Mindset

I’m in awe of how many of the folks I vehemently disagree with are willing to align themselves with others they vehemently disagree with when they have a shared interest in the next step. Some conservative and hate groups are willing to be odd bedfellows because they’re willing to share tactics, even if they don’t share end goals. Many progressives can’t even imagine coming together with folks who have a slightly different vision, let alone a different end goal, to even imagine various tactics. Why is that?

My goal in writing these essays is not because I know the solutions to some of the most complex problems that we face — I don’t — but because I think that we need to start thinking about these puzzles sideways, upside down, and from non-Euclidean spaces. In short, I keep thinking that we need more well-intended folks to start thinking like hackers.

Think just as much about how you build an ideal system as how it might be corrupted, destroyed, manipulated, or gamed. Think about unintended consequences, not simply to stop a bad idea but to build resilience into the model.

As a developer, I always loved the notion of “extensibility” because it was an ideal of building a system that could take unimagined future development into consideration. Part of why I love the notion is that it’s bloody impossible to implement. Sure, I (poorly) comment my code and build object-oriented structures that would allow for some level of technical flexibility. But, at the end of the day, I’d always end up kicking myself for not imagining a particular use case in my original design and, as a result, doing a lot more band-aiding than I’d like to admit. The masters of software engineering extensibility are inspiring because they don’t just hold onto the task at hand, but have a vision for all sorts of different future directions that may never come into fruition. That thinking is so key to building anything, whether it be software or a campaign or a policy. And yet, it’s not a muscle that we train people to develop.

If we want to address some of the major challenges in civil society, we need the types of people who think 10 steps ahead in chess, imagine innovative ways of breaking things, and think with extensibility at their core. More importantly, we all need to develop that sensibility in ourselves. This is the hacker mindset.

This post was originally posted on Points. It builds off of a series of essays on topics affecting the public sphere written by folks at Data & Society. As expected, my earlier posts ruffled some feathers, and I’ve been trying to think about how to respond in a productive manner. This is my attempt.

Flickr Image: CC BY 2.0-licensed image by DaveBleasdale.