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Nature Machine

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[Image: Illustration by Benjamin Marra for the New York Times Magazine].

As part of a package of shorter articles in the New York Times Magazine exploring the future implications of self-driving vehicles—how they will affect urban design, popular culture, and even illegal drug activity—writer Malia Wollan focuses on “the end of roadkill.”

Her premise is fascinating. Wollan suggests that the precision driving enabled by self-driving vehicle technology could put an end to vehicular wildlife fatalities. Bears, deer, raccoons, panthers, squirrels—even stray pets—might all remain safe from our weapons-on-wheels. In the process, self-driving cars would become an unexpected ally for wildlife preservation efforts, with animal life potentially experiencing dramatic rebounds along rural and suburban roads. This will be both good and bad. One possible outcome sounds like a tragicomic Coen Brothers film about apocalyptic animal warfare in the American suburbs:

Every year in the United States, there are an estimated 1.5 million deer-vehicle crashes. If self-driving cars manage to give deer safe passage, the fast-reproducing species would quickly grow beyond the ability of the vegetation to sustain them. “You’d get a lot of starvation and mass die-offs,” says Daniel J. Smith, a conservation biologist at the University of Central Florida who has been studying road ecology for nearly three decades… “There will be deer in people’s yards, and there will be snipers in towns killing them,” [wildlife researcher Patricia Cramer] says.

While these are already interesting points, Wollan explains that, for this to come to pass, we will need to do something very strange. We will need to teach self-driving cars how to recognize nature.

“Just how deferential [autonomous vehicles] are toward wildlife will depend on human choices and ingenuity. For now,” she adds, “the heterogeneity and unpredictability of nature tends to confound the algorithms. In Australia, hopping kangaroos jumbled a self-driving Volvo’s ability to measure distance. In Boston, autonomous-vehicle sensors identified a flock of sea gulls as a single form rather than a collection of individual birds. Still, even the tiniest creatures could benefit. ‘The car could know: “O.K., this is a hot spot for frogs. It’s spring. It’s been raining. All the frogs will be moving across the road to find a mate,”’ Smith says. The vehicles could reroute to avoid flattening amphibians on that critical day.”

One might imagine that, seen through the metaphoric eyes of a car’s LiDAR array, all those hopping kangaroos appeared to be a single super-body, a unified, moving wave of flesh that would have appeared monstrous, lumpy, even grotesque. Machine horror.

What interests me here is that, in Wollan’s formulation, “nature” is that which remains heterogeneous and unpredictable—that which remains resistant to traditional representation and modeling—yet this is exactly what self-driving car algorithms will have to contend with, and what they will need to recognize and correct for, if we want them to avoid colliding with a nonhuman species.

In particular, I love Wollan’s use of the word “deferential.” The idea of cars acting with deference to the natural world, or to nonhuman species in general, opens up a whole other philosophical conversation. For example, what is the difference between deference and reverence, and how we might teach our fellow human beings, let alone our machines, to defer to, even to revere, the natural world? Put another way, what does it mean for a machine to “encounter” the wild?

Briefly, Wollan’s piece reminded me of Robert MacFarlane’s excellent book The Wild Places for a number of reasons. Recall that book’s central premise: the idea that wilderness is always closer than it appears. Roadside weeds, overgrown lots, urban hikes, peripheral species, the ground beneath your feet, even the walls of the house around you: these all constitute “wilderness” at a variety of scales, if only we could learn to recognize them as such. Will self-driving cars spot “nature” or “wilderness” in sites where humans aren’t conceptually prepared to see it?

The challenge of teaching a car how to recognize nature thus takes on massive and thrilling complexity here, all wrapped up in the apparently simple goal of ending roadkill. It’s about where machines end and animals begin—or perhaps how technology might begin before the end of wilderness.

In any case, Wollan’s short piece is worth reading in full—and don’t miss a much earlier feature she wrote on the subject of roadkill for the New York Times back in 2010.

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rosskarchner
13 days ago
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Retention and the Cross-Generational Pipeline

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A few years ago, Ben Horowitz gave a talk called The Future of Humankind is Dependent on Technovation Girls. Horowitz claims that "if you educate a girl in the developing world, you educate five people – on average...because if you educate one girl, then she will educate at least four other people through the course of her life" [1]. He believes the same is true for the technology industry; that if you teach one girl computer programming, she will teach others and the ratio of women in the field will improve.

This is a nice idea, but what if the exact opposite is happening?

What if women are leaving the tech industry before they can educate other women? Or, worse, what if women in the tech industry are so unhappy that they are actively convincing their friends and daughters NOT to join.

This is exactly what's been happening in our field. The attrition of women from the technology industry, namely software engineering, over the past few decades is a significant contributor to the lack of women in the field today. And, while my research focuses mainly on women, I believe many of the same things are true for people of color. Let me explain why women are leaving, how that impacts the next generation's pipeline, and how we can go about fixing it.

Women are Leaving Tech



Women are leaving tech earlier and at significantly higher rates than men. As Rachel Thomas says in her blog post from 2015, “If you think women in tech is just a pipeline problem, you haven’t been paying attention” [2]. Attrition is one of the main reasons why we have such a gender discrepancy in our field, and I'm already starting to see this in my generation.

Currently, my female peers are opting out of the engineering workforce at alarming rates. They're pursuing career paths other than software engineering or engineering leadership because they see no future at their current jobs. By the time women reach the mid-level point in their technology career, 56% of them will have left - twice the rate that men are leaving. What's even more depressing is where those women are going. These women aren’t just leaving your company, they’re leaving the industry. Most of them are leaving for jobs in other industries and taking a pay cut to do so [3]. Despite the myth that women leave the workplace to have children, only 1 in 4 women who leave cite "spending time with their family" [4]. Instead, over half the women who leave cite bad work environments, a lack of flexibility, and no advancement opportunities as their reason for leaving.

There's even been a rise of female entrepreneurs starting companies because they are fed up with the existing tech work cultures. Imagine that, women find starting a company to be less emotionally taxing than simply working as an engineer at existing companies.

And if women are leaving tech, then they can't do what Ben Horowitz hopes they will: educate and bring 4 other women into the field during the course of their careers.

The Pipeline Won't Solve Our Problems



Attrition has an effect on the next generation's pipeline. Much of the focus on diversity has been about getting women and people of color into the industry, but that focus misses many of the major problems that exist today. Blaming the pipeline and waiting 30 years for the next generation to solve gender diversity is irresponsible at best and a malicious avoidance of responsibility at worst. It ignores the fact that women are connected across generations, and that one of the main reasons we don't have a pipeline today is because we didn't retain women in the last generation. And one of the most significant things that companies and managers can do to improve diversity in our industry is to retain the women and people of color they work with today.

Cross Generational Retention



In college, I did original research on how and why women got started in computer programming for my honors thesis called Women in Computer Science. One of my key findings is that most women in computer programming are "First Generation Women." These are women convinced to go into the field by a man; a father, brother, friend, or significant other who is male. However, there were shockingly few "Second Generation Women;" women who were convinced to go into the field by a mother, sister, friend, or significant other who is female. Given that the percentage of women in Computer Science in the 80s was 35%, more than double what it is today, why are there so few women convinced to go into the field by a woman [5]?

Let's take a look at how this can happen. While we might have had a higher percentage of women in the field in the 80s, if the work environments were toxic and they all left unhappy, then they wouldn't tell their friends, daughters, and nieces to go into the field. A friend of mine is one of the few second-generation women that I know, and her mom was a programmer during the 80s. However, fed up with the industry, she left at 29 to teach calculus at a local college. Flash forward to my friend, who went into the field despite her mother's warnings, and now at 30, she is considering opting out of the field as well.

Women significantly impact other women



There is a growing body of evidence that the race and gender of instructors and mentors significantly impact the performance and retention of their students [6]. I.e. a black professor has a significant and positive impact on the performance of her black students. Which means that the happiness of a previous generation in a field can significantly impact the next generation - in either direction.

I found this to be true in a survey I recently conducted asking people in my network: "How did you get into computer programming?". Over 500 people responded, and what I found was there were relatively few differences in the reasons why women and men entered the field. People come in through school, gaming, encouragement from teachers, and a general interest in technology. However, one of the few statistically significant differences is that women are much more likely to be influenced to go into the field by a woman than men are [7].

In other words, if women have a more powerful impact on other women, then the retention of women today will impact the pipeline of women tomorrow.


How do we get more second-generation women?



It's simple: we retain the women we already have.

Now, you might think there's some sort of magic trick to retaining women in our industry. Interestingly enough, the reasons that women leave are roughly the same as men. Getting more second generation women is not as difficult as you would think. It's the same formula that companies currently use to try to retain their male developers. There are three major things that ALL people want in their job: good management, upward mobility, and benefits and job flexibility.

Management



Bad managers are the #1 reason people leave a company [8]. Poor management is an epidemic in the tech industry (more on that some other time). The first, most basic thing companies can do to improve management is to train their people managers. Management, like programming, is a skill that requires practice. If you don’t know where to start with your training, Google did a research study on what makes an effective manager [9]. While Google itself is not a pinnacle of good people management in the technology industry, the research here is very thorough.*

*Here's the short summary of Google's findings [10].

Promotions



People want upward mobility. No one is going to stay at a company where they have no future, and currently, women are promoted at drastically lower rates than their male peers. My next post is entirely dedicated to this topic so I won’t go into a lot of depth here, but it is essential to have a clear, well-documented promotion process. Having no process for promotions is unacceptable (see my post on The Null Process) because a lack of documentation and process allows biases to run rampant. No matter how imperfect your system for promotions, having a process that is documented and accessible to every member of your team is critical to making promotions more egalitarian.

Benefits



Life is crazy and unexpected and full of so many things other than work. Friends, family, children, significant others. Every person at your company has something they are dealing with outside of work. Benefits that help employees stay healthy and give them the flexibility to deal with life are a huge component of employee happiness and retention.

Women, for example, can’t help being the gender that bears children. Companies should be able to support the perpetuation of the human race while still retaining valuable female employees [11]. Parental leave of 4 months should be an industry standard, and companies like Vodafone are even adding on transition plans for new mothers after they return from maternity leave [12]. Similarly, many people will have an aging parent at some point, so having a different kind of parental leave will be necessary so people can take care of their families in times of need [13].

Conclusion



Ben Horowitz wasn’t wrong that the future of humankind is dependent on Technovation girls. The thing he missed is that it’s not just about educating the next generation; the single most important thing you can do for diversity is to retain the current generation. You can retain any employee by valuing them equal to their work, training managers at your company, and giving employees the benefits and work flexibility to manage life outside the office. I wish we valued retaining underrepresented groups as much as we valued hiring them. The future of the technology industry depends on us retaining the women and people of color we already have.

Resources



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rosskarchner
22 days ago
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The Simpsons’ Steamed Hams as a Guitar Hero song

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related: Publio Delgado’s Harmonizator and /r/zappafied

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rosskarchner
23 days ago
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The New York Times is Now Available as a Tor Onion Service

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Illustration by Kevin Zweerink for The New York Times

Today we are announcing an experiment in secure communication, and launching an alternative way for people to access our site: we are making the nytimes.com website available as a Tor Onion Service.

The New York Times reports on stories all over the world, and our reporting is read by people around the world. Some readers choose to use Tor to access our journalism because they’re technically blocked from accessing our website; or because they worry about local network monitoring; or because they care about online privacy; or simply because that is the method that they prefer.

The Times is dedicated to delivering quality, independent journalism, and our engineering team is committed to making sure that readers can access our journalism securely. This is why we are exploring ways to improve the experience of readers who use Tor to access our website.

One way we can help is to set up nytimes.com as an Onion Service — making our website accessible via a special, secure and hard-to-block VPN-like “tunnel” through the Tor network. The address for our Onion Service is:

https://www.nytimes3xbfgragh.onion/

This onion address is accessible only through the Tor network, using special software such as the Tor Browser. Such tools assure our readers that our website can be reached without monitors or blocks, and they provide additional guarantees that readers are connected securely to our website.

Technology

Onion Services exist for other organizations — most notably Facebook and ProPublica, each of which have created custom tooling to support their implementations. Our Onion Service is built using the open-source Enterprise Onion Toolkit (EOTK), which automates much of the configuration and management effort.

The New York Times’ Onion Service is both experimental and under development. This means that certain features, such as logins and comments, are disabled until the next phase of our implementation. We will be fine-tuning site performance, so there may be occasional outages while we make improvements to the service. Our goal is to match the features currently available on the main New York Times website.

Over time, we plan to share the lessons that we have learned — and will learn — about scaling and running an Onion Service. We welcome constructive feedback and bug reports via email to onion@nytimes.com.

Finally, we would like to extend our thanks to Alec Muffett for his assistance in configuring the Enterprise Onion Toolkit for our site.

Runa Sandvik is the Director of Information Security at The New York Times


The New York Times is Now Available as a Tor Onion Service was originally published in Times Open on Medium, where people are continuing the conversation by highlighting and responding to this story.

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rosskarchner
27 days ago
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EOTK looks interesting
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Put the Ad Network Surveillance State to work for you!

jwz
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It Takes Just $1,000 to Track Someone's Location With Mobile Ads

"Regular people, not just impersonal, commercially motivated merchants or advertising networks, can exploit the online advertising ecosystem to extract private information about other people, such as people that they know or that live nearby," reads the study, titled "Using Ad Targeting for Surveillance on a Budget."

The University of Washington researchers didn't exploit a bug or loophole in mobile advertising networks so much as reimagine the motivation and resources of an ad buyer to show how those networks' intentional tracking features allow relatively cheap, highly targeted spying. [...]

"If you want to make the point that advertising networks should be more concerned with privacy, the bogeyman you usually pull out is that big corporations know so much about you. But people don't really care about that," says University of Washington researcher Paul Vines. "But the potential person using this information isn't some large corporation motivated by profits and constrained by potential lawsuits. It can be a person with relatively small amounts of money and very different motives."

Previously, previously, previously, previously, previously, previously, previously, previously, previously, previously, previously, previously, previously, previously, previously, previously.

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rosskarchner
33 days ago
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acdha
33 days ago
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A Fair Accusation of Sexual Harassment or a Witch Hunt?

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“In an interview with the BBC published early Sunday, director Woody Allen addressed the wave of allegations against Harvey Weinstein, calling it ‘tragic for the poor women’ but also warned against a ‘witch hunt atmosphere.’” — New York Times, 10/15/17

- - -

1. George is a middle-aged man who works in an office with a younger female colleague, Annie. The female colleague wears a short skit one summer day to the office. George comments, “Nice gams, Annie” and gives her a wink. Annie files a complaint with HR. Is this:

A. A witch hunt
B. A fair accusation of sexual harassment

2. In the year 1693 in Salem Village, Sarah Good is a woman living in poverty and disliked by the townspeople. A jury of men decide that she was a witch after forcing her to confess that she signed her name in the “Devil’s book,” a thing that does not exist. She is hanged several days after giving birth to a daughter. Is this:

A. A witch hunt
B. A fair accusation of sexual harassment

3. Lucas is a photographer in New York. He often comes in contact with models and sometimes when directing — whoops! — he gives them a quick pat on the bum. Several models have reported him, but nothing has been done. Is this:

A. A witch hunt
B. A fair accusation of sexual harassment

4. Sarah Osborne doesn’t go to church like the townspeople of Salem expect her to. Because of this, a group of men decide she is a witch and is accused of using dark magic to pinch several young girls in town with invisible knitting needles. They arrest her, put her in prison, where she dies. Is this:

A. A witch hunt
B. A fair accusation of sexual harassment

5. Anderson manages a restaurant. He hires a new server, named Ella. While rubbing her shoulders he tells her that if she wants more tips she should wear a lower cut shirt. Ella does not feel comfortable around Anderson, but needs a job to pay her rent, so she only mentions this to her friend who says he’s done it to her, too. Is this:

A. A witch hunt
B. A fair accusation of sexual harassment

6. Tituba is a woman from Barbados, but is now enslaved by white people in the town of Salem. She continues to practice her religion, which the people of Salem don’t understand. They assume it means she is a witch and beat her until she confesses and rambles about black dogs and riding on sticks, then imprison her, despite no evidence that witches actually exist. Is this:

A. A witch hunt
B. A fair accusation of sexual harassment

- - -

Sexual harassment: 1, 3, 5
Witch hunt: 2, 4, 6

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rosskarchner
34 days ago
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