new web technologies
- How To Protect Yourself In The Cloud
- For Once, The Entire Internet Isn't Blaming The Victims Of This Nude Celebrity Photo Leak
- Google Copies ReadWrite, Dumping "Enterprise" For "Work"
- How Big Data Reveals The Secret Life Of Cities
- Why So Few Women Are Studying Computer Science
How To Protect Yourself In The Cloud
The massive iCloud hack that exposed photos of female actresses stored in their personal Apple accounts, has left many—including myself—scrambling to change their passwords.
Some speculated that the hack was due to a vulnerability in Apple’s Find My iPhone feature, with which hackers used a “brute force” attack to guess the passwords on celebrities’ accounts, The Next Web reported.
Apple has since denied those reports, instead claiming it was a “very targeted attack” on usernames, passwords, and security questions—the keys to nearly any online account.
If celebrities can be attacked, so can you. So what can you do?
Understand The Cloud
Strong passwords are just one way Internet users can protect themselves from having their data stolen by malicious attackers. And photos aren’t the only things we have to worry about. Everyone tut-tutting actresses for taking risqué photos should think twice about where their personal data is stored. Oh, that’s right—it's in the cloud, too.
The thing about “the cloud,” is that no one really understands it. It's a deliberately vague term for computer servers you access over the Internet.
Remember the scene from Zoolander when Owen Wilson's character suddenly has an epiphany that “the files are in the computer”—and then tears open the machine looking for them? When it comes to the cloud, our understanding hasn't improved much.
Even CNN doesn’t know how to explain the cloud to viewers. It ran a story with the lower third “Leaked Nude Pics May Be From The Cloud.”
Cloud servers are like any computer: You can put files on them, and access them later. Since they're on the cloud, you don't have to have access to a physical device, or worry about how much space your laptop's hard drive has, since cloud servers typically have far more space than our own personal machines do.
The tradeoff for this convenience is security. If you can access your files using a username and password, so can anyone else who gets ahold of your credentials. And you have to rely on those companies to implement smart versions of the latest security protocols.
Cloud storage service likes Dropbox, Box and Google Drive make it simple to save and share files. iCloud, Apple’s cloud storage, automatically backs up your information like photos and documents, in case your phone or laptop needs to be replaced.
We have a fundamental expectation of privacy and security when using these services, especially when a company is automatically backing up the information to its servers. But that expectation can fail us.
Find The Right Cloud Storage
It’s hard to completely secure your cloud storage without jumping through a lot of hoops, which we'll get to shortly. But the first step is figuring out where you want your documents to be stored.
Don’t sign up for new cloud services without researching it. That includes reading the privacy policies of any company you agree to give your data to. Do they have encryption built in? Do they give your data to governments when requested? Do they control their own servers, or do they rent out servers from other companies? (Dropbox and Apple, for example, both use Amazon's servers for a portion of their online services.)
If security is your top priority, you might consider services like SpiderOak, which automatically encrypts all your data and prevents even the company from knowing what you’re uploading. But that means giving up the ease of sharing files with friends through Dropbox or collaborating with colleagues using Google Drive.
For most of us, convenience usually wins out. You should at least know that you're making that tradeoff, however.
Use Secure Passwords
According to Apple, the hackers targeted usernames, passwords and security questions, which are the first lines of defense for users.
Simply changing an “S” to a “$” does not make your password secure—especially if you recycle that password from site to site. Hackers attack less secure services and harvest usernames and passwords—and then try them on other services.
Adding unique characters along with letters and numbers is smart, but so is using passwords that are hard, if not impossible, to guess. The best passwords are a collection of random letters, numbers and punctuation, without any words you'd find in the dictionary. And each online account should have a different, complex password.
Does that sound impossible to keep track of? It pretty much is, unless you get some computerized assistance. Password managers like 1Password and LastPass provide a way to save and manage passwords, and you can carry and access your data on multiple devices.
Enable Two-Step Verification
If someone is trying to illegally access your personal information from the cloud by using your password, you might not realize it—unless you have two-step verification enabled.
With two-step verification, it’s necessary for you to input two different pieces of data in order to access your personal information. Typically, that's your password and a different code sent as a text or generated by an app on your mobile device. The code will change each time you log in.
Two-step verification can be frustrating and time-consuming, which is why many consumers elect to ignore it. But it saves you from having to clean up the potential mess a hacker could make with your credit card information or naked pictures stolen from the cloud.
Encrypt Your Files
If you’re not using a service that automatically encrypts your files, like SpiderOak or Mega, you may want to encrypt them yourself.
Google, Dropbox and Microsoft don’t offer file encryption as a built-in feature. While they may encrypt your transmissions between data centers, once you're logged in, the files are available in unencrypted form. Most consumers don’t request it, because it can be difficult to use, and encryption can be complicated for companies to enable, according to Wired.
Imagine Google Drive with no search capabilities, or Dropbox with no preview. None of those features would work with encrypted files, because they’d be unreadable by Google and Dropbox’s server software. And if Google doesn’t have the encryption keys it can’t help you out if you lose a password.
Boxcrytor and Viivo both offer DIY cloud encryption, which means you can encrypt all your files before uploading them to the cloud. These companies won’t have access to your secret keys to decrypt files, which means your data is safe from prying eyes that don’t have access to your unique key.
Ultimately, we'll need better forms of protection. Apple's TouchID fingerprint sensor is an interesting example of authentication using biometrics, or physical aspects of our bodies. PayPal's Braintree aims to detect fraud by looking at information about how we're using our mobile phones at the time we make a transaction. Companies are using sophisticated behavioral modeling to detect hackers on their networks: Perhaps one day, we'll be protected by similar technology that can tell through the way we tap on our phone's keyboards or the time of day we access our devices that we are who we say we are.
Until then, we're left changing our passwords, enabling two-factor verification, and hoping for the best.
Lead image by StockMonkeys
Date: Tue, 02 Sep 2014 03:31:17 -0700
Author: :: Category: Web
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For Once, The Entire Internet Isn't Blaming The Victims Of This Nude Celebrity Photo Leak
The latest batch of nude celebrity photos leaked on the Internet once again reminds us that the Internet is anything but friendly to women. Despite an avalanche of slut-shaming, victim-blaming headlines and social chatter, though, there are scattered signs that some people are starting to assign blame where it belongs—on the perpetrator(s) of these felony crimes and the bystanders who enable it.
Oh, and comedian Ricky Gervais.
“Celebrities, make it harder for hackers to get nude pics of you from your computer by not putting nude pics of yourself on your computer,” Gervais tweeted on Monday. His post followed news that actress Jennifer Lawrence, model Kate Upton and others has revealing photos stolen from their Apple iCloud accounts in one of the largest known celebrity-related security breaches.
Blowback from the Twitterverse was swift and furious. Gervais, known for his unapologetic, take-no-prisoner tweets, deleted the offending post. Also, he apologized.
Gervais, who is funnier than most and famous because of it, nonetheless tried to pass off the cliched criticism as comedy. “Of course the hackers are 100 percent to blame but you can still makes jokes about it. Jokes don't portray your true serious feelings on a subject,” read a subsequent tweet.
A Crime Is A Crime Is A Crime
It’s not a joke when everybody’s mom and dad are tweeting the same crusty comment that’s been repeated by civilians and security experts ever since somebody stole Tommy Lee and Pamela Anderson’s honeymoon sex tape, reportedly from their household safe.
Let's just cut to the chase. If you walk down an unlit street at midnight counting $100 bills and you get mugged, you are stupid. But the mugger is still a criminal. We all need to take precautions to protect ourselves from theft.
But it doesn't follow that we should then blame victims for being targeted by criminals. We should be able to live in a world free of muggers and 4chan photo thieves.
As history shows, we put too much emphasis on victim-blaming and not enough on troll-blaming.
Putting the criticism on the violated parties will likely remain the default response to what the celebrity magazines call “scandals.” But along with the Gervais’s Twitter apology, there a few bright points on the Internet indicating that some day, that won’t always be the case.
We Are Bigger Than The Scandal Sheets
In a post titled “Jennifer Lawrence Nude Photo Leak Isn’t A “Scandal.” It’s A Sex Crime,” Forbes contributor Scott Mendelson writes:
The actresses and musicians involved did nothing immoral or legally wrong by choosing to take nude pictures of themselves and put them on their personal cell phones. You may argue, without any intended malice, that it may be unwise in this day-and-age to put nude pictures of yourself on a cell phone which can be hacked and/or stolen. But without discounting that statement, the issue is that these women have the absolute right and privilege to put whatever they want on their cell phones with the expectation that said contents will remain private or exclusive to whomever is permitted to see them just like their male peers. The burden of moral guilt is on the people who stole said property and on those who chose to consume said stolen property for titillation and/or gratification.
It’s likely not lost on self-identifying female feminists that Mendleson is a dude, or that he’s echoed by other males on Twitter who criticize the primary focus on the women whose privacy was violated. That’s not to say these guys deserve special commendations any more than men who help out with the housework.
Still, for dinosaurs like yours truly who’ve observed appalling Internet behavior against women since the notorious early 1990s “cyberspace rape” in the online multi-player gathering LambdaMOO, it does offer the smallest suggestion of social change.
Whether this means anything in practical terms beyond possibly alleviating the abuse its victims get—from the famous to victims of revenge porn—remains to be seen. (After all, the Internet is so enlightened on every other controversial subject, from race to politics to gender relations.)
But maybe there's a draining-the-swamp argument that goes: By reducing the social acceptability of slut-shaming victims and trading their pictures with your bros, it'll limit the acclaim (and money) that hackers are after.
Something to hope for, anyway.
Lead image by Peter
Date: Tue, 02 Sep 2014 01:38:05 -0700
Author: :: Category: Web
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Google Copies ReadWrite, Dumping "Enterprise" For "Work"
Google is dumping the tired "enterprise" label for its business products, renaming them Google for Work.
Gosh, where have we heard that one before? Oh, right—here on ReadWrite, where, two months ago, we switched our coverage of business tools from the section formerly known as Enterprise to a new section known as ... yes, Work.
We can only applaud Google's change. Google has always championed bringing consumer-friendly software like Gmail and Google Docs into the work world.
The Google Enterprise name is a leftover from an earlier era—a brief period in Google's infancy when the company thought it would make money by licensing search technology to other businesses, as John Battelle documented in The Search, his history of the company.
Let's just say it: "Enterprise" is a terrible world, used for terrible reasons. At best, it's a catch-call term that's an awkward shorthand for "businesses and other large organizations" (like schools, government agencies, and nonprofits). It describes a way many companies organize their salespeople: one group selling to large customers, others selling to small ones. Or it describes products only of interest to large organizations.
None of that makes sense in a world where size doesn't matter. The employees of large companies want tools as simple and intuitive as the apps on their phones. And small businesses and individuals want the security, stability, and features found in software originally designed for big businesses.
Hence our name change. And, following in our modest footsteps, Google's, too. The enterprise is dead. Long live work.
Date: Tue, 02 Sep 2014 12:52:47 -0700
Author: :: Category: Work
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How Big Data Reveals The Secret Life Of Cities
Data At Work profiles data scientists working at the cutting edge of Big Data.
Suppose data scientists could track how people move through cities and towns as easily as e-commerce sites track them online?
Don't answer that. It's already happening—thanks, at least in part, to a startup called StreetLight Data.
StreetLight founder and CEO Laura Schewel was working on a doctorate in energy engineering at UC Berkeley when she had the “ah-ha” idea of using data from cell towers, traffic-data aggregators and GPS satellites to track people's movement patterns in cities and states across the country.
Initially, Schewel figured the information might help traffic engineers plan new highways and parking. But the data her system aggregates turns out to be useful for much, much more.
How To Track Without Tracking
Like it or not, it's ridiculously easy to see how people behave online. Cookies and more sophisticated techniques let advertisers track individuals across websites, in part because the online environment is controlled (in just about every sense of the term).
This type of tracking, and the related task of gathering insights into peoples' behavior, is much more complicated in real life.
The basic problem is one of putting together all the pieces of a massive puzzle that don't exactly fit. How do you get and make sense of the data generated by ordinary people in order to say with any degree of certainty—in generalized and anonymous but still analytically useful ways—where they shop, which highways they take or even whether they're more likely to take the train on Fridays when the Giants are playing and traffic is lousy in San Francisco?
See also: Why Data Scientists Get Paid So Much
For StreetLight, it all starts with the cellphone. It probably won't surprise you to know that major carriers collect detailed location data as your phone registers with different cellular broadcast towers (thus providing a detailed record of your movements).
But you might not have known that carriers sell access to that data in a format that basically provides a movement record for large chunks of the population. It's all anonymized: The data consists of map plot coordinates and the ID numbers that identify particular phones, with the latter run through a one-way hashing function designed to yield unique numbers that can't be matched to the original IDs.
StreetLight's proprietary pattern-recognition algorithms can infer the "favorite" places of the people covered in the carrier geodata, such as their home and work neighborhoods. Then StreetLight cross references this info with census and other demographic information such as household income, educational status and race. [Corrected: see below]
What it ends up with are richly detailed databases that can be used, say, to generate the average profile of someone who might be shopping at Whole Foods at 5pm, dropping a child off at school on a Monday morning, or commuting from San Francisco to the East Bay to work.
Put that way StreetLight sounds sounds sort of creepy—and maybe it is. Schewel and her team, of course, stress that safeguards such as those one-way hashes make it impossible to tie aggregated data about groups back to individual users. “There is no way for us to actually map anything back to individuals. All that data is stripped out long before we get it,” Schewel told me.
At the same time, de-anonymizing such information tends to become easier over time, in part because individuals are generating increasing quantities of data about themselves that can serve as a cross-reference to pinpoint actual identities.
Whether or not such privacy concerns have merit, this type of data can provide valuable information in a variety of situations. Think companies deciding whether and where to expand; city and transit planners projecting the need for new zoning, transit or roadways; and perhaps developing nations planning new infrastructure and even entire cities.
Turning Data Into Information
The process by which StreetLight maps together these very different types of data into a coherent dataset turns out to be fairly straightforward. Every month, Schewel’s team receives a messy glob of about 400GB worth of geospatial data from mobile carriers and other data providers.
That doesn't sound like much—even given that the load is expected to reach 800GB a month next year—considering that StreetLight's movement patterns cover much of the continental U.S. (The company occasionally also scrapes up Canadian data by accident, and has to discard it.) But geospatial data is fairly lean and has a small footprint, Schewel says. The data is added to StreetLight's existing multi-terabyte data store.
StreetLight then pushes the data through a custom extract, transform and load process run through Talend, a popular Big Data integration tool. This trims out unnecessary information and reformats different types of data into a uniform schema.
Along the way, this process matches up different types of data—cellular-tower location, traffic reports, census patterns, other data sources—at different geographic scales ranging from census block to town or city to region, and along expressways or other transit corridors. All that data gets referenced to particular geospatial locations and, in many cases, to specific time periods as well ("all the time," "weekdays," "rush hour," etc.).
What StreetLight Knows About Us
All that work links together disparate types of data in a meaningful way, making it possible to get a good sense of where people who fit a particular demographic profile spend their time—and when.
Say, for instance, you wanted to know more about people who shop at the Stanford Mall. The StreetLight database might tell you that people over 50 with graduate degrees who live in high-end neighborhoods shop there all the time; families with children from middle-class and high-end neighborhoods shop there on weekends (especially in August and December); and people without college degrees only visit the mall on Monday evenings in the spring.
Now that's data transparency.
StreetLight can, for instance, help out a retail chain that's thinking about opening a new store with better information about its prospective customers. For instance, whether the average shopper in a proposed mall location earns closer to $50,000 or $100,000, has one child or three, or is a 50-year-old females or a 21-year-old male. As you can imagine, such data is incredibly valuable, and not just to companies.
As Schewel explained it to me:
We can actually show what might happen if, say, a new freeway off-ramp would be built or a road is changed or even if a big snowstorm hits. We can do this by finding days in the past when an event creating similar conditions occurred. It’s much better than running simulations because it's real behavior.
For a decent degree of confidence, StreetLight needs a sample size equal to at least 1% of the population of any location. Schewel prefers 5% to 6% for better signal fidelity, though.
X-Raying The Average Shopper
Already, StreetLight is proving its worth in some unexpected ways. In 2013, the Oakland Business Development Corporation (OBDC) wanted to increase economic activity in downtown neighborhoods where hundreds of commercial properties lay vacant. Oakland locals, too, were spending up to three-quarters of their retail dollars elsewhere, in part for lack of options.
Foodies in the East Bay knew the downtown Oakland dining scene was on fire; OBDC, a nonprofit urban-development agency and business lending organization, tried to capitalize on the boom by courting retailers and developers. But it struck out when its prospects looked at demographic data on nearby neighborhoods, many of which are low-income areas, and backed away.
OBDC turned to StreetLight for a clearer picture of downtown Oakland's commercial prospects. Its data revealed that the area regularly draws a healthy mix of wealthy, middle-class and lower income people.
OBDC used those findings to convince skeptical store owners to consider locating downtown. But the organization, which also makes loans to retailers, put the data to broader use—primarily to confirm that the area's shopping demographics could support a variety of store types.
"That data helped us fill dozens of vacant storefronts over the next year," says Jacob Singer, OBDC's president and CEO.
Singer is now considering purchasing StreetLight data as part of retail and urban planning efforts around an upcoming bus-based rapid-transit project slated for downtown Oakland in the next few years. "There really are no comparable alternatives that provide data this detailed and accurate for urban planning and project assessment," he says.
Reading The StreetLight X-Ray
VeggieGrill, a rapidly growing vegetarian fast-food chain, signed up with StreetLight to learn where people who most closely matched the vegetarian demographic tended to shop and spend their time.
Other retailers are using StreetLight data in reverse. Men's Wearhouse, for instance, uses StreetLight not just to spot new store locations, but to identify underperforming stores based on traffic patterns and shopper demographics.
StreetLight's data often reveals unexpected patterns—or their absence. Sometimes it shows big differences in the types of shoppers that frequent two adjacent shopping centers, or surprising discrepancies between stores and their neighborhoods.
“We can also tell a store chain that the wealthy people who live around a location rarely go to that store,” says Schewel. "For some customers, we have seen surprising dead zones where you would think a ton of people would shop but in fact few venture in."
Schewel has big plans beyond helping merchants optimize their store locations. Like, for instance, improving public planning in developing countries with detailed data.
“Many of these countries don’t have a census and don’t really know how people are moving around, so our information would be the first real data," she says. And since countries that never had widespread land lines often have denser cellphone networks than the U.S., Schewel thinks StreetLight could provide even more detailed user data.
Ultimately, StreetLight’s data could also help answer more difficult questions about whole-day transport patterns. These patterns reflect complex human decisions that result in behaviors and traffic patterns that are hard to analyze in isolation.
As Schewel told me:
We can capture the entire traveling day of citizens. Rather than just seeing what happens when someone is going from home to work, we can see that people have not taken public transit because they have to pick up their child from school or that they are more likely to go to a supermarket to buy groceries on Friday night. This type of detail lets everyone that needs to know how people move see cause-and-effect far better than before.
Correction, 11:19pm PT: An earlier version of this article incorrectly described the information StreetLight purchases from carriers. It acquires only geolocation data from carriers, not anonymized demographic and user information.
Date: Tue, 02 Sep 2014 11:05:11 -0700
Author: :: Category: Work
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Why So Few Women Are Studying Computer Science
University students around the country are packing up their cars and making the annual pilgrimage to dorm rooms or sparsely-decorated apartments to kick off the school year. They’re pounding the concrete in Ikea for last-minute bathroom accessories, and hugging their parents goodbye until fall break.
The university experience prepares young adults for future careers. It teaches them required skills, and introduces them to peers who may one day become coworkers.
For one field in particular, the classes, and for now, the future, look similar to the fraternity houses that line a college town's streets. Computer science is a boys club.
Women earn just 18% of undergraduate degrees awarded for computer science. At top research universities, that number is 14%, according to the Anita Borg Institute.
What is most startling about that number is that it does not represent progress. In 1985, women earned 37% of computer-science undergraduate degrees.
Three decades later, computer science has become a much more vital gateway to high-paying jobs and the chance to influence the software-driven future of society. Yet vastly more men than women are stepping through it.
Why Is There A Gender Gap?
Computer science is the only field in science, engineering and mathematics in which the number of women receiving bachelors degrees has decreased since 2002—even after it showed a modest increase in recent years.
“The number of female degree earners in the last three years is starting to inch up, but it’s rising faster for men,” Linda Sax, an education professor at UCLA who is researching why women are underrepresented in computer science. “The numbers of students who go into computer science has fluctuated relative to perceived career opportunities, but that the gender gap tends to widen during periods of expansion.”
That's because when computer science is viewed as a lucrative career—as it is now—more people, both men and women, choose to pursue it. In those years, though, the ratio of men to women increases.
One reason for this is because women have historically chosen lower-paying yet fulfilling jobs like teaching or journalism, whereas their male counterparts, sometimes considered family providers, choose high-paying careers like computer science and engineering.
The advent of the home personal computer may have contributed to the historic gender gap. In the 1980s, when the PC became a standard home appliance, it was mostly men who used it. According to the National Science Foundation, a 1985 study found that men “were substantially more likely to use a computer and to use it for more hours than women; 55% of adult women reported not using the computer at all in a typical week, compared to 27% of men.”
It was a man’s machine—despite Apple’s attempts to brand one as a “homemaker appliance,” for women who run both the business and the household.
Other contributing factors, according to academic experts I interviewed, include a culture that encourages young women to play with dolls rather than robots and pursue traditionally female careers, as well as the self-perpetuating stereotype that a programmer is a white male. Sometimes women can feel like they don’t belong in a technical world dominated by men.
Those stereotypes are based on reality, according to data released by some of the largest tech companies. Among the top employers in Silicon Valley, including Facebook, Google, Twitter and Apple, 70% of the workforce is male. In technical roles, the disparity is even greater. At Twitter, for instance, only 10% of the technical workforce is female.
Telle Whitney, president and CEO of the Anita Borg Institute, is working to change those numbers. The organization, founded in 1987 by computer scientist Anita Borg, aims to equalize the ratio of men and women in technology fields.
Whitney herself knows firsthand how challenging it can be as a woman pursuing a degree in computer science.
“I did my PhD at Caltech, and at the time when I was there, it was about 14% women,” Whitney told me in an interview. “I didn’t know quite what was going on, but the feeling of isolation, like ‘I don’t necessarily belong,’ was pretty prevalent.”
Some Schools Get Good Grades
The gender disparity in tech starts young. 30,000 students took the Advanced Placement Computer science exam in high school last year. Less than 6,000 of them were women.
But AP exams don’t necessarily predict the success of students in college, or what their particular interests are. So to drive more participation in computer science classes, many colleges and universities are working to make computer science appealing to women.
At Harvey Mudd College, a private liberal arts college near Los Angeles, initiatives are underway to make the computer-science department more welcoming. As a result, 40% of its computer-science students are women. Harvey Mudd is still working to ensure women feel as welcome and as capable as their male computer science peers.
“These strategies aren’t like, ‘Oh we turned everything pink,’” Colleen Lewis, assistant professor of computer science at Harvey Mudd, said in an interview. “These are best practices for getting students with a broad range of interests interested in computer science.”
Harvey Mudd split the introduction to computer science course into three different tracks, instead of having all students of different levels complete the same course. Essentially, the course is now broken down into beginning, intermediate, and advanced levels, so each student can study and learn from peers with similar experiences, and not be overwhelmed by students who have been coding since they were in elementary school. By addressing each level individually, it prevents students with no programming experience from being deterred from the field by competing with experts.
The college also brings a number of first-year students to the Grace Hopper Celebration, a conference hosted by the Anita Borg Institute that is the largest gathering of female technologists in the world. The conference gives students the opportunity to meet other women with careers in tech, and provides role models to new students who are still discovering computer science themselves.
This year, Lewis and five other faculty members are bringing 52 students to the event.
Harvey Mudd is not alone in its efforts. In June, Carnegie Mellon University announced that for the first time ever, 40% of incoming computer-science majors are female. The university attributes the achievement to increasing female-focused networking events, mentoring opportunities, and on-campus community building.
At the University of California at Berkeley, women outnumbered men this year for the first time in the university’s introductory computer-science course. The newly redesigned course wasn’t geared specifically towards women, professor Dan Garcia told SFGate, but the lecture introduced more right-brained exercises, including talking about popular technology news at the beginning of every class.
Notably, Berkeley changed the name of the course from "Introduction to Symbolic Programming" to "The Beauty and the Joy of Computing"—a more accessible-sounding moniker for the class.
However, while some computer-science classes are brimming with women, other technical courses still fall short.
Berkeley robotics professor Ruzena Bajcsy has been a teacher for 40 years. In the last few years, she says, she’s noticed a significant increase in the number of women in her classes.
“I’ve seen more women in my classrooms,” Bajcsy said in an interview. “Maybe 10% women, up from two or three percent.”
A Culture Shift
Feeling isolated or ostracized is a common frustration among women in technology. Especially when investors, CEOs and other technology leaders are implicitly biased against women.
Tech accelerator Y Combinator founder Paul Graham once famously acknowledged his own bias and told the New York Times, “I can be tricked by anyone who looks like Mark Zuckerberg.”
Graham was also widely criticized when he said in an interview, “God knows what you would do to get 13-year-old girls interested in computers. I would have to stop and think about that.”
Female engineers and computer scientists frequently find themselves alone in a room of men. They also have to deal with sexism and harassment from both peers and people who male counterparts consider to be role models. (GeekFeminism keeps a running timeline of sexist incidences in tech communities.)
A more recent obstacle is the growth of the "brogrammer"—a shorthand term for a macho, just-out-of-the-dorm-room culture that's being imported from college campuses to startup offices.
“When I was an undergraduate at Berkeley [between 2001-2005], the brogrammer identity did not exist,” Lewis said. “There’s this growth of this new identity, which is explicitly masculine and problematic ... but it’s interesting that the brogrammer identity is the predominant one in pop culture right now.”
Universities can work to equalize the ratio of women in technology, but without a significant culture shift—ditching the idea that white male twentysomethings make the best coders—women will still be discriminated against in the workforce.
Pop culture could help scrub that identity and help women find role models in media. For instance, Silicon Valley, HBO's critically-acclaimed startup parody, is adding two new main female characters to the cast. Google, for its part, is working with the Geena Davis Institute to improve representation of girl hackers in Hollywood.
The pop-culture stereotype is unfortunately reflective of reality in some startups, which pay a lot of attention to their "culture"—in other words, workplace fun, drinking, and parties—but not to human resources. One woman who worked at GitHub, the social-coding community, described the work environment there as similar to the dystopian novel “Lord of the Flies.”
Whitney says that in order to not just encourage women to pursue tech, but to stay in it as a career, the culture needs to change.
“The Anita Borg Institute works a lot with organizations to create cultures where women thrive,” she said. “If we graduate all these people and the organizational culture that they go into is very macho, then they’re not going to want to stay.”
Lead image by Todd Kulesza; Silicon Valley image courtesy of HBO
Date: Tue, 02 Sep 2014 10:50:51 -0700
Author: :: Category: Web
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