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April 30, 2014
What A Toilet Hoax Can Tell Us About the Future of Surveillance I wasn&rsquo;t actually surprised to learn that public officials in Toronto had agreed to install &ldquo;smart toilets&rdquo; in the city&rsquo;s convention center so they could analyze public, um, data. As a privacy researcher, the idea fascinated me. Only problem: It wasn’t true. But a fake toilet company’s publicity stunt has me thinking, which is what Quantified Toilets intended. Smart toilets are just the kind of product you expect to encounter at the ACM Conference on Human Factors in Computing, or CHI, an annual event where researchers discuss the latest science of how people interact with technology. This is my favorite conference to attend. There are always new and cool projects that make me think. So when Quantified Toilets debuted at CHI this week, it was an immediate hit. The company claimed to have installed sensors in the Toronto Convention Center and other civic venues that would automatically analyze “deposits” in the toilets to detect a person’s gender, drug and alcohol levels, pregnancy status, sexually-transmitted-infection status, and… smell. There were signs in the bathrooms that read: “Behavior at these toilets is being recorded for analysis.” Read more. [Image: Reuters]

What A Toilet Hoax Can Tell Us About the Future of Surveillance

I wasn’t actually surprised to learn that public officials in Toronto had agreed to install “smart toilets” in the city’s convention center so they could analyze public, um, data. As a privacy researcher, the idea fascinated me.

Only problem: It wasn’t true.

But a fake toilet company’s publicity stunt has me thinking, which is what Quantified Toilets intended. Smart toilets are just the kind of product you expect to encounter at the ACM Conference on Human Factors in Computing, or CHI, an annual event where researchers discuss the latest science of how people interact with technology. This is my favorite conference to attend. There are always new and cool projects that make me think.

So when Quantified Toilets debuted at CHI this week, it was an immediate hit. The company claimed to have installed sensors in the Toronto Convention Center and other civic venues that would automatically analyze “deposits” in the toilets to detect a person’s gender, drug and alcohol levels, pregnancy status, sexually-transmitted-infection status, and… smell.

There were signs in the bathrooms that read: “Behavior at these toilets is being recorded for analysis.”

Read more. [Image: Reuters]

10:55am
(Notes: 67)
  
Filed under: Technology Surveillance Toilets Tech Quantified Toilets Privacy Big Data 
April 29, 2014
How to Fight Poachers With Drones and Big Data “Drones Fight Poachers&quot; has an undeniable sexiness to it as a news narrative. Who doesn’t want to read about flying killer robots battling machete-wielding criminals chasing innocent animals on the wild African plains? The instant appeal of a high-tech solution to a pervasive low-tech problem is also why Silicon Valley giant Google has given the World Wildlife Fund (WWF) $5 million for drones to stop poaching. But to actually stop poachers, WWF should focus less on drones and more on math—and some lessons learned in Iraq and Afghanistan. University of Maryland computer scientist Thomas Snitch is applying a mathematical forecasting model he developed for use by the military in Iraq and Afghanistan to Africa. Snitch is trying to overcome poaching networks’ advantages in money, opportunity, and manpower using his military model to put park rangers in the right places to intercept rhinoceros killers. Read more. [Image: Edward Echwalu/Reuters]

How to Fight Poachers With Drones and Big Data

“Drones Fight Poachers" has an undeniable sexiness to it as a news narrative. Who doesn’t want to read about flying killer robots battling machete-wielding criminals chasing innocent animals on the wild African plains? The instant appeal of a high-tech solution to a pervasive low-tech problem is also why Silicon Valley giant Google has given the World Wildlife Fund (WWF) $5 million for drones to stop poaching. But to actually stop poachers, WWF should focus less on drones and more on math—and some lessons learned in Iraq and Afghanistan.

University of Maryland computer scientist Thomas Snitch is applying a mathematical forecasting model he developed for use by the military in Iraq and Afghanistan to Africa. Snitch is trying to overcome poaching networks’ advantages in money, opportunity, and manpower using his military model to put park rangers in the right places to intercept rhinoceros killers.

Read more. [Image: Edward Echwalu/Reuters]

3:55pm
(Notes: 68)
  
Filed under: Poaching Drones World Wildlife Fund Africa Rhino poachers Conservation Big Data 
April 14, 2014
Behind the Machine&rsquo;s Back: How Social Media User Avoid Getting Turned Into Big Data Social media companies constantly collect data on their users because that&rsquo;s how they provide customized experiences and target their advertisements. All Twitter and Facebook users know this, and there is a broad array of feelings about how good or bad the persistent tracking of their social relationships is.  What we do know, though, is that—when they want to—they are aware of how to go behind the machine&rsquo;s back. They know how to communicate with just the humans without tipping their intentions to the algorithm.  In a new paper, University of North Carolina sociologist Zeynep Tufekci explores some of these strategies among Turkish protesters. She looks at these behaviors as analytical challenges for researchers who are trying to figure out what&rsquo;s going on. &ldquo;Social media users engage in practices that alter their visibility to machine algorithms, including subtweeting, discussing a person’s tweets via &lsquo;screen captures,' and hate-linking,&quot; Tufekci writes. &quot;All these practices can blind big data analyses to this mode of activity and engagement.&rdquo; The same practices, though, from the user perspective, can be understood as strategies for communicating without being computed. All they require to execute is thinking like an algorithm. Read more. [Image: Renee Magritte via Wikimedia Commons/The Atlantic]

Behind the Machine’s Back: How Social Media User Avoid Getting Turned Into Big Data

Social media companies constantly collect data on their users because that’s how they provide customized experiences and target their advertisements. All Twitter and Facebook users know this, and there is a broad array of feelings about how good or bad the persistent tracking of their social relationships is. 

What we do know, though, is that—when they want to—they are aware of how to go behind the machine’s back. They know how to communicate with just the humans without tipping their intentions to the algorithm. 

In a new paper, University of North Carolina sociologist Zeynep Tufekci explores some of these strategies among Turkish protesters. She looks at these behaviors as analytical challenges for researchers who are trying to figure out what’s going on. “Social media users engage in practices that alter their visibility to machine algorithms, including subtweeting, discussing a person’s tweets via ‘screen captures,' and hate-linking," Tufekci writes. "All these practices can blind big data analyses to this mode of activity and engagement.”

The same practices, though, from the user perspective, can be understood as strategies for communicating without being computed. All they require to execute is thinking like an algorithm.

Read more. [Image: Renee Magritte via Wikimedia Commons/The Atlantic]

1:25pm
(Notes: 142)
  
Filed under: Technology Social Media Tech Big Data 
April 7, 2014
Why The Conversation Should Be Required Viewing at the NSA Technology—iPhones, Google Glass, tablets, and the like—makes our day-to-day lives easier to quantify than ever. That&rsquo;s a good thing, in many ways; more information about how people live can help, say, improve healthcare. But fiction, from George Orwell’s 1984 to this weekend’s box-office hit Captain America: The Winter Soldier, has long warned us about the ways that data collection can also threaten privacy, freedom, and happiness. The most powerful cautionary tale for the Age of Big Data comes from an unlikely place: Francis Ford Coppola’s The Conversation, which turns 40 today. Read more.

Why The Conversation Should Be Required Viewing at the NSA

Technology—iPhones, Google Glass, tablets, and the like—makes our day-to-day lives easier to quantify than ever. That’s a good thing, in many ways; more information about how people live can help, say, improve healthcare.

But fiction, from George Orwell’s 1984 to this weekend’s box-office hit Captain America: The Winter Soldier, has long warned us about the ways that data collection can also threaten privacy, freedom, and happiness. The most powerful cautionary tale for the Age of Big Data comes from an unlikely place: Francis Ford Coppola’s The Conversation, which turns 40 today.

Read more.

12:25pm
(Notes: 282)
  
Filed under: Politics The Conversation Film NSA NSA spying Government surveillance Big Data 
March 11, 2014
Your High School Transcript Could Haunt You Forever Arizona State University, like many colleges across the United States, has a problem with students who enter their freshman year ill prepared in math. Though the school offers remedial classes, one-third of students earn less than a C, a key predictor that they will leave before getting a degree. To improve the dismal situation, ASU turned to adaptive-learning software by Knewton, a prominent edtech company. The result: Pass rates zipped up from 64% to 75% between 2009 and 2011, and dropout rates were cut in half. But imagine the underside to this seeming success story. What if the data collected by the software never disappeared and the fact that one had needed to take remedial classes became part of a student’s permanent record, accessible decades later? Consider if the technical system made predictions that tried to improve the school’s success rate not by pushing students to excel, but by pushing them out, in order to inflate the overall grade average of students who remained. These sorts of scenarios are extremely possible. Read more. [Image: Shannon Stapleton/Reuters]

Your High School Transcript Could Haunt You Forever

Arizona State University, like many colleges across the United States, has a problem with students who enter their freshman year ill prepared in math. Though the school offers remedial classes, one-third of students earn less than a C, a key predictor that they will leave before getting a degree. To improve the dismal situation, ASU turned to adaptive-learning software by Knewton, a prominent edtech company. The result: Pass rates zipped up from 64% to 75% between 2009 and 2011, and dropout rates were cut in half.

But imagine the underside to this seeming success story. What if the data collected by the software never disappeared and the fact that one had needed to take remedial classes became part of a student’s permanent record, accessible decades later? Consider if the technical system made predictions that tried to improve the school’s success rate not by pushing students to excel, but by pushing them out, in order to inflate the overall grade average of students who remained.

These sorts of scenarios are extremely possible.

Read more. [Image: Shannon Stapleton/Reuters]

1:25pm
(Notes: 302)
  
Filed under: Education School High School Big Data 
January 31, 2014
SFW: When Big Data Met Porn In his 1987 book The Secret Museum, Walter Kendrick explored the many ways that technology transforms pornography. Technological innovations—the advent of the printing press, the rise of the home video camera, the widespread adoption of the VCR—changed the way, he argued, that people related to sex as a media product. And the Internet, of course, has continued that evolution, expanding and democratizing pornography in ways that the Marquis de Sade, not to mention Hugh Hefner, could never have imagined.  In a recent paper, the team at Sexualitics, an interdisciplinary collaboration among sociologists, political scientists, and statisticians, attempted to quantify those transformations—through what they call &ldquo;a quantitative analysis of online pornography.&quot; The team looked at (&quot;looked at,&rdquo; to be clear, in the most scientific sense) videos uploaded to the porn site Xhamster between 2007 and February 2013. There were around 800,000 of them. They then extracted key words (I&rsquo;ll let you guess! Though, if you don&rsquo;t mind a literary strain of NSFW, you can also see a selection on page 11, here) from the titles of those productions. Read more.

SFW: When Big Data Met Porn

In his 1987 book The Secret Museum, Walter Kendrick explored the many ways that technology transforms pornography. Technological innovations—the advent of the printing press, the rise of the home video camera, the widespread adoption of the VCR—changed the way, he argued, that people related to sex as a media product. And the Internet, of course, has continued that evolution, expanding and democratizing pornography in ways that the Marquis de Sade, not to mention Hugh Hefner, could never have imagined. 

In a recent paper, the team at Sexualitics, an interdisciplinary collaboration among sociologists, political scientists, and statisticians, attempted to quantify those transformations—through what they call “a quantitative analysis of online pornography." The team looked at ("looked at,” to be clear, in the most scientific sense) videos uploaded to the porn site Xhamster between 2007 and February 2013. There were around 800,000 of them. They then extracted key words (I’ll let you guess! Though, if you don’t mind a literary strain of NSFW, you can also see a selection on page 11, here) from the titles of those productions.

Read more.

1:25pm
(Notes: 85)
  
Filed under: Technology Big Data SFW Data 
December 30, 2013
The Supreme Court Logic That Could Destroy Privacy in America Many Americans reacted with outrage when they learned that the NSA stores details about phone calls made by virtually everyone in the United States. They felt a strong, if vague, notion that the practice must violate their constitutional rights. Couldn&rsquo;t NSA analysis of telephone metadata reveal sensitive, private details about most anyone in the country, like their network of friends, the identity of their sexual partners, or their contact with medical or mental health professionals? Aren&rsquo;t mass searches of innocents anathema to the Fourth Amendment? The legal response from NSA defenders has leaned heavily on the precedent set in Smith v. Maryland, a Supreme Court case decided in 1979, before the era of big data. Read more. [Image: Reuters]

The Supreme Court Logic That Could Destroy Privacy in America

Many Americans reacted with outrage when they learned that the NSA stores details about phone calls made by virtually everyone in the United States. They felt a strong, if vague, notion that the practice must violate their constitutional rights. Couldn’t NSA analysis of telephone metadata reveal sensitive, private details about most anyone in the country, like their network of friends, the identity of their sexual partners, or their contact with medical or mental health professionals? Aren’t mass searches of innocents anathema to the Fourth Amendment?

The legal response from NSA defenders has leaned heavily on the precedent set in Smith v. Maryland, a Supreme Court case decided in 1979, before the era of big data.

Read more. [Image: Reuters]

12:55pm
(Notes: 163)
  
Filed under: NSA Supreme Court Privacy Big Data NSA spying Smith v. Maryland SCOTUS 
December 2, 2013
HP Lovecraft on Big Data

“The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents.”

9:25am
(Notes: 117)
  
Filed under: HP Lovecraft Big Data Technology The Call of Cthulhu Cthulhu Lovecraft 
November 21, 2013
Your Job, Their Data: This Might Be the Most Important Story About the Future All the drones, synthetic biologists, and self-driving cars notwithstanding, the story of how companies quantify, analyze, and try to predict your job performance may be the most important story in technology. That is to say, when we look back in 20 years about what has changed in our lives, we will be able to find this thread of data-driven personnel decision making as the thing that&rsquo;s changed people&rsquo;s lives the most.  My colleague Don Peck has an unnerving feature in this month&rsquo;s magazine on precisely this issue: &ldquo;They&rsquo;re Watching You At Work.&rdquo; I highly encourage you to absorb this tale&rsquo;s anecdotes and data.  After reading it, your gut may feel optimistic, like his, or queasy, like mine. Because the &ldquo;Moneyballing&rdquo; of human resources and corporate management has already begun, and who is going to stop it?  Peck&rsquo;s reporting turned up some amazing/horrifying details about the current prevalence of data-driven corporate practices. For example, he writes, &ldquo;The Las Vegas casino Harrah’s tracks the smiles of the card dealers and waitstaff on the floor (its analytics team has quantified the impact of smiling on customer satisfaction).&quot;  Maybe that&rsquo;s nice from a bottom-line perspective, but imagine working at Harrah&rsquo;s: &quot;Hey, Alexis, your smile ratio was down today. Keep those lip corners up, buddy!&rdquo; Do we want to live in that world? Read more. [Image: Shutterstock]

Your Job, Their Data: This Might Be the Most Important Story About the Future

All the drones, synthetic biologists, and self-driving cars notwithstanding, the story of how companies quantify, analyze, and try to predict your job performance may be the most important story in technology.

That is to say, when we look back in 20 years about what has changed in our lives, we will be able to find this thread of data-driven personnel decision making as the thing that’s changed people’s lives the most. 

My colleague Don Peck has an unnerving feature in this month’s magazine on precisely this issue: “They’re Watching You At Work.” I highly encourage you to absorb this tale’s anecdotes and data. 

After reading it, your gut may feel optimistic, like his, or queasy, like mine. Because the “Moneyballing” of human resources and corporate management has already begun, and who is going to stop it? 

Peck’s reporting turned up some amazing/horrifying details about the current prevalence of data-driven corporate practices. For example, he writes, “The Las Vegas casino Harrah’s tracks the smiles of the card dealers and waitstaff on the floor (its analytics team has quantified the impact of smiling on customer satisfaction)." 

Maybe that’s nice from a bottom-line perspective, but imagine working at Harrah’s: "Hey, Alexis, your smile ratio was down today. Keep those lip corners up, buddy!”

Do we want to live in that world?

Read more. [Image: Shutterstock]

7:25pm
(Notes: 152)
  
Filed under: Technology Jobs Work Big Data Futurism Human resources Moneyballing 
November 21, 2013
They&rsquo;re Watching You At Work In 2003, thanks to Michael Lewis and his best seller Moneyball, the general manager of the Oakland A’s, Billy Beane, became a star. The previous year, Beane had turned his back on his scouts and had instead entrusted player-acquisition decisions to mathematical models developed by a young, Harvard-trained statistical wizard on his staff. What happened next has become baseball lore. The A’s, a small-market team with a paltry budget, ripped off the longest winning streak in American League history and rolled up 103 wins for the season. Only the mighty Yankees, who had spent three times as much on player salaries, won as many games. The team’s success, in turn, launched a revolution. In the years that followed, team after team began to use detailed predictive models to assess players’ potential and monetary value, and the early adopters, by and large, gained a measurable competitive edge over their more hidebound peers. That’s the story as most of us know it. But it is incomplete. What would seem at first glance to be nothing but a memorable tale about baseball may turn out to be the opening chapter of a much larger story about jobs. Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed. Yes, unavoidably, big data. As a piece of business jargon, and even more so as an invocation of coming disruption, the term has quickly grown tiresome. But there is no denying the vast increase in the range and depth of information that’s routinely captured about how we behave, and the new kinds of analysis that this enables. By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007. Ordinary people at work and at home generate much of this data, by sending e-mails, browsing the Internet, using social media, working on crowd-sourced projects, and more—and in doing so they have unwittingly helped launch a grand new societal project. “We are in the midst of a great infrastructure project that in some ways rivals those of the past, from Roman aqueducts to the Enlightenment’s Encyclopédie,” write Viktor Mayer-Schönberger and Kenneth Cukier in their recent book, Big Data: A Revolution That Will Transform How We Live, Work, and Think. “The project is datafication. Like those other infrastructural advances, it will bring about fundamental changes to society.” Read more. [Image: Peter Yang]

They’re Watching You At Work

In 2003, thanks to Michael Lewis and his best seller Moneyball, the general manager of the Oakland A’s, Billy Beane, became a star. The previous year, Beane had turned his back on his scouts and had instead entrusted player-acquisition decisions to mathematical models developed by a young, Harvard-trained statistical wizard on his staff. What happened next has become baseball lore. The A’s, a small-market team with a paltry budget, ripped off the longest winning streak in American League history and rolled up 103 wins for the season. Only the mighty Yankees, who had spent three times as much on player salaries, won as many games. The team’s success, in turn, launched a revolution. In the years that followed, team after team began to use detailed predictive models to assess players’ potential and monetary value, and the early adopters, by and large, gained a measurable competitive edge over their more hidebound peers.

That’s the story as most of us know it. But it is incomplete. What would seem at first glance to be nothing but a memorable tale about baseball may turn out to be the opening chapter of a much larger story about jobs. Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.

Yes, unavoidably, big data. As a piece of business jargon, and even more so as an invocation of coming disruption, the term has quickly grown tiresome. But there is no denying the vast increase in the range and depth of information that’s routinely captured about how we behave, and the new kinds of analysis that this enables. By one estimate, more than 98 percent of the world’s information is now stored digitally, and the volume of that data has quadrupled since 2007. Ordinary people at work and at home generate much of this data, by sending e-mails, browsing the Internet, using social media, working on crowd-sourced projects, and more—and in doing so they have unwittingly helped launch a grand new societal project. “We are in the midst of a great infrastructure project that in some ways rivals those of the past, from Roman aqueducts to the Enlightenment’s Encyclopédie,” write Viktor Mayer-Schönberger and Kenneth Cukier in their recent book, Big Data: A Revolution That Will Transform How We Live, Work, and Think. “The project is datafication. Like those other infrastructural advances, it will bring about fundamental changes to society.”

Read more. [Image: Peter Yang]

10:04am
(Notes: 61)
  
Filed under: Business Work Jobs Big Data Data Longform Longreads Lit 
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