In March, the Georgia State General Assembly passed a bill that would make it illegal to access a computer or network “without authority.” Georgia Governor Nathan Deal has until Tuesday to decide whether to sign it into law or veto it. The 40-day limbo has morphed from a bureaucratic formality, though, into a heated debate with national implications. In just 43 lines, the bill raises fundamental questions about how to establish boundaries in cyberspace without hindering vital security research and, crucially, the ethics of “hacking back,” in which institutions that have been attacked can digitally pursue the hackers and even potentially retaliate.
Georgia Senate Bill 315 emerged in part out of an embarrassing and troubling incident in which a massive trove of sensitive election and voter data sat exposed for months in Georgia’s unified election center at Kennesaw State University. Frustrated that it wasn’t illegal for people to access the data when it was accidentally publicly available, lawmakers set out to limit the legality of unauthorized computer access. But critics say that the resulting legislation as written is too vague, and threatens to outlaw certain types of digital forensic research while exempting—and therefore potentially condoning—dangerous “cybersecurity active defense measures.”
“I don’t think this legislation actually solves a problem,” says Jake Williams, founder of the Georgia-based security firm Rendition Infosec.
The state of Michigan notched another mobility-industry win today when the Toyota Research Institute (TRI) announced that a 60-acre parcel in Ottawa Lakes, MI, will be the home of a new autonomous vehicle development and testing facility, the first dedicated exclusively to TRI’s use.
TRI is Toyota’s research arm, which aims to enhance the safety of automobiles, increase access to vehicles for those who otherwise cannot drive, and accelerate scientific discovery by applying techniques from artificial intelligence and machine learning to other areas in order to lower costs and improve performance.
TRI opened a $1 billion research operation in Ann Arbor in 2016, and has additional U.S. locations in Cambridge, MA, and Palo Alto, CA. The organization employs a total of nearly 300 people between all three locations, while Toyota has more than 2,600 employees across Michigan. TRI did not say whether it would need to hire additional staff at the new testing facility.
The Thai chicken bowl from Spyce Food’s new restaurant in downtown Boston wasn’t life-changing, but it’s one of the better meals I’ve had from a “fast casual” restaurant—and certainly the best I’ve had that was prepared mostly by robots.
OK, it’s the first meal I’ve eaten that was cooked by a robotic system, with help from humans. (See video below.) That novelty might attract a lot of curious and hungry customers to Spyce’s doors in the coming weeks. But if the restaurant is going to survive, it’ll come down to whether or not people like the food. Michael Farid, Spyce’s CEO and co-founder, understands this well.
Meal quality is the “most important thing,” he says in an interview this week at the restaurant, after I’ve taken my first few bites of the curry dish. “Hopefully [people will] come back a second time because they enjoyed their meal.”
Countless digital goods are free. Companies such as Facebook and Twitter obtain revenues from other sources, such as advertising. But in light of recent controversies, there have been practical discussions about changing the business model and more theoretical discussions about economic valuation. What if people were required to pay to use Facebook? How much would they be willing to spend?
Any answers would tell us something important about the value of social media in general. They might also tell us something more general about economic valuation of legal entitlements, about the potentially expressive quality of some consumption decisions, and about the disparity between traditional economic measures and actual human welfare. They would bear on potential legal regulation as well.
In April 2018, I conducted a pilot experiment to obtain some preliminary answers. Using Amazon’s Mechanical Turk, I asked 439 Facebook users—not a nationally representative sample, but one with significant demographic diversity—to say how much use of the platform is worth. More specifically, I asked 215 Facebook users a simple question: “Suppose that you had to pay for the use of Facebook. How much would you be willing to pay, at most, per month?” At the same time, I asked 234 other Facebook users a different question: “Suppose that you are being offered money to stop using Facebook. How much would you have to be paid per month, at a minimum, to make it worth your while to stop using Facebook?”
At a conference in Silicon Valley this week, Mark Zuckerberg, Facebook’s chief executive, vowed that his company would “keep building” despite a swirl of questions around the way it has dealt with misinformation and the personal data of its users.
That is certainly true in the important area of artificial intelligence, which Mr. Zuckerberg says can help the social media giant deal with some of those problems.
Facebook is opening new A.I. labs in Seattle and Pittsburgh, after hiring three A.I. and robotics professors from the University of Washington and Carnegie Mellon University. The company hopes these seasoned researchers will help recruit and train other A.I. experts in the two cities, Mike Schroepfer, Facebook’s chief technology officer, said in an interview.
The Defense Advanced Research Projects Agency has picked research teams that will develop new machine learning methods designed to enable artificial intelligence systems to adapt to new changes and implement previous knowledge and skills to new situations.
DARPA said Thursday teams from the University of California in Irvine, Tufts University and University of Wyoming will perform work on two technical areas of the agency’s Lifelong Learning Machines program.
The L2M program’s first technical area will deal with the development of complete platforms and components, while the other will look at learning methods in biological organisms and transition those mechanisms into computational processes.
Bill Benter did the impossible: He wrote an algorithm that couldn’t lose at the track. Close to a billion dollars later, he tells his story for the first time.
“I started researching because I wanted to see if I could use it myself. And there’s this hard to break through veneer of words and frameworks and mathematics — but once you get through that the concepts are actually really intuitive. In fact even more intuitive than regular programming, because you’re teaching the machine like you teach a person.”
But like the hard shell of jargon, existing tools were also rough on the edges — powerful and functional, but much more like learning a development environment than playing around in Photoshop or Logic.
“You need to know how to piece these things together, there are lots of things you need to download. I’m one of those people who if I have to do a lot of work, download a bunch of frameworks, I just give up,” he said. “So as a UI designer I saw the opportunity to take something that’s really complicated and reframe it in a way that’s understandable.”
Princeton’s computer science department has launched a research program called the IOT Inspector they hope will provide users with a little more insight into what IOT devices are actually up to. The researchers behind the project say they spent some time analyzing fifty different common IOT devices, and like previous studies found that security and privacy in these devices was a total shitshow. Sending private user data unencrypted back to the cloud was common:
Unfortunately, many of the devices we have examined lack even these basic security or privacy features. For example, the Withings Smart Blood Pressure Monitor included the brand of the device and the string “blood pressure” in unencrypted HTTP GET request headers. This allows a network eavesdropper to (1) learn that someone in a household owns a blood pressure monitor and (2) determine how frequently the monitor is used based on the frequency of requests. It would be simple to hide this information with SSL.”
Few academics will be surprised to hear that more evidence has come out showing that student evaluations of teaching are often biased.
The latest study, released this year by the American Political Science Association, found that the “language students use in evaluations regarding male professors is significantly different than language used in evaluating female professors.” The study also showed that “a male instructor administering an identical online course as a female instructor receives higher ordinal scores in teaching evaluations, even when questions are not instructor-specific.”
Kristina Mitchell, one of the study’s authors, summarized its findings in Slate last month and concluded: “Our research shows they’re biased against women. That means using them is illegal.” Academic institutions must stop giving an inordinate amount of weight to student evaluations when making employment decisions, she argued, until the institutions can account for, address, and eliminate bias.
Raising prices is always risky — especially if it’s for something customers love.
Amazon announced it will be increasing the price of a yearly subscription of Prime by $20 in the US, to $119.
CFO Brian Olsavsky disclosed the price increase on an earnings call discussing the company’s latest financial results last week, saying the change would take effect May 11 for new members and affect Prime membership renewals af
To the credit of advocates, journalists, and academic researchers, issues of fairness and bias in the algorithmic and data-driven systems that govern our lives have recently taken on an increasing sense of urgency. This heightened awareness allowed people to challenge this work immediately, whether in the room or online.
It’s a conversation that is essential for constructively scrutinizing technology and the role we want it to play in our world.
But the problem here isn’t only one of biased datasets or unfair algorithms and of unintended consequences. It’s also indicative of a more persistent problem of researchers actively reproducing ideas that damage vulnerable communities and reinforce current injustices.
New York, NY May 18, starting at 9:30 a.m., NYU Politics Department (19 W. 4th Street). “The Identity Politics Research Group (IPRG), a Northeastern research group interested in the study of race, class, gender, religion, and sexuality in American politics and comparative contexts, invites interested scholars to attend our upcoming meeting.” [registration required]
“Find a data visualization online, in a book, or create one yourself. We need a digital version of the viz you’re recreating, so save the link or take a photo of it. Now, gather up some goodies from around the house or yard and/or hit the craft store (or maybe the grocery store!) and recreate that data viz in craft form!” Deadline for submissions is May 27.
It is our pleasure to announce that Project Jupyter has been awarded the 2017 ACM Software System Award, a significant honor for the project. We are humbled to join an illustrious list of projects that contains major highlights of computing history, including Unix, TeX, S (R’s predecessor), the Web, Mosaic, Java, INGRES (modern databases) and more.
“The University of Utah’sSuresh Venkatasubramanian and Katie Shelef are teaching a course in ‘Ethics in Data Science’ and they’ve published a comprehensive syllabus for it; it’s a fantastic set of readings for anyone interested in understanding and developing ethical frameworks for computer science generally, and data science in particular.”
“If you like this kind of thing, check out this master list of tech ethics course syllabi with more than 150 such courses!”
