http://www.bbc.com/news/world-europe-39002142 An official watchdog in Germany has told parents to destroy a talking doll called Cayla because its smart technology can reveal personal data. The warning was issued by the Federal Network Agency (Bundesnetzagentur), which oversees telecommunications. Researchers say hackers can use an unsecure bluetooth device embedded in the toy to listen and talk to the child playing with it. But the UK Toy Retailers Association said Cayla "offers no special risk". In a statement sent to the BBC, the TRA also said "there is no reason for alarm".
The 2,578 Problems With Self-Driving Cars Last year, a self-driving car failed about every 3 hours in California, according to figures filed with the state's Department of Motor Vehicles. Every January, carmakers testing self-driving cars in California have to detail how many times their vehicles malfunctioned during the preceding year. These so-called disengagement reports detail every time a human safety driver had to quickly take control of their car, either due to hardware or software failure or because the driver suspected a problem. The reports—detailing 2,578 failures among the nine companies that carried out road-testing in 2016—give a unique glimpse into how much testing the different companies are doing, where they are doing it, and what is going wrong. None of this year's disengagements resulted in an accident. http://spectrum.ieee.org/cars-that-think/transportation/self-driving/the-2578-problems-with-self-driving-cars Alphabet's spin-out company Waymo still has by far the biggest testing program—its 635,868 miles of testing accounted for over 95 percent of all miles driven by self-driving cars in California in 2016. Waymo's fleet of 60 self-driving cars reported a total of 124 disengagements, 51 of them due to software problems. That represents a sharp reduction in disengagements from the previous year, from 0.8 disengagements for every 1,000 miles of autonomous driving down to just 0.2. <https://medium.com/waymo/accelerating-the-pace-of-learning-36f6bc2ee1d5#.2fldeeluo>
NNSquad http://boingboing.net/2017/02/20/the-previous-owners-of-used.html It's not just that smart cars' Android apps are sloppily designed and thus horribly insecure; they are also deliberately designed with extremely poor security choices: even if you factory-reset a car after it is sold as used, the original owner can still locate it, honk its horn, and unlock its doors. Again, this is by design: because auto-makers are worried about lockout and hacks (for example, a valet resetting your car to lock out your app), only the original dealer can sever the car's connection with the cloud accounts of the original owner. Charles Henderson, the leader of IBM's X-Force Red security division presented on this risk at last week's RSA conference in San Francisco (you can read his essay on the subject here). His ultimate recommendation is this counsel of despair: unless you are very technologically savvy, you should only buy new cars, not used ones. It's not just cars, either—the problem extends to smart appliances, thermostats, and other devices. Renting a house, staying in a hotel room, or buying a house without replacing its appliances and HVAC systems also exposes you to risks from the previous users of the devices in it. [Arthur T also noted this: How Previous Owners Can Potentially Still Access Their Cars Long After They've Sold Them http://jalopnik.com/how-previous-owners-can-potentially-still-access-their-1792534479 ]
Helen Wright, Ben Zorn, CCC Blog, 16 Feb 2017, via ACM TechNews, 17 Feb 2017 The Internet of Things (IoT) is having a multi-trillion-dollar impact on a range of industries, in addition to its significant societal impact on energy efficiency, health, and productivity. Although interconnected smart devices have unforeseen potential benefits, the IoT also comes with increased risk and potential for abuse. One major challenge of having a proliferation of IoT devices is the increased complexity that is required to operate them safely and securely, which creates new safety, security, privacy, and usability challenges. A recent Computing Community Consortium Computing in the Physical World Task Force report highlights some of the new challenges created by the IoT, and argues issues related to security, physical safety, privacy, and usability are interconnected. However, the report notes more research is needed to help manage the complexity, and to connect usability concerns with safety, security, and privacy. https://orange.hosting.lsoft.com/trk/click?ref=3Dznwrbbrs9_6-12ae0x211101x071860&
Knowledge@Wharton, 13 Feb 2017 via ACM TechNews, 17 Feb 2017 University of Pennsylvania professors Cade Massey and Joseph Simmons say their research into humans' distrust of algorithms is rooted in people's tendency to avoid following consistent, evidence-based rules in favor of their instincts and intuition. "People want algorithms to be perfect...even though what we really want is for them to simply be a little better than the humans," Simmons notes. The professors say one way to get people more comfortable with using algorithms is to give them a measure of control. "We can't get people to use algorithms 100 percent, but we can get them to use algorithms 99%, and that massively improves their judgments," Simmons says. Massey notes models and algorithms are held to a higher standard than people, and he and Simmons say their next research focus will be on applying their theories of humans' aversion to using algorithms to real-world scenarios. https://orange.hosting.lsoft.com/trk/click?ref=3Dznwrbbrs9_6-12ae0x211109x071860&
*Science* via NNSquad https://science.slashdot.org/story/17/02/19/2330251/serious-computer-glitches-can-be-caused-by-cosmic-rays A "single-event upset" was also blamed for an electronic voting error in Schaerbeekm, Belgium, back in 2003. A bit flip in the electronic voting machine added 4,096 extra votes to one candidate. The issue was noticed only because the machine gave the candidate more votes than were possible. "This is a really big problem, but it is mostly invisible to the public," said Bharat Bhuva. Bhuva is a member of Vanderbilt University's Radiation Effects Research Group, established in 1987 to study the effects of radiation on electronic systems.
Voting by paper ballots counted by hand has been in force for a number of years in The Netherlands. What's new is that the aggregation of votes into regional and national totals will now also be done manually. This is not very clear in the Guardian article. This may delay the outcome a bit. But it seems to be accepted that a reliable result is more important than an early one.
> [I am curious about chip flaws being more common than I thought. Is anyone > is a position to knowledgeably comment about this?] It seems that the designer of a safety-critical system should specify only Intel chips that are *at least* four years old: so that there is some hope that the most damaging bugs will have been shaken out! A chip less than four years old is basically still in "alpha test".
And this will work how? When even the mainstream news agencies are in the habit of (unintentionally) creating fake news? I'm reminded of a Radio 4 program a loooong time ago. There was a particularly juicy story in the news and a journalist decided to do some digging to find out where it had come from. Something to do with "a crisis in the Cabinet" with the Prime Minister (John Major, I think) having difficulties. A little bit of investigation quickly traced it back. The story originated in an interview with a Labour Shadow Minister, being interviewed about something else, and being pressed to provide information he didn't have, so he speculated. Oh!!! So the journalist dug into that story. To discover it, likewise, came from an interview with another, non-Labour, politician being pressed to speculate about another different story. To cut a long story short, I think the journalist traced this back through five or six different speculative stories, before he finally came to the real story that started it all, that had absolutely nothing to do with the story currently in the news.
In the previous RISKS, Geoff Kuenning noted Google's creepy photo-notification, but closes with: > And IMHO it certainly violates their motto of "Don't be evil." Google silently dropped the "Don't be evil" mantra many years ago. Here's an Article from 2009 noting they had dropped it: http://www.siliconvalleywatcher.com/mt/archives/2009/04/google_quietly.php Google has been quite evil for quite a long time.
Tiresome as it may be that some sites have ad-blocker-blockers, they have to pay their bills. Articles are what Wired sells—why should they give content away? If you don't like their requirements, don't view their content. I don't see asking me to view ads or pay for access as ransomware, any more than I think its unfair that my supermarket charges me for groceries. In RISKS there's [sometimes] a note about a paywall—this is essentially the same thing.
[via Dave Farber's IP] The WiReD article [URL only, in RISKS-30.14] is misleading and incomplete, and to a great extent incorrectly identifies the problem, for several reasons. (1) The problem isn't AI, or other forms of automation, it's the use to which AI and automation are put and the basic mechanisms for allocating and deploying resources in our society. For example, if AI were to be used to benefit the general population (healthcare, education, or other altruistic use) without an implication or requirement that anyone need profit by it, then one implication of the article—that the continued destruction of the middle class will to a great extent be the fault of AI -â€“ would vanish. Automation doesn't have to destroy jobs: we only say that, so we don't have to make difficult choices. We pretend that there's no choice. We simply don't want to deal with it. Yes, there are hardships, but as long as those hardships are someone else's, we don't care. As it stands, society surrenders to capital most decisions about resource allocation, and capital naturally acts in its own best interests. That is the problem. (2) The assumption that `jobs' are the only way to allocate resources is false. It derives from another false assumption, that the wealthy are morally entitled to all profits, interest, and rents. People blindly believe that the wealthy—who acquired their wealth from the labours of the working class in the first place—are `trapped' due to economic circumstances into unfortunate decisions that require job destruction. Nowadays, in our culture, people believe in the positive morality of interest (formerly, `usury') and profits and rents as surely as they once believed in the divine, inherited right of kings to rule over the lesser folk. These `rights' of the upper class, the owners, and the privileged have no basis in science or honest reasoning. There is plenty of work to be done, and there is plenty of wealth to feed, clothe, and shelter everyone, but with all of our immense knowledge we can think of only one way to address both issues: jobs offered by capitalists on the condition that they enable the capitalists to maximize their own accumulation of surplus value. Capitalists and landlords hold the common welfare hostage, demanding ransom. Once you let go of that connection, once you abandon that assumed precondition, many possibilities come to mind, including ways to deal with workers displaced by automation. The original economic sin was handing over the surplus to the few, and society has been in Purgatory and in Hell ever since. (3) The article wrongly implies that this is a new problem, that it started to show up in the 1980s. In fact, automation and machinery deployed by the capitalist system, which limits workers to market-minimized wages (including `fringe benefits' as part of a compensation package) has been forcing millions into poverty for centuries. Usually, the worst consequences are safely out of view, in the hinterlands of the empire or in the slums of our cities, where we aren't compelled to see them. AI is just another kind of capital resource, along with machine tools, farmland, workers, and pig iron. In their quests for profits, firms have been minimizing the costs of production factors for a long time. Now, however, the threat is closer to home. Think of the sewing machine. A sewing machine can make a family more independent and better off. On the other hand, sewing machines in sweatshops can provide poverty wages for many, profits for a few, and destroy handicraft industries in far-away places at the same time. The way we have employed technology wasn't mandatory: society had choices. AI and other automation offer similar opportunities for good and for bad. Where were these concerns when the lower classes, including those in the colonies and neo-colonies, were being thrown out of work? Where are those concerns now, as the poor and working classes sink lower, year after year? We don't give a damn about the lot of the poor or the working class in the Mideast, in Latin American, in Africa, or at home, as long as we middling sorts get our cut of their resources and of the fruits of their labours. We in the middle work for the rich, on commission: we have our incentives. Meanwhile, we have been conditioned by our commercial culture into believing that Bernie Sanders is a socialist, that the Soviet Union was communist, and that we live in a democracy. (I hope that most of the readers of this list know that all three beliefs are false.) Society, being willingly and comfortably ignorant, is thus poorly equipped to discuss this problem, let alone to `rise up' (to use McAfee's words, quoted in the article) and to rectify things. Again, the problem is not AI. Long ago we handed over to the upper class the power to rule over us middle, working, and lower class subjects. However, as Aristotle put it in his Politics, “But, although it may be difficult in theory to know what is just and equal, the practical difficulty of inducing those to forbear who can, if they like, encroach, is far greater, for the weaker are always asking for equality and justice, but the stronger care for none of these things.'' (Part 3, tr. Benjamin Jowett) We traded up, for the larger size problem. The problem is real. It is political, moral, social, economic, and ethical. But it is not technological. (BTW, the slides, by McAfee, linked from the article, are interesting, and worth examining, but they are short on detail and I can't draw conclusions from them alone. He doesn't explain how his plausible conclusion, that automation of routine tasks, accounts for the phenomenon with any direct or detailed data on specific job categories; he classifies, in the slides, jobs merely by high, medium, and low income. Subtext: you have to buy his new book. His conclusion requires a logical leap I can't bring myself to make. I hope that he's not equating `medium' income jobs with `middle class' jobs, that's not the way most researchers label those kinds of things; if that's what he's doing, it's very misleading. Maybe the misnomer arises in the WiReD reporting. Nor does he discuss possible additional social and financial causes for the phenomenon, causes which have been considered elsewhere. The first chapter of his book, co-authored with Erik Brynjolfsson, is on-line; it doesn't look too promising with regard to hard data: he deals more in summaries and conclusions than in raw data. None of this means that AI and other automation aren't to some extent causing the `spread' problem, it's merely that he doesn't make the case that the phenomenon is that simple. I conclude that it's an oversimplification. Kind of like a lot of TED talks, you can now go on home, being inspired and informed, knowing that you've met your obligation to go to church this week, but there's nothing in your own life that you, yourself, need to change, and nothing that you can do.)
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