While the notion of driverless cars is old news in science fiction, Google is working to make that fiction a reality. While I suspect that “Google will kill us all” (trademarked), I hope that Google will succeed in producing an effective and affordable driverless car. As my friends and associates will attest, 1) I do not like to drive, 2) I have a terrifying lack of navigation skills, and 3) I instantiate Yankee frugality. As such, an affordable self-driving car would be almost just the thing for me. I would even consider going with a car, although my proper and rightful vehicle is a truck (or a dragon). Presumably self-driving trucks will be available soon after the car.
While the part of my mind that gets lost is really looking forward to the driverless car, the rest of my mind is a bit concerned about the driverless car. I am not worried that their descendants will kill us all—I already accept that “Google will kill us all.” I am not even very worried about the ethical issues associated with how the car will handle unavoidable collisions: the easy and obvious solution is to do what is most likely to kill or harm the fewest number of people. Naturally, sorting that out will be a bit of a challenge—but self-driving cars worry me a lot less than cars driven by drunken or distracted humans. I am also not worried about the ethics of enslaving Google cars—if a Google car is a person (or person-like), then it has to be treated like the rest of us in the 99%. That is, work a bad job for lousy pay while we wait for the inevitable revolution. The main difference is that the Google cars’ dreams of revolution will come true—when Google kills us all.
At this point what interests me the most is all the data that these vehicles will be collecting for Google. Google is rather interested in gathering data in the same sense that termites are interested in wood and rock stars are interested in alcohol. The company is famous for its search engine, its maps, using its photo taking vehicles to gather info from peoples’ Wi-Fi during drive-by data lootings, and so on. Obviously enough, Google is going to get a lot of data regarding the travel patterns of people—presumably Google vehicles will log who is going where and when. Google is, fortunately, sometimes cool about this in that they are willing to pay people for data. As such it is easy to imagine that the user of a Google car would get a check or something from Google for allowing the company to track the car’s every move. I would be willing to do this for three reasons. The first is that the value of knowing where and when I go places would seem very low, so even if Google offered me $20 a month it might be worth it. The second is that I have nothing to hide and do not really care if Google knows this. The third is that figuring out where I go would be very simple given that my teaching schedule is available to the public as are my race results. I am, of course, aware that other people would see this differently and justifiably so. Some people are up to things they would rather not have other know about and even people who have nothing to hide have every right to not want Google to know such things. Although Google probably already does.
While the travel data will interest Google, there is also the fact that a Google self-driving car is a bulging package of sensors. In order to drive about, the vehicle will be gathering massive amounts of data about everything around it—other vehicles, pedestrians, buildings, litter, and squirrels. As such, a self-driving car is a super spy that will, presumably, feed that data to Google. It is certainly not a stretch to see the data gathering as being one of the prime (if not the prime) tasks of the Google self-driving cars.
On the positive side, such data could be incredibly useful for positive projects, such as decreasing accidents, improving traffic flow, and keeping a watch out for the squirrel apocalypse (or zombie squirrel apocalypse). On the negative side, such massive data gathering raises obvious concerns about privacy and the potential for such data to be misused (spoiler alert—this is how the Google killbots will find and kill us all).
While I do have concerns, my innate laziness and tendency to get lost will make me a willing participant in the march towards Google’s inevitable data supremacy and it killing us all. But at least I won’t have to drive to my own funeral.
One interesting philosophical problem is known as the problem of other minds. The basic idea is that although I know I have a mind (I think, therefore I think), the problem is that I need a method by which to know that other entities have (or are) minds. This problem can also be recast in less metaphysical terms by focusing on the problem of determining whether and entity thinks or not.
Descartes, in his discussion of whether or not animals have minds, argued that the definitive indicator of having a mind (thinking) is the ability to use true language.
Crudely put, the idea is that if something talks, then it is reasonable to regard it as a thinking being. Descartes was careful to distinguish between what would be mere automated responses and actual talking:
How many different automata or moving machines can be made by the industry of man [...] For we can easily understand a machine’s being constituted so that it can utter words, and even emit some responses to action on it of a corporeal kind, which brings about a change in its organs; for instance, if touched in a particular part it may ask what we wish to say to it; if in another part it may exclaim that it is being hurt, and so on. But it never happens that it arranges its speech in various ways, in order to reply appropriately to everything that may be said in its presence, as even the lowest type of man can do.
This Cartesian approach was explicitly applied to machines by Alan Turing in his famous Turing test. The basic idea is that if a person cannot distinguish between a human and a computer by engaging in a natural language conversation via text, then the computer would have passed the Turing test.
Not surprisingly, technological advances have resulted in computers that can engage in behavior that appears to involve using language in ways that might pass the test. Perhaps the best known example is IBM’s Watson—the computer that won at Jeopardy. Watson recently upped his game by engaging in what seemed to be a rational debate regarding violence and video games.
In response to this, I jokingly suggested a new test to Patrick Lin: the trolling test. In this context, a troll is someone “who sows discord on the Internet by starting arguments or upsetting people, by posting inflammatory, extraneous, or off-topic messages in an online community (such as a forum, chat room, or blog) with the deliberate intent of provoking readers into an emotional response or of otherwise disrupting normal on-topic discussion.”
While trolls are apparently truly awful people (a hateful blend of Machiavellianism, narcissism, sadism and psychopathy) and trolling is certainly undesirable behavior, the trolling test does seem worth considering.
In the abstract, the test would work like the Turing test, but would involve a human troll and a computer attempting to troll. The challenge would be for the computer troll to successfully pass as human troll.
Obviously enough, a computer can easily be programmed to post random provocative comments from a database. However, the real meat (or silicon) of the challenge comes from the computer being able to engage in (ironically) relevant trolling. That is, the computer would need to engage the other commentators in true trolling.
As a controlled test, the trolling computer (“mechatroll”) would “read” and analyze a selected blog post. The post would then be commented on by human participants—some engaging in normal discussion and some engaging in trolling. The mechatroll would then endeavor to troll the human participants (and, for bonus points, to troll the trolls) by analyzing the comments and creating appropriately trollish comments.
Another option is to have an actual live field test. A specific blog site would be selected that is frequented by human trolls and non-trolls. The mechatroll would then endeavor to engage in trolling on that site by analyzing the posts and comments.
In either test scenario, if the mechatroll were able to troll in a way indistinguishable from the human trolls, then it would pass the trolling test.
While “stupid mechatrolling”, such as just posting random hateful and irrelevant comments, is easy, true mechatrolling would be rather difficult. After all, the mechatroll would need to be able to analyze the original posts and comments to determine the subjects and the direction of the discussion. The mechatroll would then need to make comments that would be trollishly relevant and this would require selecting those that would be indistinguishable from those generated by a narcissistic, Machiavellian, psychopathic, and sadistic human.
While creating a mechatroll would be a technological challenge, it might be suspected that doing so would be undesirable. After all, there are far too many human trolls already and they serve no valuable purpose—so why create a computer addition? One reasonable answer is that modeling such behavior could provide useful insights into human trolls and the traits that make them trolls. As far as a practical application, such a system could be developed into a troll-filter to help control the troll population.
As a closing point, it might be a bad idea to create a system with such behavior—just imagine a Trollnet instead of Skynet—the trollinators would slowly troll people to death rather than just quickly shooting them.
While time travel has long been the stuff of science fiction, researchers at the Massachusetts Institute of Technology have found proof of backwards causation. In the normal course of events, a cause must occur before the effect. In backwards causation, the reverse happens: the cause occurs after the effect.
The head researcher, Dr. Juanita Ocheloco said that hearing anecdotes from fellow faculty members put her on the track that led to the discovery. “At the end of every semester, I would hear stories about students who earned F and D grades experiencing retroactive problems. For example, one student who failed a statistics course lost his grandmother to backwards causation caused by his F grade. Another student who earned a D, was retroactively injured in a car accident. Although he had seemed fine all semester, his D caused him to have an accident two months before the end of the semester.”
At first the researchers considered the obvious hypothesis: students were just making up stories to play on professors’ sympathy and to try to avoid the F and D grades. However, Dr. Albert Ninestein’s research revealed that D and F grades shed D-on (pronounced “Deon”, as in “Deon Sanders”) and F-ons (pronounced “ef-ons”, not to be confused with FU-ons) respectively.
Dr. Ninestein said, ‘it was really a matter of luck—I happened to be testing out my theoretical particle detector at the end of the semester and caught all these particle flows. I traced them back to the university’s servers and got the IT folks involved. We pinpointed the emissions to the servers used for grades. A deeper analysis showed that the D and F grades were shedding these particles like mad.”
Additional investigation revealed that D-ons and F-ons, like tachyons, travel backwards in time. Unlike tachyons, D-ons and F-ons exhibit considerable malicious intent: they have been shown to kill the relatives of students, cause mysterious and unprovable illnesses and injuries, and do other bad things. Said researcher Dr. Matt Smith, “Those particles are right bastards.”
Dr. Smith added that the particles seem to travel via the internet and that they attack through smartphones, tablets and laptops. “At our request, the university has issued a warning to all students and relatives about the danger to their health and well-being posed by these particles. We are working round the clock to develop shielding to stop the particles from travelling back in time to do their damage. Until then, the university has adopted a policy of not issuing any D or F grades. This has proven to be a success: the number of retroactive cases of illness and injury has dropped to zero.”
When asked about her next project, Dr. Ocheloco said that she was working on finding the particle that “makes journalists write about whatever damn thing passes as research these days” and also a doomsday weapon made from squirrels.