Book: The Most Human Human

The Turing Test is meant to gauge a machine’s intelligence. The test, as proposed by Alan Turing in 1950, asks for computers to imitate human beings well enough as to believably carry on a conversation with a human, such that the human does not realize he or she is conversing with a machine instead of an actual person.

The Loebner Prize is an annual competition that presents a platform for teams and their chatbots to see how they fare in such an imitation game and to ideally pass the Turing Test. The winner of the Loebner Prize is that bot that is voted to be the most human-like computer.

Brian Christian participated in the 2009 installment of the competition. He did not contribute a chatbot, but rather was one of the human confederates. Just like a software bot, the confederate’s task is of course also to convince the judge of his humanity during their written chats, thus trying to keep them from judging a computer program to seem more human-like than him based on a conversation. As it turns out, being the most convincing human human, has its rewards, too:

But there is also, intriguingly, another title, one given to the confederate who elicited the greatest number of votes and greatest confidence from the judges: the “Most Human Human” award.
One of the first winners, in 1994, was Wired columnist Charles Platt. How’d he do it? By “being moody, irritable, and obnoxious,” he says – which strikes me as not only hilarious and bleak but also, in some deeper sense, a call to arms: How, in fact, do we be the most human humans we can be – not only under the constraints of the test, but in life?

An intriguing question indeed! Competing against software that strives to be as human-like as possible can serve as great motivation to contemplate what exactly it means for a person to come across as a human – other than just being oneself.

Brian Christian’s book The Most Human Human: What Talking with Computers Teaches Us About What It Means to Be Alive examines that question in some depth. Our notion of (artificial) intelligence and valid tests thereof keep changing as computer become able to accomplish tasks that were previously assumed to take real, human intelligence. Chess was a great example of this and so was the game of Jeopardy.

As computers and our capacity to program them and make them smarter improves, the machines appear to be gaining ground. Does that mean it is just a matter of time, until the machines will pass the tests we present or are we able to improve ourselves to stay ahead of them? The author seems to think so:

In an article about the Turing test, Loebner Prize co-founder Robert Epstein wrote, “One thing is certain: whereas the confederates in the competition will never get any smarter, the computer will.” I agree with the latter, and couldn’t disagree more strongly with the former.

The author joined Jon Stewart for a brief segment on The Daily Show to discuss his book, the Loebner Prize and Artificial Intelligence:

It is a brief, but informative conversation. My favorite part occurs around the 2:35 mark. Jon Stewart: “Tell me, how computers have progressed – they’ve been able to, obviously, beat us at chess, and now at Jeopardy … Will they move on … beyond our hobbies? [... or will they always be stuck in these types of games in their capacities?]”

The Most Human Human is a thought-provoking, engaging read – highly recommended.

Better, worse or all the same

In The Information – How the Internet gets inside us, Adam Gobnik identifies three different perspectives of commentary with respect to the Internet and the changes it brings:

All three kinds appear among the new books about the Internet: call them the Never-Betters, the Better-Nevers, and the Ever-Wasers. The Never-Betters believe that we’re on the brink of a new utopia, where information will be free and democratic, news will be made from the bottom up, love will reign, and cookies will bake themselves. The Better-Nevers think that we would have been better off if the whole thing had never happened, that the world that is coming to an end is superior to the one that is taking its place, and that, at a minimum, books and magazines create private space for minds in ways that twenty-second bursts of information don’t. The Ever-Wasers insist that at any moment in modernity something like this is going on, and that a new way of organizing data and connecting users is always thrilling to some and chilling to others—that something like this is going on is exactly what makes it a modern moment. One’s hopes rest with the Never-Betters; one’s head with the Ever-Wasers; and one’s heart? Well, twenty or so books in, one’s heart tends to move toward the Better-Nevers, and then bounce back toward someplace that looks more like home.

All three perspectives make an important contribution to the thinking around this and none of them should be ignored. I think this is particularly true, because there really is no turning around anymore: Having introduced new knowledge and technology, once a massive progress has been put into motion, it is not going to be simply undone.

I am counting myself in the Never-Betters camp, for the most part. The above article is an excellent contribution to the discourse though. I am looking forward to learning more, particularly about the Ever-Wasers perspective that emphasizes that similar debates (and struggles) occurred at other times in history in comparable manner, when significant changes were introduced.

Research presentations need to take advantage of web technologies

Web Experts Ask Scientists To Use the Web To Improve Understanding, Sharing of Their Data in Science Magazine reports on an article by Peter Fox and James Hendler in which the authors ask for better visualizations in research presentations.

In addition to the ease of using and developing visualization on the Web, visualizations on the Web can also be easily modified, updated, customized, and recreated by other users thanks to the use of Uniform Resource Identifiers. This “linking” of data is a key feature of the new vision that Fox and Hendler outline. It is of particular importance when dealing with what they refer to as “big science” on topics such as climate change that involves data that ranges from distinct fields like biology to geology.

The actual article is titled Changing the Equation on Scientific Data Visualization and its full text is available with free registration here.

I think a significant issue here is that the typical form of presenting a piece of research online is in the form of a document, most likely in PDF, PostScript or LaTeX format. A file like that has several strong advantages: It can be easily printed, emailed or viewed in a document viewer. It is also inherently static though: A PDF file does not integrate well with the dynamic experience of the web.

Compelling visualizations, perhaps allowing readers to experiment with different views, subsets of the data or modifications of it could go some way in bringing life into the presentation. Currently, consumers of those documents are just that: consumers, readers. There is no widespread way for them to interact with the presentation – and other readers.

It would be excellent to see those presentations move from static documents to dynamic experiences. Perhaps a semantic wiki for research papers might take this in the right direction?

Users rationally ignoring security advice

In What Security Advice Should We Give?, Greg Linden points out an intriguing piece of research: According to Cormac Herley‘s So Long, And No Thanks for the Externalities: The Rational Rejection of Security Advice by Users [PDF] it often makes little sense for computer users to follow security advice. It comes down to costs (user effort) vs benefit:

It is often suggested that users are hopelessly lazy and unmotivated on security questions. They chose weak passwords, ignore security warnings, and are oblivious to certificates errors. We argue that users’ rejection of the security advice they receive is entirely rational from an economic perspective. The advice offers to shield them from the direct costs of attacks, but burdens them with far greater indirect costs in the form of effort.
[...]
Thus we find that most security advice simply offers a poor cost-benefit tradeoff to users and is rejected. Security advice is a daily burden, applied to the whole population, while an upper bound on the benefit is the harm suffered by the fraction that become victims an- nually. When that fraction is small, designing security advice that is beneficial is very hard. For example, it makes little sense to burden all users with a daily task to spare 0.01% of them a modest annual pain.

In other areas of life we have long ago come up with a way to deal with similar costs. We invented insurance for health, car, property, etc. for what-if scenarios and our policies are typically priced in a way appropriate to our risk profile. I am sure we will see lots of progress in terms of security user education, computer security research – as well as sophistication of attacks.

Could personal insurance policies against cyber attacks also become a realistic, mainstream option?