Tuesday, April 25, 2017
Review: The Farthest
I saw The Farthest last night at the Tribeca Film Festival and highly recommend it. This is about the Voyager space probes and the people who sent them to the outer solar system and beyond. That mission not only opened vast new vistas of exploration but also marked an early example of the synergy of humans and robots in achieving unprecedented things (and, remarkably, doing it with 1970s computing technology now comparable to a key fob). The film does an adept job at interweaving science communication, striking imagery and personal recollections, with narration provided by numerous interviews with project scientists, engineers and other participants.
My lifelong interest in space exploration was sparked in considerable degree, I'm sure, by seeing the images of Jupiter and Saturn returned by the Voyagers in the late 1970s and early 1980s. Seeing the film's interview with Linda Morabito, the astronomer who first saw an image of a volcanic eruption on Jupiter's moon Io, reminded me that I saw her in a TV interview back at the time. It was also good to see Nick Sagan, my onetime Space.com colleague, discuss his parents' and his own involvement with the golden record, which includes his own voice saying immortally, "Hello from the children of planet Earth." A very funny bit of the movie recalls a press conference about that record that NASA, reluctant to emphasize the mission's "alien" aspect, relegated to a hotel banquet hall with a wedding in progress on the other side of a room divider.
I expect the film will find an audience among the sorts of people I've worked with in science- and space-focused journalism, and I hope it will find a broader audience as well. An interesting perspective from the filmmakers, who were present last night for a Q and A and who are from Ireland, is that this is a uniquely American story; no other country has done anything like this, on such a scale. At the same time (and as reflected in the multilingual, multicultural golden record) the mission was an achievement for humanity at large. And while this particular feat won't happen again (it hinged on a once-in-176-year planetary alignment) may the future have much more where that came from.
Friday, April 21, 2017
Review: Deep Thinking
I tweeted this a few days ago:
As Kasparov aptly notes, chess is not a great measure for intellectual ability in general. Notwithstanding the game's demands for memory and concentration, correlations between chess skill and general intelligence are weak. For all its dazzling variety of possibilities, chess is not deep enough to have required the sort of machine learning that recently enabled a program to beat the top human player of the game Go. Rather, chess programs rose to Grandmaster level through simpler programming--using brute-force techniques of searching through numerous positions and assigning values (based on material strength of pieces and other readily measurable factors) rather than developing strategic concepts, let alone any understanding of the psychology of an opponent.
Consider the ascending level of difficulty an AI would face in accomplishing the following tasks (this hierarchy is my notion, not Kasparov's):
1. Playing chess really, really well. (Done.)
2. Playing a randomly selected chess variant really well, with different rules, pieces, shape and size of board, etc. (I considered this possibility a decade and a half ago in a perhaps slightly weird article.)
3. Inventing a new chess variant or other board game, with an emphasis on one that has many novel, unexplored possibilities. (Bonus: marketing the game and persuading people to play it.)
4. Subjectively experiencing any of the above, including feeling emotions about its activities.
5. Deciding unprompted to move on to a new career, such as writing, running for office, etc.
A computer that does all that does not seem likely to arrive anytime soon, even as AI logs genuine accomplishments in a wide range of fields. Kasparov, who has about as much reason as anyone to be chagrined about computers' capacity to outperform humans and take away their jobs, takes a persuasively optimistic view, seeing technology's potential to expand rather than replace human abilities. He notes the high performance that human-computer combos have had in the chess world, and that in addition to human and computer ability a key role can be played by "process"--being the best at meshing the two to maximize their strengths. He makes many other interesting observations, such as about the danger of excessive reliance on optimization--fine-tuning existing abilities--as a substitute for innovation that opens entire new avenues and measures of what can be done.
Fears of computers taking away jobs--or taking over the world--may soon give way to fears of humans doing bad things with the vast computer resources now at hand. I suspect the latter danger will get growing attention as more is learned about how the Russian government and its allies (or pawns) have deployed hacking and data mining in American and other elections around the world. As it happens, Kasparov has been a prescient observer of the geopolitical danger emanating from Russia.
The rapid advances in computing and other technologies require, well, deep thinking, and this book by that name deserves a wide audience, including but not limited to chess aficionados.
Note: I'd originally intended and been commissioned to review the book for the magazine Scientific American Mind, which unfortunately is no longer appearing in print form, hence my choice to write a review here at my own blog instead.
I've now read Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins and can say that I was not disappointed. It's a thoroughly absorbing book, most of which I read in one sitting. It did confound my expectations in a way, though: somehow I'd expected there to be less chess in it. In retrospect, I realize that reflects the extent to which I've come to think of Garry Kasparov as a writer and activist no less than as a chess player; but of course chess was and always will be a central element of his career, and so it should be no surprise that computer chess, and in particular his battles with IBM's Deep Blue, occupies much of the space in this book. Even so, he does a capable job of tying that history--deeply personal for him--into broader considerations about human and machine intelligence.I've been looking forward to this, by @Kasparov63, which just arrived as review copy. High expectations. pic.twitter.com/zkhVXy3sZB— Kenneth Silber (@kennethsilber) April 17, 2017
As Kasparov aptly notes, chess is not a great measure for intellectual ability in general. Notwithstanding the game's demands for memory and concentration, correlations between chess skill and general intelligence are weak. For all its dazzling variety of possibilities, chess is not deep enough to have required the sort of machine learning that recently enabled a program to beat the top human player of the game Go. Rather, chess programs rose to Grandmaster level through simpler programming--using brute-force techniques of searching through numerous positions and assigning values (based on material strength of pieces and other readily measurable factors) rather than developing strategic concepts, let alone any understanding of the psychology of an opponent.
Consider the ascending level of difficulty an AI would face in accomplishing the following tasks (this hierarchy is my notion, not Kasparov's):
1. Playing chess really, really well. (Done.)
2. Playing a randomly selected chess variant really well, with different rules, pieces, shape and size of board, etc. (I considered this possibility a decade and a half ago in a perhaps slightly weird article.)
3. Inventing a new chess variant or other board game, with an emphasis on one that has many novel, unexplored possibilities. (Bonus: marketing the game and persuading people to play it.)
4. Subjectively experiencing any of the above, including feeling emotions about its activities.
5. Deciding unprompted to move on to a new career, such as writing, running for office, etc.
A computer that does all that does not seem likely to arrive anytime soon, even as AI logs genuine accomplishments in a wide range of fields. Kasparov, who has about as much reason as anyone to be chagrined about computers' capacity to outperform humans and take away their jobs, takes a persuasively optimistic view, seeing technology's potential to expand rather than replace human abilities. He notes the high performance that human-computer combos have had in the chess world, and that in addition to human and computer ability a key role can be played by "process"--being the best at meshing the two to maximize their strengths. He makes many other interesting observations, such as about the danger of excessive reliance on optimization--fine-tuning existing abilities--as a substitute for innovation that opens entire new avenues and measures of what can be done.
Fears of computers taking away jobs--or taking over the world--may soon give way to fears of humans doing bad things with the vast computer resources now at hand. I suspect the latter danger will get growing attention as more is learned about how the Russian government and its allies (or pawns) have deployed hacking and data mining in American and other elections around the world. As it happens, Kasparov has been a prescient observer of the geopolitical danger emanating from Russia.
The rapid advances in computing and other technologies require, well, deep thinking, and this book by that name deserves a wide audience, including but not limited to chess aficionados.
Note: I'd originally intended and been commissioned to review the book for the magazine Scientific American Mind, which unfortunately is no longer appearing in print form, hence my choice to write a review here at my own blog instead.
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