This post is originally from my personal website, xtrp.io where you can read about me, check out my projects, and more.
Deep Thinking is a book written by Garry Kasparov about chess and machine learning. Kasparov, who is a former chess world champion, is famous not only for his achievements in chess, but for being the first world champion to lose to a computer in May 1997.
IBM's Deep Blue (chess machine) beat Kasparov in 1997, making the match one of the most well-known and famous chess matches in history, boosting IBM's stock by 3.6%, reaching a 10-year high, in just one day.
Deep Thinking is a very informative book and sheds a lot of insight into Kasparov's own experience with machine intelligence, as well as his thoughts on how machines will drastically influence our future as a society.
It has become clear that, in general, humans think and solve problems differently than machines. Machines are very logical and not creative, thinking and working in very straightforward instructions and algorithms. Humans, on the other hand, are more abstract thinkers and are more creative.
The fact is that in many ways, while machines succeed where humans do not, the converse is also true. A human may be able to match a face to a person with great ease, whereas a machine may have to be programmed with complex algorithms to achieve facial recognition. On the other hand, machines may be able to calculate a very long mathematical formula very quickly, whereas a human may take a long time to calculate the result.
The different ways of thinking between humans and machines are made clear in Kasparov's match versus Deep Blue.
Deep Blue uses a very brute force method of play, calculating millions of possible positions using a variation of the minimax algorithm with an evaluation function. Deep Blue pays attention to the calculations in chess.
Kasparov, however, is human and plays with strategy. He may not be able to calculate as fast a machine, nor could he evaluate every possible position 20 moves ahead. Despite this, he does know general principles and heuristics of the game. After all, he was the world champion.
The match was close, and Deep Blue won. Kasparov was spoken of as the defender of human intelligence, and losing the match was widely regarded as the turning point where machine intelligence had surpassed that of humans. However, the loss for Kasparov was a huge win for the IBM team and computer science as a whole (it was also great for IBM's investors, but that's a different blog post).
With machine vs. human matches becoming more popular at the time, Kasparov came up with an idea for a different, new type of chess, not where humans played against humans or where humans played against machines, but a human+machine tournament, where each human had the assistant of a chess engine and computer next to them during games.
The idea of combining human and machine intelligence has been around for a long time. In fact, whenever we use technology, we are combining our human intelligence with machine intelligence. For example, we can use a calculator (machine intelligence) along with human problem-solving skills to solve more lateral-thinking based math problems.
As Kasparov explains, this concept of human+machine intelligence is a primary influencer of driving our society forward. Huge companies like IBM are investing in human+machine intelligence, called IA, or "Intelligence Amplification".
Kasparov argues in the book that even as machines grow more and more intelligent, they will never be able to replicate the human qualities of emotion and creativity and joy. In truth, Kasparov says, machines can allow us to be more human by allowing us to be more creative, and be happier, not having to do previously tedious tasks that machines are increasingly starting to do for us.
As a developer, this opens up a whole new way of thinking of the future in tech. Kasparov writes that the future will likely be defined by how we use machines to help our society achieve our goals, whether that be through machine learning advancements, the rise of the internet of things, or both.
As a result, it may be helpful to consider the value of further diversifying developers’ roles and skills to have an increased focus on machine learning and AI.
While the future Kasparov speaks of in Deep Thinking may not be close, it is still approaching, and those that understand machines and AI will likely be at the forefront of that future.
Written by a person whose job and entire way of life was threatened by the rise of machines, Deep Thinking truly captures the idea that machines are shaping our future, and we need to focus our efforts on working with machines to achieve new and innovative technologies and realities.
I would really recommend reading Deep Thinking for yourself, and I hope you enjoyed this post. Garry Kasparov, the writer of the book, maintains a blog here, and is very active on his Twitter account. Of course, everything written in this post is my opinion, and I encourage you to do your own research on this topic.
Thanks for scrolling.
— Gabriel Romualdo, October 19, 2019
Originally published on my personal website: xtrp.io
Note: I formerly wrote under my pseudonym, Fred Adams.