In Thinking Sideways, Jenifer Shahade shows that you don’t have to be a great chess player to think more like a chess player. From building mind palaces to crafting decision trees, she reveals the most useful strategies from the ancient game that we can use in our daily lives. Drawing on examples from business, sports, and psychology, as well as her own experiences touring the world as a chess and poker player, Shahade transforms our understanding of what success looks like, and how to achieve it for ourselves.
Pegasus Books kindly sent me a PDF galley of the book, which I read with enthusiasm. To give you an impression of the content and style, I will quote a passage, with kind permission of the publishers.
Thinking one move ahead
The King‘s Indian Attack is a universal opening: easy to learn, flexible, and rich in both tactical and positional opportunities.
Chess players have a reputation for thinking many moves ahead and many of us admire and attempt to imitate this in our lives. But the truth is more nuanced. Thinking far ahead can bring fewer rewards than looking thoroughly at more options. Imagine two decision makers. One looks at their favourite move ten moves forward, a branchless tree high into the sky. The second decision maker looks at four different moves, imagining each three moves into the future, for a shorter, fuller tree, with more branches. Who is looking at more moves? The second player, with twelve possibilities instead of ten. Player two looked fewer moves ahead, but they looked at more moves. And those moves are more likely to materialize, because they don’t require as many assumptions about how the future will unfold. The breadth of analysis matters even more than the depth.
As Grandmaster Anna Muzychuk says: “It’s not the length of the lines we are able to analyse, but the precision of the lines. Sometimes we only calculate two or three moves ahead.” Even Magnus Carlsen, the high-est rated chess player of all time, has said he doesn’t consider himself a particularly deep calculator. Rather: “I am good at calculating short lines” and “seeing little details” that others miss.
The third World Chess Champion, José Raúl Capablanca, known for his incredible chess talent and suave manners, put it best. In a legendary exchange, a journalist asked him, “How many moves do you think ahead?” The Cuban genius replied simply, “One. But it’s the right one.” If Capablanca looks only one move ahead how could he be so sure it was the right one? Because he scanned all the possibilities. One move ahead, but every move wide. The quote may be apocryphal and exaggerated but that has not stopped it from spreading widely through the decades. It is now more relevant than ever.
In 2024, Google’s artificial intelligence think tank DeepMind published an article based on their research, “Grandmaster-Level Chess Without Search”, a new chess AI model that played exactly in the famous ‘I think one move ahead’ mode. It was not about trying to make AI that could beat the best human chess players – that was already done in 1997. Nor was it trying to make the most powerful chess AI – DeepMind had already did that in 2017. It was more about removing a seemingly essential component to see if the AI could still function. How well could AI play well without any search at all? ‘Search’ here means ‘looking ahead’. This program would not plan ahead at all. It would just examine all of its options and pick the move that best matched success in similar patterns. Let that sink in. Imagine writing a poem without the letter ‘E’ or making brownies without chocolate.
What the program lacked in depth, it made up with in breadth. Using a database of millions of games and positions, totalling 15 billion data points, it had an extensive network of patterns to draw from that would help it guess the correct move in any situation. And yet, the idea of thinking ahead to the next sequence of moves is so intertwined with the popular idea of what makes a good chess player that it’s hard to imagine such a computer program playing well. It could easily miss a checkmate two moves ahead. So how good would this player be? Awful? Brilliant? Or somewhere in between?
The computer reached the level of a strong master, surpassing expectations and, most importantly, crushing the myth that strong chess players must plan many moves in advance.
Decision Trees 25help it guess the correct move in any situation. And yet, the idea of thinking ahead to the next sequence of moves is so intertwined with the popular idea of what makes a good chess player that it’s hard to imagine such a computer program playing well. It could easily miss a checkmate two moves ahead. So how good would this player be? Awful? Brilliant? Or somewhere in between?The computer reached the level of a strong master, surpassing expectations and, most importantly, crush-ing the myth that strong chess players must plan many moves in advance.
Humans can’t store billions of data points, so our ability to play well by thinking zero moves ahead would not work out as well as it did for the AI. But it also may not be as bad as you think. Imagine making decisions in life after laying out all possible options, then picking based on instinct. You probably would make a lot of mistakes, but you’d also make a lot of great choices. As someone who fell in love at first sight, I’m glad I didn’t think too many moves ahead when I decided to talk to the guy with the beaming smile that struck me from across the room.
About the author
Jennifer Shahade is a three-time National Chess Champion, author, and professional poker player. She competed on the 2004 U.S. Olympic team that won a silver medal. The first female to win the U.S Junior Open, Jennifer is passionate about empowerment and creative work around the games she loves most: chess and poker. She is a two-time Global Poker Award winner, has appeared on Jeopardy!, and has over 33,000 followers on X. She’s also on Instagram with 14,000 followers. Her writing has appeared in The Washington Post, The Wall Street Journal, and The New York Times. She is featured regularly on major news outlets as a spokesperson for women in chess and on topics like The Queen’s Gambit boom in chess popularity. Jennifer lives in Philadelphia.
