This book covers the rise of computers and AI over the period Kasprov’s chess career. But for me the interesting insights are into the rising impact of technology on our lives, and the roles of psychology in decision making.
In my comments I have focused more on the takeaways I think are more widely applicable rather than on the chess focused aspects. I have replicated lots of wonderful and insightful quotes from the book:
Chess
It gives a fascinating insight into how much chess is a game of psychology at the elite levels.
- Emanuel Lasker – chess is not a science or an art – it is a fight. Play the man and not the board – play the move that makes your opponent feel most uncomfortable. It’s a psychological game.
It also gives insight into how someone like Kasparov is not just looking for the next best move but is aiming to develop an overarching strategy that he aims to adapt and customise to his understanding of his opponents strategy, be that opponent human or machine.
He summarises the rise of Chess playing computers as a timeline: Thousands of years of status quo human dominance, a few decades of weak computer competition, a few years struggle for computer supremacy. Then game over. For the rest of human history machines will be better than humans are chess. This is the unavoidable one-way street of technological progress in everything from the cotton-gin to manufacturing robots to intelligent agents.
The impact of technology on our lives, work and education
- It’s far easier to tell millions of newly redundant workers to retrain for the Information Age than to be one of them or to actually do it.
- The machines have finally come for the white collared, the college graduates, the decision-makers. And it’s about time.
- It is callous to say that all who suffer the consequences of tech disruption should be ignored and just get over it because, in the long run, this suffering won’t much matter. The point is that when it comes to looking for solutions to alleviate that suffering, going backwards isn’t an option. A corollary is that it is almost always better to start looking for alternatives and how to advance the change into something better instead of trying to fight it and hold on to the dying status quo
- Romanticising the loss of jobs to technology is little better than complaining about antibiotics putting too many gravediggers out of work. The transfer of labour from humans to our inventions is nothing less than the history of civilisation.
- Educating and retraining a workforce to adapt to change is far more effective than trying to preserve that workforce in some sort of Luddite bubble.
- We aren’t competing against our machines, no matter how many human jobs they can do. We are competing with ourselves to create new challenges and to extend our capabilities and to improve our lives. Inturn these challenges will require even more capable machines and people to build them and train them and maintain them – until we can make machines that do those things to, and the cycle continues.
- If we feel like we are being surpassed by our own technology it’s because we aren’t pushing ourselves hard enough, aren’t being ambitious enough in our goals and dreams. Instead of worrying about what machines can do, we should worry more about what they still cannot do.
- The desire for service wins out over a vague desire for privacy. Technology will continue to make the benefits of sharing our data practically irresistible. Our lives are being converted into data.
- The trend cannot be stoped so what matters more than ever is watching the watchers. The amount of data we produce will continue to expand, largely to our benefit, but we must monitor where it goes and how it is used. Privacy is dying, so transparency must increase.
- Kids thrive and connections and creation and they can be empowered by today’s technology to connect and create in limitless ways. The kids to go to school is it in brace this empowerment most able will thrive. That our classrooms still mostly look like they did 100 years ago isn’t quaint; it’s absurd.
- The world is changing to quickly to teach kids everything they need to know; they must be given the methods and means to teach themselves. This means creative problem-solving, dynamic collaboration online and off, real time research, and the ability to modify and make their own digital tools. They are aided by how far we have come in making powerful technology easily accessible. A room full of kids can assemble their own digital textbooks and syllabus in a few minutes of drag-and-drop on a tablet collaborating from the very start.
- Wealthy nations are approaching education in the same way the wealthy aristocratic family approaches investing. The status quo has been good for a long time; why rock the boat? I have never seen such a conservative mindset in any other sector. Not only in the administrators and bureaucrats but the teachers and parents as well. Everyone except for the kids. The prevailing attitude is that education is too important to take risks. My response is that education is too important not to take risks. We need to find out what works and the only way to do that is to experiment. The kids can handle this. They are already doing it on their own. It’s the adults who are afraid.
- Many jobs will continue to be lost to intelligent automation, but if you’re looking for a field that will be booming for many years, get into human machine collaboration and process architecture and design. This isn’t just user experience, but entirely new ways of bringing machine-human coordination into diverse fields and creating new tools we need in order to do so.
- To keep ahead of the machines, we must not try to slow them down because that slows us down as well. We must speed them up. We must give them, and ourselves, plenty of room to grow. We must go forward, outward, and upward.
- We can never go back to the way it was before. No matter how many people are worried about jobs, or the social structure, or killer machines, we can never go back. It’s against human progress and against human nature. Once tasks can be better done, cheaper, safer, faster, by machines, humans will only ever do them again for recreation or during power outages. Once technology enables us to do certain things we never give them up.
- He ends with a discussion around super intelligence and general AI. And seems to favour an argument that that is some time away, but we have lots of real challenges with the rise of AI in everyday situations today that we have still to grapple with properly.
- This is not a choice between utopia dystopia.It is not a matter of us versus anything else. We will need every bit of our ambition in order to stay ahead of our technology. We are fantastic at teaching our machines how to do our tasks, and we will only get better at it. The only solution is to keep creating new tasks, new missions, new industries that we don’t even know how to do ourselves. We need new frontiers and then we will explore them. Our technology excels at removing the difficulty and uncertainty from our lives, and so we must seek out ever more difficult and uncertain challenges.
Philosophy
- The mind goes beyond reasoning to include perception, feeling, remembering, and, perhaps most distinctively, willing – having and expressing wishes and desires.
- Pablo Picasso “computers are useless. They can only give you answers.“
- Dave Ferrucci “computers do know how to ask questions. They just don’t know which ones are important.”
- To know which questions are the right questions, you have to know what’s important, what matters. And you cannot know that unless you know which outcome is most desirable.
- To become good at anything you have to know how to apply basic principles. To become great at it, you have to know when to violate those principles.
- Larry Tesla says that “intelligence is what ever machines haven’t done yet”
- Joseph Weizenbaum quotes: Machines can decide but they do not choose. Why does the machine do what it does? Every mechanised decision can be traced back – eventually it reaches the inevitable conclusion of “because you told me to”. For humans this is not the case and the new destination is instead “because I chose to“. With in that simple phrase lies human agency, human leadership, human responsibility, and humanity itself.
- Better technology, smarter technology, does not change human nature. It empowers us, for better and for worse. Good people will use it for good. Evil people will use it for evil. That is why we must remember that becoming better humans will always be more important than creating smart machines.
- Kasprov argues that our technology can make us more human by freeing us to be more creative, but there is more to being human then creativity. We have other qualities the machines cannot match. They have instructions while we have purpose. Machines cannot dream. Humans can, and we will need our intelligent machines in order to turn our grandest dreams into reality. If we stop dreaming big dreams, if we stop looking for a greater purpose, then we may as well be machines ourselves.
Psychology, and behaviour and decision making
- Bill Gates “we always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten”
- Leaving your comfort zone involves risk, and when you are doing well the temptation to stick with the status quo can be overwhelming, leading to stagnation
- No matter how much you love the game, you have to hate to lose if you want to stay in top. You have to care, and care deeply
- A simple lack of self confidence results in decision-making that is slower, more conservative, and inferior in quality. Pessimism leads to watch the psychologists called “a heightened sense of potential disappointment in the expected outcome“ of one’s decisions. This leads to indecisiveness and the desire to avoid or postpone consequential decisions.
- Intuition is the product of experience and confidence. It is the ability to act reflexively on knowledge that has been deeply absorbed and understood. Depression or self doubt short-circuits intuition by inhibiting the confidence required to turn that experience into action.
- We rely on assumptions and heuristics to make sense of the complex world around us. We do not calculate every decision by brute force, checking every possible outcome. It is inefficient and unnecessary to do so, because generally we get by pretty well with our assumptions. But when they are isolated by researchers, or exploited by advertisers politicians, and other con artists, you can see how we could all use a little object of oversight, which is where our machines can help us. Not merely by providing the right answers, but by showing us how idiosyncratic and easily influenced our thinking can be. Becoming aware of these fantasies and cognitive blindspot won’t prevent them in entirely, but it’s a big step toward combating them.
- We suffer from similar irrationalities and cognitive delusions at the chessboard as we do in life. We often make impulsive moves when careful analysis refutes our plans. We fall in love with our plans and refuse to admit new evidence against them. We allow confirmation bias to influence us into thinking that what we believe is right, despite what the data may say. We trick ourselves into seeing patterns in randomness and correlations where none exist.
Strategy and Decision Making
- What separates him from other strong players? Experimentation and adaptability. The willingness to take on new challenges, to keep trying new things, different methods and uncomfortable tasks
- Hard work is a talent. The ability to push yourself to keep working, practising, studying more than others is itself a talent.
- Focusing on your strengths is required for peak performance but improving weaknesses has the potential for greatest gains
- Kasparov speaks regularly about the difference between strategy and tactics, and why it’s essential to first understand your long-term goals so you don’t confuse them with reactions, opportunities, or mere milestones. The difficulty of doing this is why even small companies need mission statements and regular checkups to make sure that they are staying on course. Adapting to circumstances is important, but if you change your strategy all the time you don’t really have one. We humans have enough trouble figuring out what we want and how best to achieve it, so it’s no wonder we have trouble getting machines to look at the big picture.
- Computers use an exhaustive search algorithm. Humans use a very different heuristic when making plans. Strategic thinking require setting long-term goals and establishing milestones along the way, leaving aside for the moment how are your opponent, or business or political rivals, might respond. There are no calculations involved yet, only a type of strategic Wish List. Only then do I begin to work out whether it’s actually possible and what my opponent might do to conunter it.
- When it comes to big innovations you have to start earlier. The earlier on in the development tree you look, the bigger the potential for disruption is, and the more work it will take to achieve. If we only rely on our machines to show us how to be good imitators, we will never take the next step to become creative innovators. If everyone imitates, soon there will be nothing new to imitate. Demand can be stimulated by incremental product diversification for only so long. It’s called innovating at the margins.
- While using your phone isn’t cheating in real life, you might develop a cognitive limp from an over reliance on a digital crutch. The goal must be to use these powerful and objective tools not only to do better analysis and make better decisions in the moment, but also to make us better decision-makers.
- Checklists and goalposts are vital to disciplined thinking and strategic planning. We often stop doing these things outside of a rigid work environment, but they are very useful and today’s digital tools make them very easy to maintain
- You have to be brutally honest at objective self-evaluation. If you’re truthful and diligent when collecting data and making your evaluations, you will find you get better and better making correct estimations.
Follow ups to read more on: Oxford Martin School, Nick Bostrom, Ian Goldin, Google’s Peter Norvig, Bridgewater’s Dave Ferrucci and of course Douglas Hofstadder.
