artifical intelligence · Big data · Business Culture · decision making · Investment · Learning · Maths · Statistics

The unrules by Igor Tulchinsky, founder and CEO of WorldQuant

Igor’s rules

  1. The UnRule: all theories and all methods have flaws. Nothing can be proved with absolute certainty is, but anything may be disproved, and nothing that can be articulated can be perfect.
  2. You only live once. Your time on earth is the only truly irreplaceable resource. If today was my last day, what would I be doing with it?
  3. Life is unpredictable. There are limits to planning; the key is to act. Foster opportunities, then take advantage of outcomes. If you have to decide and you can’t, flip a coin. If it’s the wrong action, you will feel it and reverse course. Actions have a compounding effect; it’s bad to deliberate for too long.
  4. Establish concrete quantifiable goals and always go from A to B. Concrete things are attainable. Abstract and nebulous wishes are not.
  5. Develop willpower and persist. The most important limit is how much ability and persistence you have. Age means little.
  6. Play to your strengths, don’t compromise. Weaknesses can only be improved marginally, but strength can be improved more.
  7. Obstacles are information. If you can’t get something to work there is a reason. Learn adjust and attack it again.
  8. Aim for the anxious edge, the point of mild anxiety
  9. Arrogance distorts reality. Arrogance makes you perceive the environment in the way that maximises your ego. Environment does not exist for you, so your perceptions turn into fiction. You make bad decisions by chasing illusions. This gets harder after success when hubris slips in.
  10. Make everyone benefit
  11. Opportunity is unlimited, ideas are infinite
  12. Blame no one else. Minimise regrets.
  13. There is a virtue in economy of expression. Efficiency implies clarity and economy of thought. Pretend you have a fixed number of words in your life. The sooner they are all said, the sooner you’ll die.
  14. Value diverse and competing methods. Because all theories are flawed, the best approach is to collect as many of them as possible and use them all, in as optimal a fashion as you can devise, simultaneously.
  15. Value multiple points of view.
  16. Make everyone benefit. Align your endeavours with everyone around you and you will create your own tail wind.

Quotes and other insights

  1. To be successful in this investment business you have to think about it all the time. Thomas Peterffy
  2. Keep losses small. Profits will take care of themselves. Izzy Englander
  1. Don’t get emotional about your trades. React instantly to bad news. If it’s scary run. Take aggressive risks but manage losses. Aggressive behaviour forces your environment to react to you, rather than the other way around. You’re in control; you have the wider array of options in a higher probability of success. You need an exit route if it doesn’t work out.
  2. In systems with a high degree of interactive complexity, multiple and unexpected interactions of failure are inevitable.
  3. A good business runs itself. And create this by choosing the right people. A lot of time should be invested in that activity. Optimal compensation schemes are vital.
  4. Minimise bureaucracy. Time is money; time is scarce. Bureaucracy wastes time and money. If you have the right people, right systems and the right compensation scheme you can scale without adding bureaucracy.
  5. What makes a good trader? Intelligence, focus, action orientation, and the ability to learn from errors; economy of words and thoughts, honesty, and a strong sense of self; the ability to take risks, compartmentalise, and handle setbacks without ego getting crushed.
  6. What makes a good researcher? Creativity, tenacity, attention to detail, intelligence, relentlessness, follow-through, and top-level programming skills.
  7. What makes a good manager? Empathy, intelligence, creativity, relentlessness, and follow through.
  8. In their view, quantity of alphas is far superior to quality. Quality cannot easily be defined. They seek to maximise exponentially the number of Alphas they pursue.
  9. If data increases exponentially, predictability should improve linearly.
  10. They key to testing ideas is to have good simulation software.
  11. As complexity increases so will the number and frequency of non linear events will also increase (ie many std dev events – rogue waves, schrodinger equation)
  12. Power laws very common in nature. In some systems the largest entity often brakes scale invariance, ie. it is even bigger than predicted eg. In network systems, dominant player much bigger.

WorldQuant online university in financial literacy worth checking out.

artifical intelligence · Culture · decision making · Learning · Philosophy · politics · Psychology

21 lessons for the 21st century by Yuval Noah Harari

  • The book picks up on several themes that I think are very important for understanding where the world is trending over the coming years.

    Politics

    • Disillusionment picks up on the rise of anti ellitest autocratic and populist rulers (connections to The Demise of Western Liberalism by Edward Luce).
    • Issues of identity, nationalism clash with global problems. Identity and the definition of your tribe are themselves changing rapidly in today’s world.
    • Immigration also poses growing challenges in many parts of the world, both to the countries from which people are departing and those to which they are aiming to immigrate to.
    • Traditional democracy offers no solutions to the global technological disruption and ecological challenges we are facing.
    • All the existing human tribes are absorbed in advancing their particular interests rather than understanding the global truth.
  • Many are writing about the potential impact of AI on jobs in future (connections to Deep Thinking by Gary Kasparov). Yuval draws out some interesting insights:
    • In the past machines competed with humans in raw physical abilities, while humans retained an immense edge over machines in cognition. AI has the potential to change that.
    • In the future machines will become better at analysing human behaviour and predicting human decisions. (Already happening with social media’s ability to draw and captivate us). AI May out compete us in jobs that require intuition about other people, it may be able to more accurately assess people’s emotional states.
    • AI gets its power and ability to outcompete us not from replacing a single human but through integrating the experience of millions in a single network. AI cars will have far more driving experience than any human. AI doctors similarly. Healthcare could become far better and far cheaper.
    • What jobs will be more immune from relegation? Jobs that require a wide range of skills and an ability to deal with unforeseen scenarios. Human care for young, sick and elderly will probably remain a human activity. Human creativity is often lauded as the area AI will least impact but there he argues as AIs get to understand what touches human emotion they will start to impact this.
    • The idea of human being augmented by machines in all of these areas will inevitably be correct, hopefully greatly improving productivity but continuing the acceleration of change.
    • What do we do to try to create enough new jobs? Will governments create effective retraining programs? How will we cope with the psychological challenges of having to retrain multiple times in our careers?
    • And what happens if job losses far outstrip job creation? What if we get to the point where a large portion of society just don’t have much of a relevant role to play in the work that is economically valued and paid for?
    • What sort of changing social policies will we need eg. Universal Basic Income and what sort of tax policies if the value creation is owned by a few large data owning corporations?
    • Will we start recognising the enormous value of jobs that are not currently paid for such as careers and parenting?
    • Can we envisage a society where work is not where most people find their meaning and purpose? How will we pay for that?
    • Human happiness depends less on objective conditions and more on our own expectations, and how we compare our condition to those of other people. How will we adjust our expectations in this new world.

    The other big questions he raises

    • How do we regulate the rise of big data and protect freedoms, who owns the data (see Kasparov’s comments about us sacrificing our privacy for service willingly, and the need for transparency from the big data owners)
    • What does terrorism look like in future?
  • On spirituality, ethics, secularism and religion
    • The future of spirituality, our concept of God, the contradictions between religions preaching individual humility but exercising collective arrogance in its exclusive demands. Marrying this with secularism and science, a seeking of objective truth, the development of secular ethics around concepts such as compassion, equality, freedom, courage.
    • “Questions you cannot answer are usually far better than answers you cannot question.”
    • But even secular movements repeatedly mutate into dogmatic creeds, especially in times of war or economic crisis where societies must act promptly and forcefully. Eg. communism’s of capitalism both become dogmas. Even the right to freedom can become a dogma against all censorship. At some point in time a search for objective truth is circumvented by the desire for expediency and simplicity.
    • “Every religion, ideology and creed has its shadow, and no matter which creed you follow you should acknowledge your shadow and avoid the naïve reassurance that ‘it cannot happen to us’.”
  • On truth and power
    • Ignorance: you know less than you think. “People rearely appreciate their ignorance, because they lock themselves inside an echo chamber of like minded friends and self confirming news feeds, where their beliefs are constantly reinforced and seldom challenged.
    • Providing people with more and better information is unlikely to improve matters. Most of our views are shaped by communal groupthink rather than individual rationality, and we hold these views out of group loyalty. Bombarding people with facts and exposing their individual ignorance is likely to backfire.
    • “If you want to go deeply into any subject you need a lot of time, and in particular the privilege of wasting time. You need to experiment with unproductive paths, to explore dead ends, to make space for doubts and boredom, and to allow little seeds of insight to slowly grow and blossom. If you cannot afford to waste time you will never find the truth.”
    • Power inevitably distorts the truth. Power is all about changing reality rather than seeing it for what it is.
    • Power depends on creating and believing fictions. We are the only mammals that can cooperate with numerous strangers because only we can invent fictional stories, spread them around, and convince millions of others to believe in them. As long as everybody believes in the same fictions, we all obey the same laws, and can thereby cooperate effectively.
    • For better or worse, fiction is among the most effective tools in humanity’s toolkit. By bringing people together religious and cultural creeds make large scale human cooperation possible. The power of human cooperation depends on a delicate balance between truth and fiction.
    • As a species, humans prefer power to truth. We spend far more time and effort on trying to control the world than on trying to understand it – and even when we try to understand it, we usually do so in the hope that understanding the world will make it easier to control it.
    • How to avoid fake news? If you want reliable information, pay for it. If some issue seems exceptionally important to you, make the effort to read the scientific literature on it.
  • On education
    • You will need to reinvent yourself again and again in order to keep up with the world.
      To survive and flourish in such a world you will need a lot of mental flexibility and great reserves of emotional balance. Unfortunately teaching kids to embrace the unknown and keep their mental balance is far more difficult than teaching them a physics equation.
      People don’t need more information, they need the ability to make sense of the information, to tell the difference between the important and the unimportant and to combine many bits of information into a broad picture of the world.
      What should we teach: critical thinking, communication, collaboration and creativity
      To do this you need to work hard on knowing who you are, and what you want from life, know thy self.
  • How do we usually get to know ourselves? The power of stories
    • We usually do this by telling ourselves stories to give meaning to our lives. My story must give me a role to play, and it must extend beyond my horizon, giving me an identity and a meaning to my life by embedding me in something bigger than myself.
      However when you believe a particular story, it makes you extremely interested in its minutest details, while keeping you blind to anything that falls outside its scope.
      Often we want our personal story to carry on beyond death, either through religious reassurance or through something tangible in either cultural or biological form.
      Why do people believe in these fictions? One reason is that their personal identity is built on the story. By the time their intellect matures they are so heavily invested in the story, that they are far more likely to use their intellect to rationalise the story than to doubt it. Most people who go on identity quests are like children going treasure hunting. They find only what their parents have hidden for them in advance. Second, not only our personal identities but also our collective institutions are built on the story. Once personal identities and entire social systems are built on top of the story, it becomes unthinkable to doubt it, because its collapse will trigger a personal and social cataclysm. Once you suffer for a story it’s usually enough to convince you that the story is real. And in following our own story we may even inflict suffering on others. We do not want to admit either that we are fools or villains and so we prefer to believe that the story is true.
      Throughout history almost all humans believed in several stories at the same time, and whenever absolutely convinced of the truth of any one of them. This uncertainty rattled most religions, which therefore considered faith to be a cardinal virtue and doubt to be amongst the worst possible sins. With the rise of modern culture the tables were turned. Faith looked increasingly like mental slavery, while doubt came to be seen as a precondition for freedom.
      Modernity didn’t reject the plethora of stories it inherited from the past. Instead, it opened a supermarket for them. The modern human is free to sample them all, choosing and combining what ever fits his or her taste.
      One common modern story is the Liberal story. Like all of the cosmic stories, the liberal story to start with a creation narrative. It says that the creation occurs every moment, and I am the creator. What then is the aim of my life? To create meaning by feeling, by thinking, by desiring, and by inventing. Anything that limits the human liberty to feel, to think, to desire and to invent, limits the meaning of the universe. Hence liberty from such limitations is the supreme ideal.
      In order to understand ourselves, a crucial step is to acknowledge that the ‘self’ is a fictional story that the intricate mechanisms of our mind constantly manufacture, update and re-write. There is a storyteller in my mind that explains who I am, where I am coming from, where I am heading to, and what is happening right now. And like government Spin Doctors, the inner narrator repeatedly gets things wrong but rarely, if ever, admits it. My inner propaganda machine builds up a personal myth, with prized memories and cherished traumas that often bear little resemblance to the truth.
      We humans have conquered the world thanks to ability to create and believe fictional stories. We are therefore particularly bad at knowing the difference between fiction and reality. Overlooking this difference has been a matter of survival for us.
  • Philosophy and the final frontier: our minds
    • In Yuval’s view the big question facing humans is not “what is the meaning of life?” But “how do we get out of suffering?” (Vs Victor Frankl who looks to find meaning even in suffering). He believes “suffering is the most real thing in the world”.
      He goes on to discuss how he can, as a sceptic still wake up cheerful in the morning.
      He turns inward on himself in mindfulness meditation.
      How does one study the mind? The only mind I can directly observe is my own. If I cannot observe some external thing without bias, how can I objectively observe my own mind? But the only tool available is meditation: the direct observation of one’s own mind.
      “The most important thing I realised was that the deepest source of my suffering is in the patterns of my own mind. When I want something and it doesn’t happen, my mind reacts by generating suffering. Suffering is not an objective condition in the outside world. It is a mental reaction generated by my own mind. Learning this is the first step towards ceasing to generate more suffering.”
      Serious meditation demanded minutes amount of discipline. If you try to objectively observe your sensations, the first thing you notice is how wild and impatient reminders.
      We had better understand our minds before the algorithms make our minds up for us.
    Business culture · decision making · Learning · Philosophy

    Deep Work by Cal Newport

  • The basic idea behind this book is that in an age of increasing distraction, being able to really concentrate and do deep focused work is a super-power. He spends the first half of the book explaining why he believes this is the case and the second half offering some really pragmatic strategies for achieving this.

    Deep work is completely undistracted, focused problem solving, in a state of “flow”, where we do our most meaningful work. We can only really achieve this for between 1 and at most four hours a day. But very few of us achieve even the one hour, true deep work is rare. Mos to the time spent responding to emails, in meetings etc. Is not facilitating deep work. Most of us proxy business for deep work, they are not the same thing.

    His key insight is: developing a deep work habit is to move beyond good intentions and add routines and rituals to your working life design to minimise the amount of your limited willpower necessary to transition into and maintain a state of unbroken concentration.

    He sets out 4 depth philosophy’s

    1. Become a monk. Set your entire life up to minise distraction and do only deep work

    2. Become a monk some of the time: A bimodal philosphy where for parts of the year you are able to become completely isolated and work intensely

    3. Have a rhythmic schedule to doing deep work every week, clear well defined periods where you will be uninterrupted – this is probably the most practical for most of us

    4. Journalistic approach, jumpy into deep work with every spare minute of time, as journalists are trained to do because they often work to tight deadlines. The main challenge here is the context switching which makes getting into a deep work mindset very challenging.

    He then has a series of very practical suggestions to maximise your deep work and its impact.

    Ritualise your deep work

    • Have a specific place to do deep work
    • Decide for how long you will do it, and don’t be over ambitious to begin with
    • Decide how you will work eg. Ban internet and email completely, have a cup of coffee before hand
    • Keep track of how much time you actually do it, in a clear visible place eg. On a calendar, see if you can build up a habit of tracking and expanding the time you do deep work
    • Commit to it with grand gestures eg. Money, time commitment, public commitment, stuff that will make you more psychologically committed to achieving it.

    Interestingly he is not saying it has to be in complete isolation. There are many examples of good collaboration producing meaningful work and often improving the quality of thinking but this probably comes through an approach of coming together meaningfully and then separating out meaningfully again.

    Don’t just know what you need to do, also focus on how you will execute.

    • Focus on the wildly important. Identify a small number of ambitious outcomes to pursue with your deep work don’t try to do too much.
    • Focus on lead measures, not the results. Lead measures are the things that you can control that drive success that create the output eg. The time you spend on deep work.
    • Keep a scoreboard
    • Create a cadence of accountability: confront the scoreboard, with a team eg. A weekly review, identify when it went well and when it went poorly why and what could be done to improve it.

    He also emphasise the need to create mental space around the deep work. When you work, work hard, when you are done be done.

    • Down time aids insights, give you unconscious mind time to untangle more complex problems
    • We suffer from Attention fatigue. Having walks especially in nature very helpful. Exercise probably has a similar effect, Having “inherently fascinating stimuli” that fascinate the mind but do not tax it in terms of directed concentration and decision making is very restorative to the mind
    • Have a shutdown ritual: as you complete your work day, identify incomplete tasks, capture them where you can and let you brain know that you have a plan for how to complete it, and then ritualise leaving your work behind you and switching off to it.
    • Embrace boredom and specifically here, don’t fill it up with constant stimuli, overcome our desire for constant distraction. People who multitask all the time cannot filter out irrelevancy. We are wired for distraction and crave it, more so in the social media age. His specific recommendation here is to “schedule the occasional break from focus to give into distraction” rather than let distraction be the default in our down time. Eg. Schedule when you watch Tv or browse the internet or check the news.

    Other suggestions

    • Work with intensity like Teddy Roosevelt: schedule high intensity work and give yourself a drastically shorter hard deadline than you would ordinarily give yourself to get the task done, though it must still be feasible. Do this only once a week to begin with and then systematically increase it.
    • Productive meditation: take a period when you are occupied physically but not mentally eg. Walking, showering, exercising, and focus your attention singularly on a well defined problem you are working on, and specifically what part of it you need to think through next. When your mind wanders away from it bring your attention back to it.

    He then makes various suggestions to limit the impact and time spent on shallow work or not important goals

    • Select the tools (specifically networking and digital information tools) that you use very carefully to maximise your chances of success at your key goals. Identify your key goals and the factors that will determine success and adopt a tool only if its positive impacts substantially outweigh the negative.
    • 80 % of your productivity comes from 20 % of your activity/tools etc. Cut out the other 80 % ruthlessly to allow more time on the 20 % that makes the biggest difference. Eg. Cut out social media

    Manage your schedule ruthlessly

    • Put more thought and structure into your leisure time evenings and weekends.
    • Schedule every minute of every day. That does not mean you have to stick to the schedule, if something else comes up that is more important, change the schedule but it forces you to be thoughtful about the day and how you are spending your time. Including scheduling time for the admin and the unexpected. This also helps improve your realism about how long different tasks take.
    • Quantify the depth of every task (how long would this task take you to teach someone else to do?)
    • Set your self very strict work time allowances and a fixed time by which you need to have finished your work day eg. 8 hours a day, finished by 5:30, once everyone has less time to get their work done they respect that time even more, people become stingy with their time and don’t waste it doing things that just don’t matter.
    • Decide what percentage of your time should be spent on shallow work vs deep work and get your boss to agree that.
    • This changes perspective:any obligation beyond your deep work objectives is potentially disruptive.

    Manage other people’s demands on your time

    • The most dangerous word in managing your productivity is saying “yes”
    • Become hard to reach
    • Manage your email
    • eg. On email train people not to expect a response and have people filter out what they send you themselves and what sort of response to expect from you.
    artifical intelligence · Computer Science · decision making · Learning · Philosophy · Psychology

    Deep Thinking by Garry Kasparov

    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.