Tag Archives: Artificial Intelligence

Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian, Tom Griffiths

  1. Studying algorithms and how they might be implemented to help us better solve every day problems. Thinking about human cognition and behavior through this computer science lens helps shed light on how we think, why we make the mistakes we make, why and how we have such incredible computational powers, and what rationality really means. We can learn how to make the best decisions given the limited knowledge, time and other resources we have and how to do it with imperfect insights all while dealing with yourself and other messy people. Many problems are intractable but these algorithms will at least give you a jumping off point to begin.
Key Takeaways
  1. Master key algorithm for getting stuff done
    1. Earliest due date and shortest processing time is the master key to determining what to work on and in what order. Work on what has the highest value when importance is divided by completion time. Something must be twice as important if it takes twice as long.
    2. If all you want to do is get through tasks and reduce your to do list, do those things you can accomplish quickest first.  There are many algorithms to follow, it all depends on what your goal is and what you want to maximize.
  2. The Optimal Stopping Problem
    1. These cases you should have two phases: a looking phase where you commit for a certain period of time (usually 1/3 of the total amount of time you’re willing to look) and then a leap phase where you take anything that’s better than what you’ve seen during the look phase
    2. If there is some objective criteria you could set, you can then create a threshold and anyone or anything above the threshold should be accepted
    3. Our time horizon or the intervals of which were looking at strongly determine how much we explore and try new things and how much we exploit – going back to well known favorites. Since the interval determines the strategy we can also determine the strategy from the interval. An overload of sure things such as sequels is a good signal of short-termism.
    4. Optimism is the best solution for regret and we should give people, things, and experiences the benefit of the doubt because we don’t know their upper bound – how good they can be – because we don’t have enough information yet. You should be willing to explore when there’s not enough information to make a reasonable conclusion. However, in real life people tend to over-explore and not know when to lean towards the optimal solution. Win – stay, lose – shift
    5. Older people tend to have fewer social connections but that’s because they have refined over decades the type of people they want to spend time with and that naturally seems to decrease over time. This ties together our explore / exploit phenomenon because younger people who have a longer time frame are more on the explore phase and older people with a more finite time frame are in the exploit phase. As you get older and switch from seeking pleasure from exploitation versus exploring, your quality of life will necessarily improve as you are going back to well-known favorites more often
  3. A | B Testing
    1. Tinkering on an extreme scale is done today by some of the world’s largest companies to see what little tweaks between two options can cause. This iteration is done over millions of times per day so that the product/service/experience is ever improving, at least maximizing what is being measured and sought after. You can use this iteration mindset to make small changes and adjustments to your routine, habits, behaviors, thoughts, and see how it impacts you and others over time
  4. Sorting
    1. Fundamental lesson learned about sorting is that scale hurts.
    2. Simply by breaking tasks or projects down into more manageable units can sorting be reduced by multiples.
    3. However, the first question should be whether it needs to be sorted at all. Efficient sorting which is unnecessary is extremely inefficient and sometimes mess and disorder is the optimal solution
  5. Cache
    1. Keeping around pieces of information that you refer to often or anticipate needing shortly at hand so you can quickly retrieve it
    2. Keep things you use often in close physical proximity so that you can get them quickly
    3. It has been found in many different domains that events that have recently happened are more likely to happen in time and the longer it goes without happening the less likely it is to happen again (Lindy Effect)
  6. Over-Fitting
    1. Over fitting is when we try to use too much data too many factors into making our decisions and they not only make things more complex but actually lead to worse predictions and decisions. If there is high uncertainty and unlimited data, paint with a broad stroke and make it simple. Going into the nitty-gritty only hurts you
    2. It’s better to be approximately right then precisely wrong
  7. Other
    1. Procrastination is often associated with laziness but it can simply be that people lose sight of the important things and are racing through their tasks. They have the right strategy for getting things done but it is the wrong metric – favoring the easy over the meaningful
    2. Be aware of context switching costs. Flow and deep work sometimes takes an hour just to warm up and get into the flow and interrupting people or getting interrupted can ruin hours worth of work or more.
    3. There is a constant tension and trade off between throughput and responsiveness. If you’re too responsive you got nothing done and if you’re throughput is all you’re maximizing you’ll never respond to anyone.
    4. Thrashing is the point when your interrupted so often and have so much to do that you get no actual work done and at this point you can step back and reevaluate and often just do whatever you can get done and not worry about the optimal way to do it.
    5. Batching tasks and having set times to do things such as only looking at emails first thing in the morning and at night is a good way to keep from being interrupted too often
    6. You can become better at predicting by knowing if you’re dealing with power laws or normal distributions and the better information you have of course the better guess you can make. That’s why we are quite good at predicting how much longer a person can live for we know the general lifespan of people
    7. Our predictions tell us a lot about who we are because they’re based on our experiences.
    8. If you can’t explain things simply you don’t understand it well enough
    9. If you can’t solve a problem, relax the constraints and try to solve an easier version of the same problem to see if it gives you any clues or jumping off points for how to solve the real problem
    10. Exponential back off is a technique you can use when things fail or you don’t know how to proceed. For example, if people cancel their plans with you last minute wait a week to reschedule. If they cancel again, wait two weeks. Then four, etc…
    11. The first and only rule of hierarchy is that the hierarchy must be preserved
    12. The innovators dream is not a eureka moment but rather a situation that makes you say, “huh, that’s funny.”
    13. Seek games in which honesty is the ultimate policy and then just be yourself – Vickers Auction – where the winning bid pays only the second highest bid price
    14. Sometimes even the optimal strategy will yield bad outcomes which is why you must focus on process over outcome
    15. Sometimes good enough is simply good enough
What I got out of it
  1. Some good techniques and thought processes for how to make better decisions

Snow Crash by Neal Stephenson

  1. Stephenson weaves virtual reality, Sumerian myth and a strange future in a great thriller
Key Takeaways
  1. Hiro protagonist, TY, Raven, uncle Enzo, Mr. Lee
  2. Hiro delivers pizza for Uncle Enzo but in the “metaverse” he is a warrior prince
  3. A new computer virus is killing hackers all over and his quest is to destroy the villain behind the virus
  4. “Is it a religion, a drug or a virus? What’s the difference?”
  5. There is deep linguistic infrastructure which he to exist for us to be able to acquire languages. There are certain phrases that c an be used to get right to this deeper pet and bypass language. Brain is unable to protect itself in this case and body becomes a slave. Until Enki, first fully conscious and modern man arrived in Sumer and was able to create new phrases which control people. Makes analogy that this language is like a virus, both biologically which stays with the person forever and metaphorically. Reminds me of Jaynes’ Origin of Consciousness
What I got out of it
  1. Interesting read and although strange and futuristic, many parallels to today’s wolr

Humans are Underrated by Geoff Colvin


  1. As technology advances, people shouldn’t focus on beating computers at what they do but rather develop our most essential human abilities and interpersonal experience. The people who can emphasize and foster these skills, especially empathy, will be the most valuable members of our workforce.
Key Takeaways
  1. Many people will lose their jobs due to advancing technology and automation but that frees people up to pursue more “human” jobs and interactions
  2. The changing nature of the economy will shift the valuable sills to those which are more deeply “human” – sensing the thoughts and feelings of others, working productively in groups, building relationships, solving problems together, expressing ourselves with greater power than logic can ever achieve
  3. Computers are getting ever better at certain human abilities such as reading emotions, being creative, and even physical work like driving cars. However, this should not worry people as what we truly desire is a deep interaction with someone. A computer cannot reciprocate emotions, body language, etc. even if it “understands” what you are feeling. Human interaction is an inherent need we have and this holds the key to our value in this changing world
  4. There are certain universal human traits and understanding these will help us figure out how to best serve each other – empathy; people admire generosity and disapprove of stinginess; we all cry and make jokes; we all make music and dance; we all have a concept of fairness and reciprocity; we all have pride; we all tell stories; every society has leaders
  5. People want and need to interact with other people, to look into people’s eyes and read their body language. Interaction jobs are the fastest growing in our economy and having this skill is vital to success in any industry
  6. Rather than ask what computers can’t do, it’s much more useful to ask what people are compelled to do (and they aren’t always rational)
  7. Social networking has shown to make us less happy and satisfied with our lives. The further we get from in-person interactions, the less satisfying and productive it is
  8. Working face-to-face makes people and groups smarter, more productive, efficient and collaborative.
  9. Era of Empathy – Empathy is the foundation of all other abilities that increasingly make people valuable as technology advances. It means discerning what some other person is thinking and feeling and responding in some appropriate way. Computers, even if they “understand” our emotions through facial recognition, cannot reciprocate and empathize with us. Increased use of social media has shown to decrease empathy. Always make building relationships your top priority in any interaction. This mindset will never steer your wrong on any business or social setting
  10. Building relationships can be broken down into three parts – relationship establishment, development and engagement
  11. To build empathy in kids, read aloud to them, let them play on their own and do as much role playing as possible
  12. When somebody comes to talk to you about something difficult, never say “I understand.”
  13. In order to improve performance in any realm, you must measure everything, make the practice as real as possible and immediately review the results. You must often be brutally honest with feedback in order for people to learn as quickly and effectively as possible. The more information we get, the better decisions we can make, we can better understand and remember why something worked well or didn’t work and leads to higher motivation since they are more engaged
    1. The army, navy, air force example is amazing. The After-Action Review (AAR) literally changed the way these people train their soldiers. The margin of improvement was 5x! in an era where 5% improvement was good
  14. Technology is much less influential than the people using it (Navy, Air Force example where their way superior planes weren’t beating the Russians and Vietnamese)
  15. The good news for many people is that interpersonal skills can be learned and empathy is like any other muscle which must be “exercised” to grow
  16. After Action Review
    1. It happens immediately after the event or sometimes even during the event
    2. Everyone is involved
    3. The discussion stays focused on the issue of how well the exercise achieved its objective. What was supposed to happen and did we do it?
    4. Assess performance of everyone involved – soldiers, leaders and the group as a whole
    5. Not to assign a grade but to identify specific strengths and weaknesses that will guide future training
    6. The discussion must be brutally honest – absolute candor
  17. How you deliver a message is just as important as the message itself
  18. Paul Azinger was charged with putting together an American team for the Ryder Cup without Tiger Woods. He took a different approach and decided to group similar personality types together. Social people with social people, aggressive players with aggressive players, etc. Also, he broke the 16 man team into 4 groups which allowed the players to get to know one another more intimately. This had great success as the players were closer-knit and they ended up beating the Europeans even without Tiger
  19. The effectiveness of a group correlates highly with the social sensitivity of that group and also the number of women on it. Women are inherently more empathetic and socially sensitive than men and this will be very valuable moving forward. The number one factor in making a group effective is skill at deep human interaction. Great groups iterate a lot of ideas, interact about equally and offered both their own ideas and responding to others. Two other very important traits for a productive group is cooperativeness and generosity
  20. Generally judge and assess people’s trustworthiness in less than 1/10th of 1 second
  21. Storytelling is incredibly human and will become ever more important. The storyteller and listener’s brains align and they become connected in a very deep way
  22. Seeing stories in random events is much easier for us than not seeing stories
  23. People absolutely love happy endings and the “classic” hero structure – normal guy, issue, defeats issue and goes back to normal but is somehow changed for the better
  24. While computers are getting ever better at being creative (cooking, music, etc.) people need and love having somebody to connect with that creativity
  25. The most creative and productive groups split their time between exploring and engaging. Also, more trust lead to more creative and higher quality ideas. Groups of 2 can trust others the way larger groups often can’t and is why we often see such productivity from two people. more ideas and better judgment is what makes groups better
  26. Proximity of groups is also extremely important. Proximity leads to better communication which leads to more creativity
  27. Intrinsic motivation stimulates creativity much better than does extrinsic motivation
  28. Women are better at Reading the Mind in the Eye (RME) test. Women are empathizing whereas men are systemizing and in this world the women have a big advantage
  29. Eliminate competing for status in any group if you want them to be successful
  30. Speaks about how infotech can be utilized to built empathy and understanding others feelings through virtual reality training and other software programs
What I got out of it
  1. Really interesting read. Although technology will eliminate many jobs, what people innately desire, deep human interaction, will never disappear and will make people with empathy and are good socially ever more valuable

Rise of the Robots by Martin Ford


  1. Our Goldilocks period has reached its end, and the American economy is moving into a new era. It is an era that will be defined by a fundamental shift in the relationship between workers and machines. That shift will ultimately challenge one of our most basic assumptions about technology: that machines are tools that increase the productivity of workers. Instead, machines themselves are turning into workers, and the line between the capability of labor and capital is blurring as never before.
Key Takeaways
  1. While lower-skill occupations will no doubt continue to be affected, a great many college-educated, white-collar workers are going to discover that their jobs, too, are squarely in the sights as software automation and predictive algorithms advance rapidly in capability.
  2. The fact is that “routine” may not be the best word to describe the jobs most likely to be threatened by technology. A more accurate term might be “predictable.”
  3. The virtuous feedback loop between productivity, rising wages, and increasing consumer spending will collapse. That positive feedback effect is already seriously diminished: we face soaring inequality not just in income but also in consumption.
  4. The question I will ask in this book is bigger: Can accelerating technology disrupt our entire system to the point where a fundamental restructuring may be required if prosperity is to continue?
  5. Manufacturing jobs in the United States currently account for well under 10 percent of total employment. As a result, manufacturing robots and reshoring are likely to have a fairly marginal impact on the overall job market. The story will be very different in developing countries like China, where employment is far more focused in the manufacturing sector.
  6. In the United States and other advanced economies, the major disruption will be in the service sector—which is, after all, where the vast majority of workers are now employed. This trend is already evident in areas like ATMs and self-service checkout lanes, but the next decade is likely to see an explosion of new forms of service sector automation, potentially putting millions of relatively low-wage jobs at risk.
  7. Once one of the industry’s major players begins to gain significant advantages from increased automation, the others will have little choice but to follow suit.
  8. The third major force likely to disrupt employment in the retail sector will be the introduction of increased automation and robotics into stores as brick and mortar retailers strive to remain competitive.
  9. Seven Deadly – Stagnant Wages, “Bowley’s Law,” Labor Force Participation, Diminishing Job Creation, Lengthening Jobless Recoveries, and Soaring Long-Term Unemployment,
  10. the problem is not that more jobs are being destroyed in downturns; it is that fewer are being created during recoveries.
  11. Routine jobs are eliminated for economic reasons during a recession, but organizations then discover that ever-advancing information technology allows them to operate successfully without rehiring the workers once a recovery gets under way.
  12. The main idea behind comparative advantage is that you should always be able to find a job, provided you specialize in the thing at which you are “least bad” relative to other people.
  13. Continued progress depends on a vibrant market for future innovations—and that, in turn, requires a reasonable distribution of purchasing power.
  14. Deep learning systems already power the speech recognition capability in Apple’s Siri and are poised to accelerate progress in a broad range of applications that rely on pattern analysis and recognition.
  15. In some cases, however, computers are pushing even further and beginning to encroach into areas that nearly everyone assumes are the exclusive province of the human mind: machines are starting to demonstrate curiosity and creativity.
  16. Blinder has conducted a number of surveys aimed at assessing the future impact of offshoring and has estimated that 30–40 million US jobs—positions employing roughly a quarter of the workforce—are potentially offshorable.
  17. One factor that is, I think, underappreciated is the extent to which advances in artificial intelligence as well as the big data revolution may act as a kind of catalyst, making a much broader range of high-skill jobs potentially offshorable.
  18. The jobs of the future will involve collaborating with the machines.
  19. Advising workers that they should learn to “race with the machines”—rather than against them
  20. Human-machine collaboration, rather than full automation, will come to dominate the workplaces of the future.
  21. One of the most important lessons of history is that there is a powerful symbiosis between technological progress and a well-functioning market economy. Healthy markets create the incentives that lead to meaningful innovation and ever-increasing productivity, and this has been the driving force behind our prosperity.
  22. The biggest disruption of all could come when 3D printers are scaled up to construction size. Behrokh Khoshnevis, an engineering professor at the University of Southern California, is building a massive 3D printer capable of fabricating a house in just twenty-four hours.
  23. I think that commercial fleets could be one of the first places where we see widespread adoption of automated vehicles.
  24. The primary message this book has delivered so far is that accelerating technology is likely to increasingly threaten jobs across industries and at a wide range of skill levels.
  25. In virtually every industry sector that caters directly to American consumers—from home appliances to restaurants and hotels to retail stores—the mid-range is struggling with stagnant or declining sales, while companies that target top-tier consumers continue to thrive.
  26. Even if China does succeed in rebalancing its economy toward domestic consumption, it seems optimistic to expect that the country’s consumer markets will be fully open to foreign companies.
  27. It is not at all clear how the poorest countries in Asia and Africa will manage to dramatically improve their prospects in a world that no longer needs untold millions of low-wage factory workers.
  28. Overall, about 20 percent of US college graduates are considered overeducated for their current occupation, and average incomes for new college graduates have been in decline for more than a decade. The result very often is credential inflation; many occupations that once required only a high school diploma are now open only to those with a four-year college degree, the master’s becomes the new bachelor’s, and degrees from nonelite schools are devalued.
  29. A basic, or guaranteed minimum, income is far from a new idea. In the context of the contemporary American political landscape, a guaranteed income is likely to be disparaged as “socialism” and a massive expansion of the welfare state.
  30. The most important factor in designing a workable guaranteed income scheme is getting the incentives right. The objective should be to provide a universal safety net as well as a supplement to low incomes—but without creating a disincentive to work and to be as productive as possible. The income provided should be relatively minimal: enough to get by, but not enough to be especially comfortable. There is also a strong argument for initially setting the income level even lower than this and then gradually increasing it over time after studying the impact of the program on the workforce.
  31. There are two general approaches to implementing a guaranteed income. An unconditional basic income is paid to every adult citizen regardless of other income sources. Guaranteed minimum incomes (and other variations, such as a negative income tax) are paid only to people at the bottom of the income distribution and are phased out as other income sources rise. While the second alternative is obviously less expensive, it carries with it the danger of disastrous perverse incentives. If the guaranteed income is means-tested at relatively low income levels, recipients will see an effective tax rate on any further earnings that can reach confiscatory levels. In other words, they can fall into a “poverty trap” where there is little or no benefit to working harder.
  32. In general, I think the fact that some people would elect to work less—or perhaps even not at all—should not be viewed in universally negative terms.
  33. A basic income program might help revitalize many of the small towns and rural areas that are losing population because jobs have evaporated.
  34. “47 percent” (the fraction of the population who currently pay no federal income tax).
  35. Rather than simply raising taxes across the board or on the highest existing tax bracket, a better strategy would be to introduce several new higher tax brackets designed to capture more revenue from those taxpayers with very high incomes—perhaps a million or more dollars per year
  36. Foremost among these policies is the critical need for the United States to invest in public infrastructure. There is an enormous pent-up requirement to repair and refurbish things like roads, bridges, schools, and airports.
What I got out of it
  1. Really interesting take on the future of jobs as it relates to automation and advancing technology. It is interesting to compare Colvin’s Humans are Underrated to this. I don’t think they’re that different but Colvin is much more upbeat about it.