Notes from Average is Over by Tyler Cowen

Notes and thoughts on this thought provoking, and motivating, book:

• “This book is far from all good news.”
• Two jobs in the future: Are you working with computers, or can they replace you.
• Foxconn to increase the number of robots in its factories one hundred fold, getting them to one million robots.
• “There is not a joke that ‘a modern textile mill employs only a man and a dog – the man to feed the dog, and the dog to keep the man away from the machines.'”
• If machines can correctly gage the pulse of a people and its climate, will there be a need to vote in the future? This can, in fact, be done currently. With a few calculations based on a few variables like GDP and unemployment rate and inflation we can predict elections we’ll. Does this change one’s perception of machines? Or is this a denial of a small moment of the human experience?
• Would you hand over you identity for 20% off laundry detergent?
• Regulatory obstacles will be greatest for health care and pharmaceutical companies – much less so for companies like Apple, Google, and Amazon. The big question is how will society adjust for the failures of technology. How will we react when machines cause harm, rather than people.
• Tevhnology will help us make things more cheaply. This means there will be excess value left over. Where will it go? Quality land. IP. And quality labor.
• Technology in many instance many will create more jobs. When a problem is solved, or automated, new ones arise. However, new, highly skilled labor is required to fill those jobs. Unmanned drones may replace a pilot, but requires 300 people working in the background; whereas a fighter pilot requires 100.
• An overlap of having the ability to solve real-world problems and some technical knowhow is key today.
• Not all STEM graduates will be ready for the market. “Does anyone envy the job prospects of a newly minted astronomy PhD?”
• The world is getting better at measuring value. Average effort and average results will no longer be tolerated. Only quality will matter. Productivity will matter most.
• Will any of this lead to happiness?
• As grows the need for quality talent, so does the need for quality management. More hires means the need for more people to manage the team. The more efficient they can make the team, the higher their earning power. The greater the care in building the teams, the better the output.
• Women are more prepared for the new workplace. They’re more conscientious and exact and rarely hold resentment.
• Showing up is no longer enough.
• The author does not think the middle class is shrinking. He wonders how much of the middle class is made up of government workers; people who don’t actually produce nearly as much as they’re paid. How will this affect the job market? On the one hand you have efficient organizations, moving the advancement needle to its edge, and in the other is one that rewards inefficiencies and failure, but is too growing wildly.
• “From June 2009 (the official end of the recession) to June 2011, inflation-adjusted median household income fell 6.7 percent, more rapidly than it fell during the recession itself (3.2 percent). Median income in 2011 was more than 8 percent lower than in 2007 and indeed median household income peaked in 1999.”
• If the need for higher and higher skilled labor grows, what does this mean for people who are already highly skilled? Is the current workforce at Google already behind? Maybe not. This is just how people move into positions of management and mentorship and guidance and leadership. These skills will always be in need.
• There is a lot of focus on technical jobs as being high paying, but financial companies, with the help of the government, have grown massively large and can afford the Take larger risks; and pay higher and higher salaries.
• Unfortunately technology industry is filling with people who are after money rather that technological innovation.
• The age at which people make achievements is moving up. Twenty year olds use to prove mathematical theorems. Now it’s the thirty year olds. As problems get harder and harder, the need for experience and wisdom increases. There is no longer the advantage of starting from scratch.
• There is still demand for people with high, general intelligence. People who picked the hyper path of Harvard or Yale. Even though they offer little interns of productivity and knowledge or even what is required to advance an organization, there is still a fear based need for such people. We glamorize these people, even though if we were to set aside their degrees, we would have idea what to do with these people.
• There are few, if any, problems that are at the early stages. There was such a computing boom because we were starting fresh, from the ground up. This is not the case anymore. Now you need to know so much more, even when just starting out, to be even considered at zero.
• Computers are good at chess because it is easy to solve for. Computers are decision machines and chess is about whittling down decisions. Whereas creating a vision for an organization and driving that vision needs human interaction. This is uplifting because if computers can take over areas humans have no need to run, then they can focus on being more human like.
• Men are being driven out of the workforce at an alarming rate.
• There are large numbers of people who actively avoid the work market simply because it does not suit them. Ten years ago 5 million people received disability benefits. Now it’s 8.2 million. The workplace is safer than ever, so what is the cause of this increase.
• “For men, from 1969 to 2009, as measured, it appears that wages for the typical or median male earner have fallen by about 28 percent.” This is during time of unprecedented economic growth.
• Three quarters of people aged between seventeen and twenty four are unfit to serve in the military. This is even the military continually lowering its standards.
• The housing crash forced companies to fire off large chunks of their workforce. It ended up improving output because the weakest workers went first, and they never hired them back because the efficiency is now so high. When was the last time the government had a substantial layoff? Where TARP was a bailout of the banks, are government jobs bailouts for citizens?
• Young workers will slowly be reemployed, but it will be at lower and lower salaries.
• The new healthcare plan and increased minimum wage drastically slow hiring. Both make hiring more expensive than it’s worth. Companies cannot keep up with the rising costs of healthcare or minimum wage, so they just expect more from the people they have. And as it’s turning out, good workers can pull more than their weight.
• The newly self-employed averages around 500k a year. This is not because people are energized to enterprise, but rather they may have no choice.
• Is the life of a food truck owner a sign of the reversal of the American Dream? Certainly people don’t do it for the lifestyle, and most definitely not for the riches, of which there are none. This appears to be more like life in developing nations.
• Are service sites like fiver good or bad? Are people so desperate for work they’ll take any random job, like retrieving keys from a garbage disposal, they can find?
• We are computers. Or, rather, work in cahoots with a computer. You have the option to use yourself when, say, preparing for an interview or a sales call. Or you can use a computer for an edge or advantage; spending some time researching an industry or new sales tactics or a potential client.
• Grandmaster chess players can’t beat even average or club level players who use computing systems for help because they rely too much on mastery and intuition.
• Takeaways so far:
1. Human-computer teams are the best teams.
2. You don’t need to be an expert to work along side a machine.
3. Jobs that are not critical will be less effective if given to a human.
4. Know your limit.
• It’s not that dating algorithms are good at matching people, but rather they’re good and getting people to get together, and that’s all it really takes. A conservative is more likely to message a liberal, than visa-versa; so the algorithm will display liberals to conservatives, but less so the other way around.
• Even grandmaster chess players don’t make the same, recommended moves as computers because it is hard to be objective, to stay focused, and, of course, to calculate the large number of move variations.
• Will computers make people more humble? Take chess, for example. Computers outperform even grandmasters to such a degree that their command for respect has greatly lessened. It’s not that computer are more intelligent, it’s that they’re great at making decisions. This lessens or reveals achievements more for what it is; something anyone can do and not all that exceptional. So, there seems to be little difference between good chess players and great ones.
• GPS is responsible for hundreds of thousands of accidents; hard to verify. If true, what does this say about technological solutions? Is it the human element? Are people distracted by the machine? Are they foolishly stopping on train tracks when instructed?
• Because business want to save money, we’ll be in situations where we’ll be picking up the slack. Ever have to navigate your way through a customer-support phone tree? That’s in place to save the company money. They’ve outsourced the work to you. We may see more of this type of outsourcing. Simplifying your life will be ways around this. E.g. Don’t own a car. Limit how many services or subscriptions you have. Etc.
• We give favor to regularized systems rather than more advanced or perfect ones. Microsoft Excel is ubiquitous because it is interchangeable and easy enough understand and use, not because it is the perfect solution.
• Chess players are given a score that rates their playing ability or standing. Will employees in the future be scored? Surely if the workplace becomes more normalized this is a real possibility. If one could find and hire a lawyer based on their ranking, would that be so bad? Maybe it would cause some havoc in the industry initially, but where winning a case is critical to a client, maybe this is a good thing. Yes, it will probably be easy to artificially inflate one’s rating, but it could open the door to people who otherwise would be ignored because they lack the advantage of things like nepotism.
• “It’s the bumps and delays that will make the rise of smart machines a livable process.” Adoption rates are surprisingly slow. Think if industries like maritime. They’re only just starting to adopt the most basic of computing technologies. Most industries, of course, adopt smart technology gradually, either at a pace they are comfortable with, or a rate pushed by the world at large.
• This idea that we’ll be able to scan our brains and upload them to a storage device seems far fetched. He idea that thought lives outside the requirements of a brain. We’re still learning just how strongly connected our minds our to our bodies; for energy and nourishment and focus. For this we’d need to replicate or emulate the entire human body. Maybe a mix of scanning and cloning?
• What’s the point of the Turing test? What good could it be knowing that a computer can be perceived as intelligent? There are no signs this will even happen, but so what. What’s more interesting is that with the diversity of human beings, there are people who cannot pass it. Think of the symptoms of autism or Aspergers. In a Techniche study of the Turing test, involving a mix of humans and computers, only 63% of the audience could identify humans as humans.
• There seems to be little to no evidence that foreign competition destroys U.S. jobs. The belief is that we can’t compete against their low-wedge workforce. However, their productivity is very low. Also, numerous service jobs are not threatened by outsourcing; filing clerks, admins, cashiers. It’s technology that has had the largest effect. (Foreign nations can’t seem to compete with the U.S. Their lack of innovation and hyper focus on collecting and saving capital are indicators of this. If their future was bright, there’d be signs of spending cash.)
• Papers by Giovanni Peri, and others, reveal immigration boosts American wages.
• Factor price equalization – “If an apple sells for $2 in the United States and $1 in Bolivia, there is incentive to ship the apples until the prices move closer together.” This same thinking is used for human workers. Yes, outsourcing negatively affect American jobs, but it makes the U.S. market sluggish. And those losses are offset by gains elsewhere.
• “A study by Michael Spence and Sandile Hlatshwayo shows that jobs gains have been in government, health care, and education. These have strong job security, but are subject to daily market tests.” So, whether they provide good service or not is indeterminate. How does this affect the job market as a whole? Will these sectors be inclined to pull low quality workers? Surely it helps keep the American Dream alive.
• Online chess schools have taught millions of people to the point of mastery. This is astonishing and remarkable. People who otherwise would now have access to such training. And it’s driven by commercial incentives. “In 2008 and 2012 the small nation of Armenia too first place in the Chess Olympiad.”
• The current pitfall of online education is that it requires one to be self motivated. Really, for these people, it’s only a matter of access to great learning resources that would have prevented their education. “Chess teacher Peter Snow reports that some of his students love playing against the computer, but they deliberately put the quality settings on the program so low that they can beat it many times in a row.” Mastery requires ratcheting up, always improving; this appears to be some form of entertainment.
• One criticism of online education is that students miss the motivational aspects of a teacher. If this is true, why is this quality not taken into consideration when hiring educators? Or why is it given so little importance when hiring? “Let’s treat professors more like athletic coaches, personal therapists, and preachers, because that is what they will evolve to be.”
• The way we educate may split in two. One, a more hands-off approach where students self-teach and rely on infrequent teacher-student interactions. The other, a more motivational, boot camp driven approach where effort is taught just as much as subjects.
• Three types of workers (who work with machines and need to retrain):
1. Individuals who opt for self-education
2. Those who are less self-motivated, but follow extreme forms of discipline for short bursts
3. Those who just try to get by
• Self-education. Reeducation. This is the clearest path to success.
• Machine science currently is “human directing computer to aid human doing research.” It will become “human feeding computer to do its own research” and then “human interpreting the research of the computer.”
• Altruism, and the largest demographic of voters, will keep government programs like Medicare intact.
• A government healthcare plan makes the job market tougher. “The greater the value of the mandate, the less enthusiastic the business will be to hire more workers. Quite simply, mandates lower the demand for labor and create downward pressure on the general level of wages.”
• Want to predict the future? See where people are moving. Texas has wild growth – because of cheap housing and strong job market. Other than this, Texas scores rock bottom: low education, few social services, hot and humid, etc. It shows people want cash in their pocket.
• Is the author proposing we replicate developing nations by building tiny-home subdivisions, wired with Hulu and send our elderly there to live out the remained of their lives? Either way, people will either move to where land is cheap or find ways to make their land cheap to adjust for any loss of income.
• The disparity of healthcare access will widen.
• Is this a story that demotivates? Or is it something to be seen as an opportunity? Does the world need to change? Or do we?
• Mortality is the cure-all. Future generations will be unaware of the difficulties presented by transformative technologies. If one were to go back even 100 years they’d have great difficulty navigating most any workplace.