By Myriam Melki, Pam Liou, Sam Lavigne, Jon Wasserman
Erik Brynjolfsson and Andrew Mcafee begin the Second Machine Age with a broad discussion of human progress, asking: “What have been the most important developments in human history?” They argue that human social progress corresponds with technological progress, and that the last great leap in human progress can be directly traced to the invention of the steam engine. Furthermore, we, in our current historical moment, are in the early stage of what will become the next great technological and social breakthrough. Where the previous leap had been brought about by our ability to leverage the power of steam (and fully expressed itself in the industrial revolution), the current leap is catalyzed by advances in computer technology, and will lead to what they call a “second machine age.” And what, exactly, will human progress look like? “We’re heading into an era that won’t just be different; it will be better, because we’ll be able to increase both the variety and the volume of our consumption.”
In chapter 2 Brynjolfsson and Mcafee point out how computers have become increasingly good at performing tasks that were previously assumed to be impossible for a computer to complete. For example, self-driving cars, once thought to be beyond computation, have now become a technical reality and will likely soon enter the consumer space. At the same time, computers like the Jeopardy machine “Watson” are getting better at processing natural language. They argue that three key characteristics are most foundational in the “second machine age”: technology is becoming increasingly “exponential, digital, and combinatorial.”
Chapter 3 tackles the exponential quality of technology. Brynjolfsson and Mcafee reference Moore’s law and describe how computer technology advances at a consistently exponential rate, due mostly, they claim, to the ingenuity of computer engineers and designers. They argue that exponential advances accelerate so quickly that they are difficult to fully comprehend.
Chapter 4 describes the power of digitization. Brynjolfsson and Mcafe’s main point is that information is becoming increasingly digitized, which increases overall understanding “by making huge amounts of data readily accessible.” Large quantities of cheap data can be analyzed and collated. As an example they cite Waze, a GPS app that collects information about road conditions from everyone who has the app installed, thereby converting smartphones into data collection devices.
Some thoughts: the description of our current state of technology seems accurate. This is, however, a utopian, pro-capitalist, pro-consumerist book that enshrines a new form of exploitation, one that is distributed and crowdsourced. Technological advances will continue to replace human labor. The authors give this march of innovation an uncritical positive value. Unfortunately, the utopian goal to free up human time can never happen because the owners of innovative technology don’t distribute the surplus value they create. It’s difficult to benefit from “exponential, digital, and combinatorial” advancements unless you control the robot that replaces you.
Chapter 5 starts with a very interesting quote, one the whole book seems to be revolving around: “Productivity isn’t everything, but in the long run it is almost everything” (Paul Krugman). The authors emphasize the importance of general purpose technologies. GPTs such as steam and electricity impacted more than just their respective industries, they spread quickly to other sectors of the economy and revolutionized the industrial world. And Information and Communications Technologies are the new GPT. And although innovations get used up, causing the economy to be stagnant at times, recombinant growth generates new ideas, thus boosting the economy once again. All inventions are a mish mash of things invented in the past and overlooked. There are endless possibilities for new ideas because there are always ways to recombine things and ideas in new ways, especially in the internet age. In the early stages of development, growth is constrained by number of potential new ideas, but later on it is constrained only by the ability to process them. The solution would presumably be to bring in more eyeballs in order to process more ideas. According to the authors “Plenty of building blocks are in place, and they’re being recombined in better and better ways all the time”.
Chapter 6 is entitled Artificial and Human Intelligence in the Second Machine Age. The authors seem confident about the future, because “We’re going to see artificial intelligence do more and more, and as this happens costs will go down, outcomes will improve, and our lives will get better. Soon countless pieces of AI will be working on our behalf, often in the background. They’ll help us in areas ranging from trivial to substantive to life changing.” IBM are building the world’s best diagnostician, a robot. And C-Path is a computational pathologist that is supposedly more accurate and less biased than human pathologists. Moreover, the digital network has supposedly led to an overall improvement in all fields, including the environment (air quality for example).
Chapter 7 gives an overview on the important productivity growth that followed the introduction of Information and Communications Technologies in our lives. Despite its “productivity paradox”, this GPT has led to an improvement in various sectors of the economy. The authors then explain how the introduction of the internet and sometimes even just organizational softwares in firms and industries have improved in the long run their productivity.
The Second Machine Age details the shortcomings of the current models of measuring economic growth: GDP. Are there alternative metrics to articulate the productivity and wealth of a nation other than GDP? What does GDP fail to capture?
Free digital goods pose a profound challenge to qualitative measurement because they offer value and improvements to quality of life without driving revenue. These innovations create efficiencies; however, the jury is still out on whether these benefits outweigh the effect of an exponentially increasing number of new, free digital goods flooding the market.
Various alternative approaches include:
Would you rather? Method
The choice between for comparable services over time Produce mark rather insubstantial qualitative gains, while digital services has improved by leaps and bounds.
Measuring Consumer Surplus-
“If you would happily pay one dollar to read the morning newspaper but instead you get it for free, then you’ve just gained one dollar of consumer surplus.” Measured in money AND time; “rapidly growing consumer surplus from price declines in computers increased economic welfare by about $50 billion each year.”
Gross National Happiness- Bhutanese index to measure quality of life per capita across a wide range of categories.
New Products- Measuring SKU’s or introduction of new items into the market. Think of it as the product always existing, but was infinitely expensive to produce prior to its invention.
Our global economy has reached an event horizon where the rate of innovation in digital tools and commodities has outpaced the rate of innovation in physical/engineered ones. While digitalization has made marked improvements to the manufacture of goods and production, there are limits to those gains (um–like, physics). Pushing these limits through globalization and aggressive (but common) Supply Chain Management tactics has led to tenuous infrastructures and complete collapses of entire verticals.
How do you account for an economy where the loftiest, highest creative needs are met while the basic needs are not? Maslow would be reeling. SMA treats digital innovations as the same as physical ones, but they would be weighted differently.
Here’s a perfect illustration of this: Korean parents let baby starve as they play with virtual child.
The disproportionate distribution of wealth that privileges the leader in a category and front-runners of all kinds. That’s pretty much all this chapter says, and supports this claim with lots of statistics.
Technology is not a scalar that benefits a cross section of the population equally.
Chapter 12 is basically about the future. We worry or expect that machines will take over completely, they say. And they probably will with the exciting developments like Google’s autonomous car. But never fear, humans still have the upperhand on deviating from rigid prescribed operations. This is, for now, the thing that robots can’t do better than us. They suggest that you should find an area of industry where people are becoming obsolete, and then figure out the one adjacent space where you can provide human expertise, thus capitalizing on the scarcity. Seems like sound advice.
Chapter 13 makes broad suggestions about future forward policy decisions to prolong the human ability to be productive and desirable to an economy. They assert that we can ”encourage technology to race ahead while ensuring that as few people as possible are left behind. They start off the chapter saying, “With sci-fi technology becoming reality it might seems that radical steps are necessary, but… many recommendations for growth and prosperity found in any “Economy 101″ textbook are the right place to start now and for a while.” The reason for this is that humans can still manage enough logical work better than machines. This could be interpreted as the obvious way to continue participating in this economic system but NOT because the current economic philosophy is sound.
The way to beat the labor force challenge is to grow the economy. There are a number of ways to do that not least of which is to incorporate more technology into education. That’s good because Education has been a “laggard” compared to other Industries. Therefore if we stop being laggards about learning better and using more technology, then by transitive property we will naturally (guaranteed and obviously) catch up to other industries. Because Education is an Industry and in this economic model is bound to compete with other Industries.
Chapter 14 addresses the long-term strategies and challenges. While admitting that History (not human choice) is “littered with unintended… side effects of well intentioned social and economic policies”, the authors cite Tim O’Reilly in pushing forward with technology’s momentum rather than clinging to the past or present. They suggest that we should let the technologies do their work and just find ways to deal with it. They are “skeptical of efforts to come up with fundamental alternatives to capitalism”. The features of private control over production as opposed to governmental work so well, that they’re even used in China, “which is still officially communist”! Their existence is proof of their success and durability and doesn’t need to be challenged or evaluated.
Most of earners are laborers. As androids take over our jobs, employers will be forced to pay lower wages and ultimately cut jobs. One solution that has been floating around for a few hundred years is Basic Income, a format where everyone is paid to have a minimum standard of living. Endorsed even by Richard Nixon, his last attempt was thwarted by caseworkers and administrators of welfare programs, notorious for their large numbers and unbalanced influence, who were worried about losing their jobs. But the authors are wary of endorsing that solution, because “work” provides more than just money, it provides self-worth among other noble attributes.
Chapter 15 reasserts that we are at an “inflection point”, the precipice of another Industrial Revolution. But with technological advancements, we open ourselves up to accidents and malice of greater magnitude. The internet of things amplifies this further. “There’s a genuine tension between our ability to know more and our ability to prevent others from knowing about us. When information was mostly analog and local, the laws of physics created an automatic zone of privacy.”
So what’s in store for us? Utopian future or dystopian future? The Singularity or Terminator? “It’s wise to never say never, but we still have a long way to go” they say. At the end, it all boils down to Uncle Ben.