What Will Humans Do In An Artificially Intelligent World
The Argentinian writer Jorge Borges had a fascination with a concept known as the infinite monkey theorem. The idea is that if you had an infinite amount of monkeys pecking away at an infinite amount of typewriters, they would randomly create the collected works of Tolstoy and every other masterwork ever written (or that could be written).
The theorem, which has been around for at least a century, is troubling because it calls into question what it means to be human. If we can be inspired by something that could so easily be randomly generated, then what does it mean to be meaningful? Is meaning just an illusion we construct to make ourselves happy?
In recent years, the rise of artificial intelligence has transformed this theoretical dilemma into an intensely practical issue. In a world in which machines are taking over work long thought of as intensely human, what is the role of human labor? How do we create value that is distinct from what machines can do faster and cheaper? The answers will shape our future.
Machines Replacing Humans
The first industrial robot, called Unimate, was installed on an assembly line at General Motors in 1961. Since then, robots have become highly integrated into our economy. They do dangerous jobs, like bomb disposal, as well as more prosaic ones, like running warehouses and legal discovery.
And lest you think that automation only applies to low-skill, mechanical jobs, robots are also invading the creative realm. One book written by a machine was even accepted as a submission for the prestigious Hoshi Shinichi Literary Award in Japan. There are now robots that advise physicians, movie producers and music executives. Some even write songs.
Yet these things have been, for the most part, going on in the background. Very few of us see robots at work in factories, much less evaluating scripts, reading mammograms or doing research for lawyers. However, the introduction of ChatGPT brings the power of AI to anyone with an Internet connection.
If you haven’t tried it yourself yet, here’s an example: I asked it to explain the infinite monkey theorem to me and this is what I got:
The infinite monkey theorem states that a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type any given text, such as the complete works of William Shakespeare. The theorem is often used as a humorous illustration of the basics of probability theory. However, the theorem is actually a misnomer, since the chances of a monkey randomly typing a meaningful sequence of characters is incredibly small, and the concept of an “infinite” amount of time is physically impossible
And just for fun, I asked it to produce a one paragraph promotional biography of Greg Satell:
Greg Satell is a thought leader in innovation and business strategy, with over 20 years of experience in the industry. He is a popular speaker and author, known for his bestselling book “Mapping Innovation: A Playbook for Navigating a Disruptive Age.” Greg has also held executive roles at leading companies and has a track record of driving innovation and growth through effective business strategies.
Each of these responses appeared in seconds and, while they are not what I would have chosen to write myself, they are more than passable. With the technology advancing at this pace, how can we compete with the machines?
The Automation Paradox
In 1900, 30 million people in the United States were farmers, but by 1990 that number had fallen to under 3 million even as the population more than tripled. So, in a manner of speaking, 90% of American agriculture workers lost their jobs due to automation. Yet those out-of-work farmers weren’t impoverished. In fact, the 20th century was an era of unprecedented prosperity.
Consider this: Although the workforce in the US has more than doubled since 1950, labor participation rates remain close to all-time highs. Still, a recent report by the US Chamber of Commerce found that we have a massive labor shortage. In the highly-automated manufacturing sector, it estimated that even if every unemployed person with experience were employed, it would only fill half of the vacant jobs.
In fact, when you look at highly automated fields, they tend to be the ones that have major labor shortages. You see touchscreens everywhere you go, but 70% of openings in the retail sector go unfilled. Autopilot has been around for decades, but we face a massive global pilot shortage that’s getting worse every year.
Once a task becomes automated, it also becomes largely commoditized and value is then created in an area that wasn’t quite obvious when people were busy doing more basic things. Go to an Apple store and you’ll notice two things: lots of automation and a sea of employees in blue shirts there to help, troubleshoot and explain things to you. Value doesn’t disappear, it just shifts to a different place.
One striking example of this is the humble community bookstore. With the domination of Amazon, you might think that small independent bookstores would be doomed, but instead they’re thriving. While its true that they can’t match Amazon’s convenience, selection or prices, people are flocking to small local shops for other reasons, such as deep expertise in particular subject matter and the chance to meet people with similar interests.
The Irrational Mind
To understand where value is shifting now, the work of neuroscientist Antonio Damasio can shed some light. He studied patients who, despite having perfectly normal cognitive ability, had lost the ability to feel emotion. Many would assume that, without emotions to distract them, these people would be great at making perfectly rational decisions.
But they weren’t. In fact, they couldn’t make any decisions at all. They could list the factors at play and explain their significance, but they couldn’t feel one way or another about them. In effect, without emotion they couldn’t form any intention. One decision was just like any other, leading to an outcome that they cared nothing about.
The social psychologist Jonathan Haidt built on Damasio’s work to form his theory of social intuitionism. What Haidt found in his research is that we don’t make moral judgments through conscious reasoning, but rather through unconscious intuition. Essentially, we automatically feel a certain way about something and then come up with reasons that we should feel that way.
Once you realize that, it becomes clear why Apple needs so many blue shirts at its stores and why independent bookstores are thriving. An artificial intelligence can access all the information in the world, curate that information and present it to us in an understandable way, but it can’t understand why we should care about it.
In fact, humans often disguise our true intent, even to ourselves. A student might say he wants a new computer to do schoolwork, but may really want a stronger graphics engine to play video games. In much the same way, a person may want to buy a book about a certain subject, but also truly covet a community which shares the same interest.
The Library of Babel And The Intention Economy
In his story The Library of Babel, Borges describes a library which contains books with all potential word combinations in all possible languages. Such a place would encompass all possible knowledge, but would also be completely useless, because the vast majority of books would be gibberish consisting of random strings of symbols.
In essence, deriving meaning would be an exercise in curation, which machines could do if they perfectly understood our intentions. However, human motives are almost hopelessly complex. So much so, in fact, that even we ourselves often have difficulty understanding why we want one thing and not another.
There are some things that a computer will never do. Machines will never strike out at a Little League game, have their hearts broken in a summer romance or see their children born. The inability to share human experiences makes it difficult, if not impossible, for computers to relate to human emotions and infer how those feelings shape preferences in a given context.
That’s why the rise of artificial intelligence is driving a shift from cognitive to social skills. The high paying jobs today have less to do with the ability to retain facts or manipulate numbers—we now use computers for those things—than it does with humans serving other humans. That requires more deep collaboration, teamwork and emotional intelligence.
To derive meaning in an artificially intelligent world we need to look to each other and how we can better understand our intentions. The future of technology is always more human.
This post originally appeared on Greg Satell's blog. Read that and more here.