Fear Not the Bots: Prospering in the AI Age Through Adaptation and Integration | Teen Ink

Fear Not the Bots: Prospering in the AI Age Through Adaptation and Integration

June 23, 2023
By KevinS78 BRONZE, Palo Alto, California
KevinS78 BRONZE, Palo Alto, California
1 article 0 photos 0 comments

A few months ago amidst the ChatGPT hype, I picked up and read the book The AI Economy by British economist Roger Bootle out of curiosity about the future of artificial intelligence (AI). Just a few chapters in, I was completely hooked by the thorough, fascinating, and thought-provoking discussions regarding the implications of AI on the economy of the near future. And after finishing the book, I felt that I had a complex understanding of the promises of AI for the first time — not just because the book was often eye-opening, but also because I found myself disagreeing with several points Bootle made in his book.

To reconcile my own intuition and thinking with my reading, I knew I had to further pursue the topic and dive deeper. This article is the culmination of what I learned on that dive, and I hope that it can offer the reader with new perspectives or insights into how AI may affect our lives in the coming years.

Artificial intelligence is defined by the Encyclopedia Britannica as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings,”  and the idea of AI is generally regarded as having originated from English mathematician and computer scientist Alan Turing in the mid-20th century. Since then, the field has advanced tremendously. Today, AI is used in myriad applications, ranging from autonomous vehicles to the stock market, and from manufacturing to social media.

As AI progressed, there has tended to be a disconnect between expectations and reality. Originally, many believed that although AI could be very efficient at relatively simple work, it could not match human intelligence at complex tasks. Then, in 1997, the IBM supercomputer Deep Blue defeated the then-world chess champion Garry Kasparov, shocking the world. Experts reasoned that this was possible because chess is a game that could be “solved” using brute computational force. AI again exceeded expectations in 2016, when Google’s AlphaGo defeated top-ranked Lee Sedol at the ancient Chinese board game Go, which is far more complex than chess, requires a degree of intuition, and is difficult to brute-force. Just last year, OpenAI released the AI chatbot ChatGPT, which took the world by storm with its ability to generate human-like writing.

As AI technology is certain to continue advancing, more and more activities traditionally thought to be uniquely human will likely become replicable by AI. This trend has led some to fear that AI will become more advanced than humans to the point of causing an economic and employment crisis in the near future, which in turn has prompted many to come up with theories and ideas on how humanity should react to the incoming wave of AI automation.

However, before considering the best ways to respond to automation, it is important to discuss the actual proximity of the AI revolution and the changes it promises to bring — whether increased automation will happen in ten years or fifty years will greatly impact whether or not it makes sense to start preparing today.

McKinsey Global Institute predicted that before 2030, up to 39 million people would be displaced in the US alone assuming “midpoint automation,” and this figure increases to 73 million people if assuming “rapid automation.” These amount to over 20% and 40% of McKinsey’s predicted 2030 US workforce, respectively. Given the nature of AI-based automation, it would most likely replace jobs based on occupation rather than company or region. People who are predicted to lose their jobs would be made obsolete, so retraining and re-education would then be necessary.

However, many people would likely not have the resources to support such activities after suddenly losing their jobs. If McKinsey’s predictions are accurate, this would lead to large groups of people becoming not just unemployed, but unemployable, by 2030. The 20% and 40% estimates mean that the unemployment rate during the AI revolution could reach or exceed what it was during the Great Depression (which was around 25%).

Yet there are also experts who disagree with this notion of imminent mass unemployment. Instead, they argue that AI technology will not advance fast enough to be able to replace large amounts of human workers in the near future. Roger Bootle writes in The AI Economy that “there are many areas where humans possess an absolute advantage over robots and AI, including manual dexterity, emotional intelligence, creativity, flexibility, and, most important, humanity.” According to Bootle, these advantages would allow human workers to retain their jobs for the most part, at least in the near future.

However, this viewpoint regarding AI is rather limited and flawed. Developments in AI are, in fact, likely to advance rapidly, and AI of the near future would almost certainly be able to gain qualities that are traditionally thought to be human. In a Forbes article, author and AI visionary Calum Chace refers to “AlphaGo’s famous move 37 in its second game against Lee Sedol in 2016” as “one of many proofs that machines can be creative,” and “the progress of robots developed by Boston Dynamics and others in the last few years” as disproving the idea that “humans will remain supreme forever in manual dexterity and flexibility.”

The famous “move 37” is considered to be an excellent yet completely unintuitive move. Less than 20 years ago, Boston Dynamics struggled to develop quadrupedal robots that could walk on much more regular surfaces without looking awkward. But today, it has developed humanoid robots capable of traversing uneven terrains, completing parkour courses, and even performing acrobatics. Even if there are certain tasks that AI is strictly worse at completing than humans, past trends indicate that AI will likely overcome these obstacles before long.

As a result, if no action is taken, AI is almost certain to pose a substantial threat to the employment of human workers in the near future. In order to be prepared to rectify whatever harm this may cause, society urgently needs to consider, experiment with, and possibly even implement appropriate responses to the AI revolution today.

Different parts of society will certainly need to work together to prepare for AI-based automation. As a uniting and mediating force, governments will have to be the leaders of this effort to devise and implement reforms, just as they have been in the past. To promote the welfare and prosperity of their citizens, policymakers need to make perhaps radical laws to adapt to the changing world. However, this will be no easy task.

Right now, many ideas are being thrown around as potential ways to ameliorate the imminent wave of unemployment. One popular idea is a robot or AI tax. Its supporters, including Bill Gates and Bernie Sanders, believe that an effective way of supporting human workers would be to slow down the advancement of AI-based automation by imposing a new tax on businesses and industries that employ robots and AI.

In an interview with Quartz, Gates said that for robots and AI, “taxation is certainly a better way to handle it than just banning some elements of it” and that since the robot and the human it replaced fulfill fundamentally the same role, the robot should also be taxed in the same way to maintain equilibrium. If businesses still decide to use employ robots, the new tax could be used to fund more welfare programs, for example.

Though the idea of a robot tax is popular, it also has its fair share of opponents. Roger Bootle points out in his book that “in an increasingly globalized world, if one country taxes capital equipment, this would make it more likely that less capital investment will take place within its borders.” This means that if a country like the US were to impose a robot tax, businesses may opt to move to a country like China, whose “relative lack of regulation” regarding AI is already “fueling faster experimentation and innovation,” according to Bootle. Large businesses always have the option to move away from a country if its policies become unfavorable, unless all countries could unanimously agree to implement a robot tax. This would harm the economies of countries with robot taxes, which would in turn hurt the very workers the robot tax was supposed to protect.

A better way of supporting human workers in the AI revolution would be to adapt to increasing automation, rather than discouraging it. Policymakers could instead consider developing a system like universal basic income (UBI). Simply speaking, UBI is the policy that every individual in a society should be provided with a sum of money regularly, regardless of their income or employment status, the goal being to ensure everyone has enough money to meet their basic needs and have a minimum standard of living. In the US, this would be a payment from the government of around $500 to $1000 per month per person.

UBI has been tested on several occasions. For instance, a UBI experiment in Stockton, California showed that UBI had clear economic and psychological benefits — reduced income fluctuations, unemployment, anxiety, and depression. Even if someone would lose their job in the AI revolution, a UBI system like the one tested in Stockton would ensure that they have enough money to at least meet their basic needs, giving them the ability to reskill themselves or to search for new work.

As for the money necessary to fund a nationwide UBI, part of it could come from eliminating current welfare programs (as is commonly suggested). The remaining amount could come from increasing taxes on the superrich or from decreasing other government spending. By adapting to AI automation using UBI instead of restricting it through a policy like a robot tax, society will best support its human workers without causing harmful side effects.

Although government policy is both powerful and necessary in helping society through a crisis of unemployment, it will not be sufficient by itself. Policymakers can provide a solid floor through systems like UBI, but individuals will still have to lift themselves up from that floor by taking personal responsibility and action.

It is not difficult to find advice that says to prepare for the AI revolution by selecting careers in industries perceived to be hardest to automate with AI. One particular idea is that individuals should shift their focus towards jobs in the leisure and hospitality sectors because of the human interaction aspect of those industries. Roger Bootle explains in his book that people still pay lots of money to attend in-person entertainment events like concerts despite there being many cheaper or free options, such as those available online, because people value human authenticity and interaction. Then, during the AI revolution, even if AI becomes capable of being employed in the leisure and hospitality industries, people would likely still prefer to have these roles filled by other humans, leaving these jobs as a safe haven that humans should seek out.

Although this idea has merit in theory, it is difficult to put into practice because the jobs where human interaction is valuable simply are not enough to support the workforce. According to the US Bureau of Labor Statistics, only 16.5 million Americans worked in the leisure and hospitality industries out of the 155 million total non-farm workers, as of February 2023. Since leisure and hospitality jobs currently account for such a small portion of the job market, it is unreasonable to say that the workforce can all focus on these jobs if other industries become dominated by AI.

Instead, a more practical course of action for individuals is to educate themselves about AI and learn the skills necessary to collaborate with AI in their area of employment. According to research by authors H. James Wilson and Paul R. Daugherty published in the Harvard Business Review, “firms achieve the most significant performance improvements when humans and machines work together. Through such collaborative intelligence, humans and AI actively enhance each other’s complementary strengths.”

AI-based automation naturally excels at speed, efficiency, and power, whereas humans naturally excel at leadership, creativity, and empathy. By having human employees work together with AI, businesses can combine the greatest strengths of both and maximize their productivity. Thus, it makes sense that workers should learn these relevant skills (and a system like UBI can provide the resources for this) to make themselves more attractive to companies. Finally, unlike jobs in a specific sector like leisure or hospitality, which are a limited resource, everyone can learn the skills needed to work with AI if they have the time. Therefore, this plan of integrating human intelligence with AI can essentially apply to everyone, ensuring general prosperity in the AI age.

As past and current trends in the advancement of AI technology predict, a future where AI can readily displace human workers is not distant. Consequently, in order to survive, society must come together to prepare for the advent of the AI revolution. Governments can support human workers by establishing systems like UBI, which would provide a financial safety net if people do lose their jobs to automation. At the same time, individuals must also take an active role by learning to integrate their own human skills with the power of AI, thereby reducing the likelihood of losing their jobs in the first place. If society can succeed in adapting to this revolutionary change that is soon to come, we will be able to largely mitigate the harmful effects of AI and reap its benefits to secure the well-being of all. 


The author's comments:

This article was originally written as a paper for my school English class. While writing it, I had learned a lot about the topic and wanted to share what I learned with other people, which is why I decided to edit the paper into article form and submit it to Teen Ink.


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