Artificial Intelligence and the Future of Work
Introduction:
Artificial Intelligence (AI) has become one of the most transformative technologies of our time, with its impact felt across various industries and sectors. AI refers to the development of computer systems capable of performing tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and problem-solving. With advancements in machine learning, deep learning, and natural language processing, AI has made significant strides in recent years, enabling machines to learn, adapt, and perform complex tasks with remarkable efficiency. As AI continues to advance and integrate into our daily lives, it raises important questions about the future of work and the potential implications for the labor market.
Is AI a liberating or a destructive force?
For many of us, the term “AI” conjures up sci-fi fantasies or fears about robots taking over the world. The depictions of AI in the media have run the gamut, and while no one can predict exactly how it will evolve in the future, the current trends and developments paint a much different picture of how AI will become part of our lives. New technology brings with it risks like widening the gap between rich and poor countries by shifting more investment to advanced economies where automation is already established. This could in turn have negative consequences for jobs in developing countries by threatening to replace rather than complement their growing labor force. The impact of AI on the workforce is a subject of intense debate.
So to what extent is employment at stake?
While AI has replaced several jobs, it has created other jobs, which have employed highly skilled workers such as data scientists, problem solvers and employees specialized in Machine Learning. The catch here is that thousands of unskilled workers have already lost their jobs and it is estimated that it will replace 85 million jobs (gross) globally by 2025, with them being replaced by AI. As technology has advanced, many tasks once executed by humans have now become automated and have made several jobs obsolete, thus demanding upskilling in other fields for these workers.
Jobs such as legal workers, customer service supporters, sales representatives, content creators, writers etc.. and on the other side jobs such as weavers, textile mill workers etc.. have become or are soon expected to become trivial and easily replaceable with AI. Thus, reduced demand for such labour will lead to lower wage rates due to lesser bargaining power in the hands of workers in these sectors.
AI has been one of the key factors that drive and control the labor market. Although there are several debates about whether AI will replace human capital, and there were times when people were alarmed by the term “technological unemployment” (historically stated by John Maynard Keynes), the recent decades depict no contraction of employment despite the massive advancement of AI. In fact, it has evidently improved labor productivity and sectoral growth. Hence, it is important to note the fact that AI complements their intellectual activity—it doesn't replace it! It has the potential to augment human capabilities and create new opportunities. By automating mundane tasks, AI can free up human workers to focus on higher-value activities that require creativity, critical thinking, and emotional intelligence. AI can act as a powerful tool for productivity enhancement, allowing humans and machines to work together more effectively. A paper published by the MIT Task Force on the Work of the Future entitled “Artificial Intelligence And The Future of Work,” looked closely at developments in AI and their relation to the world of work. Rather than promoting the obsolescence of human labor, the paper predicts that AI will continue to drive massive innovation that will fuel many existing industries and could have the potential to create many new sectors for growth, ultimately leading to the creation of more jobs.
Historical examples in advanced economies like the US are the transition from rural agriculture to urban manufacturing during the first half of the 20th century, and from manufacturing to services in more recent times. This is even more true if we consider another beneficial effect of technological change: everyday objects like dishwashers, vacuum cleaners, washers, and dryers have all reduced the burden of housekeeping and freed up time for women to seek employment. Indeed, the labor force participation rate was 67% in 2000, compared to 59% in 1948. The increases in labor productivity brought about by technological change spill over into higher wages for workers: in a 2015 report by Economic Policy Institute, economists Josh Bivens and Larry Mishel have documented that the average hourly compensation for the typical American worker in 2014 grew by about 110% relative to 1948.
Furthermore, the rise of AI is also expected to create new jobs and industries. As AI technology continues to evolve, there will be a growing demand for AI specialists, data scientists, machine learning engineers, and experts in ethical AI development. AI-driven innovations may also create entirely new sectors and business models, stimulating economic growth and job creation.
The above graph represents the global growth rate over the last two millennia. Growth has been stagnant for more than 80% of the period. Empirically, growth has occurred around the same time as technological growth and the spill-over effect has also been vast. The per capita growth also has the same curvature, which implies that people’s productivity and incomes have grown with technological progress.
However,
While AI has made major strides toward replicating the efficacy of human intelligence in executing certain tasks, there are still some major limitations stated as follows:-
In particular, AI programs are typically only capable of “specialized” intelligence, meaning they can solve only one problem, and execute only one task at a time. Often, they can be rigid, unable to respond to any input changes, or perform “thinking” outside of their prescribed programming. Humans, however, possess intelligence with problem-solving, abstract thinking, and critical judgment that will continue to be important in business.
AI often requires “learning” which can involve massive amounts of data, calling into question the availability of the right kind of data, and highlighting the need for categorization and issues of privacy and security around such data.
There is also the limitation of computation and processing power. The cost of electricity alone to power one supercharged language model AI was estimated at a few million dollars.
Another important limitation is that data can itself carry bias, and be reflective of societal inequities or the implicit biases of the designers who create and input the data. If biased data is input into an AI, the results will carry on that inherent bias.
We are a long way from reaching a point in which AI is comparable to human intelligence, and could theoretically replace human workers entirely. After all, it is essential to note that “human beings” as a whole cannot be replaced. Humans possess “generalized intelligence”, and have problem-solving and critical judgment capabilities that will continue to be significant in any sector. Human judgment will be relevant certainly throughout every level across all sectors.
Increasing concerns about the challenges faced by the IT market due to the rise of AI are redundant because people now have a new and different set of responsibilities to carry on and to pioneer furtherance of technological advancement, not only the General Purpose Technology (GPT) such as Artificial Intelligence discussed so far but other variations as well.
Categorizing how people perceive the emergence of every new GPT, there are three categories namely enablers, users and ignorers. These enablers are factors that contribute to the development of a particular technology such as researchers. The users like us, and every other business/organization come up in the second stage and facilitate efficiency in every aspect. Currently, it becomes essential for us to be one of the early adopters of advancements in technology, to catch up with the pace of world growth.
In fact, the only biggest challenge faced by any substantial sector contributing to growth is that people must be quick enough to update themselves and upskill themselves with the latest developments and advancements. The question should then become not humans or computers but “humans and computers” involved in complex systems that advance industry and economic prosperity.
Conclusion:
We cannot say that technological change has no cost to society. The transition from agriculture to manufacturing took time, and in the short run produced economic anxiety, unemployment, and poverty among former agricultural workers. The same applies to the transition to a service economy. The transition to manufacturing was associated with higher wages and more employment opportunities. The transition to services is not so much: low-skill service workers tend to be paid less than workers of similar skills in manufacturing.
Although AI may be completely different from the technological advances of the past, we should be skeptical that automation will mean the end of work. Jobs—or even specific tasks might be displaced, but workers will relocate to different jobs or take up different tasks. For low- and medium-skill workers, the relocation will likely occur in jobs of lower quality, meaning either lower pay, fewer benefits, or a combination of both. Workers who possess skills that are complementary to new technologies, on the other hand, will benefit from the advent of automation by reaping most of the productivity increases in the form of higher wages. And the very few CEOs of successful tech companies will see their incomes skyrocket.
In conclusion, the rise of AI presents both challenges and opportunities for the future of work. While there may be concerns about job displacement, AI also has the potential to enhance productivity, create new industries and job opportunities, and augment human capabilities. By embracing lifelong learning, nurturing creativity and soft skills, fostering collaboration between humans and machines, addressing ethical considerations, and providing social safety nets, we can navigate the evolving landscape of work in the age of AI and ensure a prosperous and inclusive future.
References:
Written by Pratyasha Kar in collaboration with Tharuni Mudumby | Proofread by Yasmin Uzykanova
