By Abhilash Mishra
Oct 20, 2023
When I was a graduate student in Astrophysics at Caltech in the 2010s, a running joke was that a Ph.D. in Astrophysics was excellent training to become a data scientist to help Facebook or Google sell ads. In 2012, the Harvard Business Review declared being a data scientist the “sexiest job in the 21st century,” and many of my peers eschewed uncertain job prospects in academia for more financially lucrative opportunities in tech.
However, we’re already seeing this trend come to an end. Tech companies are increasingly replacing “high-skill” workers with AI and cutting jobs they predict AI will replace. AI will have far-reaching effects on the “high-skill” tech workforce globally, with tech workers outside the US in markets like India feeling the brunt. These changes require reimagining how we train and upskill tech talent for the future. It’s up to business leaders and educators globally to confront this challenge with urgency.
Let’s discuss how we got here. After the turbulence of the first half of 2020, tech companies inflated their teams thanks to low-interest rates in the US and exploding revenues. Then, interest rates began to rise in March 2022, which began an economic cooldown. Corporations and small businesses started to tighten their purse strings and spend less on ads, and we continue to see tech layoffs weekly.
Simultaneously, tools like ChatGPT and Github co-pilot have demonstrated that tasks by data scientists and software developers can be executed more efficiently with these tools. As Ethan Mollick, an Associate Professor at Wharton, has documented on Twitter, ChatGPT has the potential to turbocharge the efficiency of data science professionals. Instead of needing to hire hundreds, even thousands, of data scientists, tech companies can now accomplish the same tasks in shorter periods, requiring fewer employees to get the job done.
As the economy stabilizes over the coming months and years, the boom in tech hiring we experienced during the pandemic likely won’t be back. And neither will many of the high-tech jobs lost in the layoffs.
So, what does this mean for the future of the tech workforce globally? First, salaries in tech will be lower. Tech workers in major hubs from Silicon Valley to Bangalore should recalibrate their expectations and prepare their financial futures with this new reality.
As the current chill in venture capital funding thaws, startups, particularly in AI, will grow. These startups will have a unique opportunity to take advantage of the high-skill “talent glut” in the current job market. More importantly, deflating compensation in Big Tech means overlooked sectors like climate, healthcare, education, and government, which urgently need tech talent, have a better chance of enticing workers.
The current malaise around tech companies can also spur innovation in the social sector. Technologists should look for lesser-paid but more impactful jobs in social enterprises, nonprofits, and the public sector, which are starved for tech talent.
Finally, current and aspiring technology workers must become proficient in using AI tools. For example, data science projects require arduous data cleaning and assimilation before analyzing the data. New tools like GPT code interpreter will make this process very efficient, allowing data scientists to increase their productivity.
Upskilling is not only the responsibility of those looking for employment. As Gary Becker, the Nobel Prize-winning economist from the University of Chicago argued in his seminal work on human capital, employers need to continue investing in on-the-job upskilling, if they want a productive workforce. This upskilling needs to focus on specialized skills like using emerging AI tools for their jobs, as opposed to more general skills gained through an undergraduate or masters education. Simultaneously, educational institutions must pivot their curricula to train their data scientists in these tools. In addition, as supported by the Future of Jobs Report, they should equip their students with critical thinking skills and flexibility. From disinformation to subpar copywriting, there’s valid widespread concern over the outputs of AI tools. Whatever an AI tool spits out needs to be checked for accuracy and bias, which requires a discerning human trained to identify and debate these topics. This educational shift is especially important in countries such as India, where universities focus on technical ability at the cost of building more widely applicable critical thinking skills. The workplace will inevitably see mass disruption and an increased need for critical thought, so technologists need to be able to adapt dynamically and creatively to their environments.
Companies, too, need to focus on education. They have to develop a habit of regular training and a culture of learning to stay competitive with technological advancements. It’s unsustainable for companies to rely on external talent, as progress will continue to happen rapidly, or for companies to rely on employees to take on training in addition to their regular workload. Upskilling needs to be a part of their business strategy instead of an employee benefit for the curious few.
We need only look at the last century to understand how technological transformations can affect the labor force. As Nobel-prize winner Claudia Goldin and Lawrence F. Katz referenced in their book The Race between Education and Technology, at the beginning of the 20th century, over 40% of the American workforce was employed in agriculture. Mechanization and farm innovations led to sweeping increases in agricultural productivity, and by the end of the century, only 2% of the population was engaged in agriculture. The technological revolution in agriculture did not lead to mass unemployment; instead, new types of jobs were created.
The current AI-driven tech transition is likely to follow a similar path. New jobs will be created over the coming decades. But the transition is expected to be messy. Business leaders, technologists, and educators need to prepare proactively for this transition or prepare to be left behind. This is the transition Equitech Futures aims to ease.