Opinion In a world run by AI, the early-career professionals stand to lose the most
Research-backed science now shows ample evidence that critical thinking and cognitive abilities are being eroded by GenAI apps. The machines are learning how to think and act better, leaving the humans behind to do the mundane
Most people seem to be working under a theory of trickle-down AI economics, where investments in large conglomerates powering AI will eventually trickle down and create value for all of us Written by Sai Rahul Poruri
AI, and in particular GenerativeAI, has a remarkably different effect on students and junior employees when compared to seasoned professionals. For instance, in the software profession, numerous experienced professionals report a dramatic increase in their output; overall, the quantity of code they produce has increased without a significant reduction in quality, thanks to GenAI apps. They effectively treat GenAI apps like junior employees, prompting them to make various kinds of changes, running tests to verify that the changes work as expected, and reviewing all the changes line by line using their expert judgement. Unlike a junior employee who might need multiple hours, if not days or weeks, to make the necessary changes, GenAI apps work practically instantly. Given how important iteration is in the software development process, seasoned professionals are able to iterate much faster than they ever were able to before.
But what happens to students and junior developers, you might wonder. Well, firstly, many firms seem to have halted hiring students and early-career professionals, because it’s much cheaper to pay for a GenAI app subscription than it is to hire someone new. And the senior professionals don’t need to have the emotional bandwidth to work with and mentor another human. Most companies hiring early-career professionals seem to be expecting them to use GenAI to be more “productive”, which might sound good in the short-term but is shown to negatively affect the long-term professional development of the individual. Software development, like most knowledge work, requires significant practice. Writing software programmes, discovering bugs, debugging the software, and fixing them are all essential to growing as a software developer, and mentorship plays a significant role in shaping the mental models that junior developers have when building software.
Unfortunately, in the software industry, individuals were measured on the quantity of software they produce and not necessarily the quality. This situation has only gotten worse with GenAI. Junior developers are having trouble debugging problems caused by GenAI-written software, and they are unable to develop the expertise needed to evaluate whether the GenAI-produced software adheres to best practices and industry standards. In a few cases, GenAI-written software is being reviewed by other AI-powered tools, and the junior professionals are being left out of the process, leaving little to no room for their professional development. In the worst case scenario, junior developers are effectively becoming passive factory workers, asking the apps to write a piece of code, as if they were pushing a button or pulling a lever on a factory line, without the ability to understand the code it produced.
This phenomenon seems to be occurring across the knowledge work industries, not only in the software industry. Knowledge professionals “think for a living,” and the quality of their work directly depends on their knowledge and expertise of the subject matter. Junior lawyers need to practice writing legal drafts. Junior copywriters gain experience through numerous rounds of editing. Junior educators discover their voice and perspective by repeatedly teaching the same information from different perspectives. Research-backed science now shows ample evidence that critical thinking and cognitive abilities are being eroded by GenAI apps. The machines are learning how to think and act better, leaving the humans behind to do the mundane.
Companies powering the GenAI bubble, like Alphabet (which recently joined the ranks), Apple, Nvidia, and Microsoft, are now worth trillions of dollars. Significant investments are being made in AI around the world by companies and nation-states alike. Most people seem to be working under a theory of trickle-down AI economics, where investments in large conglomerates powering AI will eventually trickle down and create value for all of us. Yet, when was the last time you experienced lasting value from GenAI?
The writer is CEO, FOSS United
Share
