ChatGPT: End of the Road or Beginning of a New Era for Knowledge Workers?

I recently had the honor of moderating a debate at Digital Research Company ( DRC | ?? ?? ?? ) about how #chatgpt would impact knowledge workers in the future. The session began with a live demonstration of ChatGPT's abilities.?We then had a captivating discussion with diverse viewpoints. While everyone agreed that ChatGPT's capabilities are impressive, especially in quickly gathering and presenting existing knowledge, the group concluded that the arrival of AI powered chatbots does not signal the end of the road for knowledge workers. Rather, it heralds the beginning of a new era, where they can be liberated from the drudgery of boring and repetitive tasks and focus on what knowledge workers are actually supposed to do: creative thinking, problem solving and generating new ideas.

The discussion made me reflect on my own personal experiences of how technological advances over the last 50 years have transformed the nature of the knowledge work.

As a child in the 1970s, I often wondered what my parents and their colleagues - all of them engineers - were up to when they spent days holed up in a room, seemingly engaged in some mysterious routine. They were surrounded by stacks of paper, with their desks covered in strange drawings. I observed them drinking endless cups of coffee while muttering seemingly random numbers to odd-looking toys they couldn't seem to put down. Later, I came to understand that these strange devices were tools used for calculations: a slide rule and a mechanical calculator that required one to press hard on the numbers and produced answers with a whirring sound after turning a handle. I knew very well not to interrupt them and walk around in tip toes when they were deep in concentration with their magical tools. Any mistake could cost them days of rework. It was also made clear to me that if one day I wanted to be a successful engineer, I needed to be really good at crunching numbers. ?

Not much had changed by the time I began preparing for my engineering education. Though scientific calculators were becoming more common and affordable by the time I reached my senior years of school, we still had to manually perform complicated calculations using only logarithmic tables for support to prove our aptitude for engineering.

However, the era of manual calculation orthodoxy slowly gave way to advancing technology. By the time I entered engineering school, I was the proud owner of a sleek new Casio scientific calculator. I used it so much that by the end of the second semester, all the numbers on the keys had worn off. For more complex and repetitive calculations, such as analyzing 50 years of hydrological data on a river, we had access to the mainframe computer. However, this meant entering all the data and code into punch cards, sending them for processing, and patiently waiting for two days to receive a huge bed-sheet sized printouts of the calculations, which usually contained many error messages (For those of you fortunate enough to be unfamiliar with the term, punch cards are pieces of stiff paper with holes used to store information for computer before the arrival of magnetic storage devices such floppy discs and pen drives). We then spent our days scrutinizing the holes in the punch cards against a light and comparing them with the printout to find and fix errors, hoping that in the next iteration, the ‘bedsheet’?would come back with the right answers.

In those days, being a successful engineer definitely meant having the skill to handle punch cards, examine their holes, and, of course, produce flawless engineering drawings on a drafting board. Having gone through it myself, I am only too familiar with the pain that accompanies the phrase 'going back to the drawing board.' It seemed that patience was key to successful career in engineering. ?

Everything changed with the arrival of mini computers - suddenly there was no longer a need to painfully check the punch cards. We could type in the code and see the results in real time. Of course, debugging was still required, but it was faster and more effective. And soon there were programs available to do the engineering drawings. We were finally free from the drudgery of number crunching and drawing. With more time available, we were able to focus on creative and innovative tasks, such as designing the best dam and power plant. I could come up with ten different options for building a power plant on a river in a fraction of the time it used to take me to produce a mediocre design using my old friends: the scientific calculator, the draft board, and the punch card.

In late 80s, my life took a very different turn as I drifted from the fascinating world of power plants, transmission lines, coding, and number crunching to enter the exciting world of business. After about a decade of running businesses, I eventually gravitated back to the world of knowledge work. I completed my MBA and worked as a management consultant before moving on to coach and advise senior leadership teams, and becoming a scholar leadership of strategic change. I was also fortunate to be able to complete a doctorate on the topic I'm so passionate about.

But, as in the world of engineering, I found that in the world of consulting and scholarship, the work involved moments of inspiration (when conducting primary research and creating new ideas), accompanied by long periods of perspiration (associated with endless iterations of writing, rewriting, and secondary research_. Just as the ability to patiently crunch through a large volume of numbers was a prerequisite for becoming a good engineer, the ability to elegantly write up ideas in text and slides was a prerequisite for becoming a successful consultant and scholar. In some instances, style appeared to trump substance. The underlying notion was that an idea only became valuable if it was presented elegantly, and if one was not able to produce a polished write-up, their ideas were not worth considering. This painful reality is summed up by Shashi Mudunuri , the founder of AJE, who mentions that the fact that his father had to abandon his research career due to issues with communicating his ideas in academic writing inspired him to found a company that specialized in editing support for academics.

But with the arrival of ChatGPT, a lot of the monotony of spending endless hours rewriting things and packaging ideas into an elegant text and doing secondary research can be delegated to the chatbot. It does the boring leg work for you and your job is to guide it in the right direction and check its quality. It frees up time for things that add value - thinking, coming up with ideas, creating new knowledge. Out of curiosity, I asked ChatGPT to help me with a paper on a topic similar to one that I had just finished working on. Did it do a good job? Yes and no. ChatGPT was very good at consolidating existing knowledge and presenting it in well-written academic language. However, when it came to creating new insights from the data, ChatGPT sometimes produced odd results. Nevertheless, having ChatGPT to assist me would have freed up a substantial amount of time to focus on more value-adding tasks, such as primary research, analysis, and generating new ideas.

So, as far as I’m concerned, I don’t think that the arrival of AI-powered chatbots such as ChatGPT is the end of the road for a knowledge worker. On the contrary, it will actually transform our work and make it more meaningful and exciting by freeing us from the drudgery of being calculators, number crunchers, coders, error-checkers, drafters, slide producers, report writers and copy editors. We will have more time and energy to do what we are really supposed to be doing : being original thinkers and creating new knowledge.

Of course, if someone is in the business of repackaging existing ideas and selling glorified common sense as gold dust, there’s definitely ‘end of the road’ sign ahead for them. They may want to look for some other business models,?perhaps?asking ChatGPT?the question?about what they should be doing next.