Why content scientists are the new rockstars
Peter Thiel, the controversial tech entrepreneur who co-founded PayPal, once called master investor Warren Buffett (92) "the sociopathic grandpa from Omaha" and an example of the "finance gerontocracy". The latter’s investment fund, Berkshire Hathaway, recently held its annual meeting. Buffett and his right-hand man, Charlie Munger (99) were the headliners.
Their shareholders had obviously quite a few questions about artificial intelligence. Munger seemed unimpressed, saying, “I am personally skeptical of some of the hype that has gone into artificial intelligence. I think old-fashioned intelligence works pretty well." But in the meantime, Apple is by far Berkshire Hathaway's most important stock investment, and CEO Tim Cook declared 2 weeks ago that AI is being "seamlessly woven into all products".
What a weird year. Since ChatGPT was launched on November 30 last year, the world has been talking about nothing else. Every presentation I give, every board meeting, every dinner at our home, even conversations with taxi drivers on the way to the airport: it's guaranteed to be about generative AI. BC no longer stands for Before Christ, but for Before ChatGPT.
Last week, I gave a keynote speech for one of the largest private equity players. They had invited their top 400 for the annual strategic conclave and proudly displayed their "private" version of ChatGPT. It was impressive. The company had fed an AI tool with information about all of its deals over the past decades, and with the help of ChatGPT, all employees could produce documents and research reports in no time. The CEO of the company said, "Normally, we would hire McKinsey for that, and it would cost us hundreds of thousands of dollars. Now we can achieve the same thing in minutes instead of weeks, for a fraction of the cost."
The company was also adamant about the use of this internal tool and not the public version of GPT, to ensure that no internal information would ever leak out. The possibilities for unlocking internal knowledge with these types of tools are phenomenal, but nobody wants to see their confidential knowledge appear in the next version of ChatGPT, of course. Information architecture is therefore becoming one of the biggest challenges of the technology.
The new rockstars
A new type of role is emerging in companies; that of content scientist. In recent years, many companies have been looking for data scientists who can collect, filter, and convert transactional data from an organization into valuable insights, helping with important decisions and optimizing customer service.
The content scientist will do something similar, but will not be dealing with numbers in databases. Instead, they will be dealing with information that is scattered throughout the company, in various forms and sources, from Word documents to PDFs and PowerPoints, stored on drives, servers, Google Drives or SharePoints. If you can feed all that content into generative AI in a coherent way, you can make a huge efficiency gain in your company. Believe me, we will all be looking for content scientists in the coming years.
Two days after my keynote speech, I gave a presentation to the leadership of one of the largest law firms. After a heated discussion about ChatGPT and what it could mean for the role of the lawyer, it was clear that the older partners found it only moderately interesting. They were only a few years away from retirement, and the technology would have little impact on their income. The younger partners, however, saw the writing on the wall and expected AI to have a huge impact on the operation of their office, market pricing, and speed of work.
There is a clear law in the world of AI: the older you are, the less you worry about it. But I am firmly convinced that BC will soon seem like ancient history to the majority of the business world.