Co-Intelligence: Living and Working with AI

That feedback is then used to do additional training, fine-tuning the AI’s performance to fit the preferences of the human, providing additional learning that reinforces good answers and reduces bad answers, which is why the process is called Reinforcement Learning from Human Feedback (RLHF).

The search for high-quality content for training material has become a major topic in AI development, since information-hungry AI companies are running out of good, free sources.

We have invented technologies, from axes to helicopters, that boost our physical capabilities; and others, like spreadsheets, that automate complex tasks; but we have never built a generally applicable technology that can boost our intelligence.

Early studies of the effects of AI have found it can often lead to a 20 to 80 percent improvement in productivity across a wide variety of job types, from coding to marketing. By contrast, when steam power, that most fundamental of General Purpose Technologies, the one that created the Industrial Revolution, was put into a factory, it improved prod

ChatGPT reached 100 million users faster than any previous product in history, driven by the fact that it was free to access, available to individuals, and incredibly useful.

General Purpose Technologies typically have slow adoption, as they require many other technologies to work well. The internet is a great example. While it was born as ARPANET in the late 1960s, it took nearly three decades to achieve general use in the 1990s, with the invention of the web browser, the development of affordable computers, and the gr

AI is what those of us who study technology call a General Purpose Technology (ironically, also abbreviated GPT). These advances are once-in-a-generation technologies, like steam power or the internet, that touch every industry and every aspect of life. And, in some ways, generative AI might even be bigger.

Innovation has been slowing alarmingly in recent decades. In fact, a recent, convincing, and depressing paper found that the pace of invention is dropping in every field, from agriculture to cancer research. More researchers are required to advance the state of the art. In fact, the speed of innovation appears to be dropping by 50 percent every 13

In field after field, we are finding that a human working with an AI co-intelligence outperforms all but the best humans working without an AI. In our study of Boston Consulting Group, where previously the gap between the average performances of top and bottom performers was 22 percent, the gap shrank to a mere 4 percent once the consultants used G