ChatGPT vs Hybrids: The future depends on our choices  

ON MARCH 29, some 1,000 AI funders, engineers and academics issued an open letter calling for an immediate pause on further development of certain forms of generative AI applications, especially those similar in scope to ChatGPT. With irony, some of the letter’s signatories are engineers employed by the largest firms investing in artificial intelligence, including Amazon, DeepMind, Google, Meta and Microsoft.

This call for reflection came in the wake of overwhelming media coverage of ChatGPT since the chatbot’s launch in November 2022. Unfortunately, the media often fails to distinguish between generative methodologies and artificial intelligence in general. While various forms of AI can be dated back to before the Industrial Revolution, the decreasing cost of computing and the use of public domain software have given rise to more complex methods, especially neural network approaches. There are many challenges facing these generative AI methodologies, but also many possibilities in terms of the way we (humans) work, learn or access information.

Insead’s TotoGEO AI lab has been applying various generative methodologies to business research, scientific research, educational materials and online searches. Formats have included books, reports, poetry, videos, images, 3D games and fully scaled websites.