When Eliza, the first AI chatbot to speak, launched in 1973, it ushered in an era of fascination with artificial intelligence. Over the next decade, scientists developed computer programs that could perform more complex tasks than a human, from chess to medical diagnosis. But these early successes did little to make the general public aware of the potential for revolutionary change posed by AI.
That changed when chess champion Garry Kasparov was soundly defeated by IBM’s Deep Blue supercomputer in 1997. The resulting media coverage of the landmark win allowed non-technologists to understand the speed and sophistication of AI.
Since then, the industry has raced to develop the next big thing in AI. Many have come close.
Today’s large language models, for example, are capable of producing accurate, human-like responses to almost any question. They can also translate text, create essays and articles, and generate ideas from nothing.
What is missing, however, is an understanding of how these systems actually work. For most, that is the most challenging aspect of the emerging field.
A new generation of generative AI will bring about a wide range of transformations in both our daily lives and the workplace. But this technology can pose challenges, including increased automation leading to job loss, the possibility of bias or discrimination based on the data sets on which the AI is trained, and the potential for it to replace human judgment in some situations. The Hackett Group brought together business leaders, industry peers and Gen AI experts to share perspectives on leveraging generative AI for breakthrough performance.