magine a group of young men gathered at a picturesque college campus in New England, in the United States, during the northern summer of 1956.
It’s a small casual gathering. But the men are not here for campfires and nature hikes in the surrounding mountains and woods. Instead, these pioneers are about to embark on an experimental journey that will spark countless debates for decades to come and change not just the course of technology – but the course of humanity.
Welcome to the Dartmouth Conference – the birthplace of artificial intelligence (AI) as we know it today.
What transpired
Here would ultimately lead to ChatGPT and the many other kinds of AI which now help us diagnose disease, detect fraud, put together playlists and write articles (well, not this one). But it would also create some of the many problems the field is still trying to overcome. Perhaps by looking back, we can find a better way forward.
The summer that changed everything
In the mid 1950s, rock’n’roll was taking the world by storm. Elvis’s Heartbreak Hotel was topping the charts, and teenagers started embracing James Dean’s rebellious legacy.
But in 1956, in a quiet corner of New Hampshire, a different kind of revolution was happening.
The Dartmouth Summer Research Project on Artificial Intelligence, often remembered as the Dartmouth
Conference, kicked off on June 18 and lasted for about eight weeks. It was the telegram database users list brainchild of four American computer scientists – John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon – and brought together some of the brightest minds in computer science, mathematics and cognitive psychology at the time.
These scientists,
Along with some of the 47 people they invited, set out to tackle an ambitious goal: to make intelligent machines.
As McCarthy put it in the conference what type of house is best for a hurricane proposal, they aimed to find out “how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans”.
Five elderly men standing loan data on a stage in front of a commemorative plaque
Trenchard More, John McCarthy, Marvin Minsky, Oliver Selfridge and Ray Solomonoff were among those who attended the Dartmouth Conference on artificial intelligence in 1956. Joe Mehling, CC BY
The birth of a field – and a problematic name
The Dartmouth Conference didn’t just coin the term “artificial intelligence”; it coalesced an entire field of study. It’s like a mythical Big Bang of AI – everything we know about machine learning, neural networks and deep learning now traces its origins back to that summer in New Hampshire.
But the legacy of that summer is complicated.
Artificial intelligence won out as a name over others proposed or in use at the time. Shannon preferred the term “automata studies”, while two other conference participants (and the soon-to-be creators of the first AI program), Allen Newell and Herbert Simon, continued to use “complex information processing” for a few years still.
But here’s the thing: having settled on AI, no matter how much we try, today we can’t seem to get away from comparing AI to human intelligence.
This comparison is both a blessing and a curse.
On the one hand, it drives us to create AI systems that can match or exceed human performance in specific tasks. We celebrate when AI outperforms humans in games such as chess or Go, or when it can detect cancer in medical images with greater accuracy than human doctors.
On the other hand, this constant comparison leads to misconceptions.
When a computer beats a human at Go, it is easy to jump to the conclusion that machines are now smarter than us in all aspects – or that we are at least well on our way to creating such intelligence. But AlphaGo is no closer to writing poetry than a calculator.