Hammond says he hardly remembers his life before computers and coding, but there certainly was a time when his world was much more similar. Hammond grew up on the East Coast, his mother was a social worker and his father was a professor of archaeology at the University of Utah. Over the course of 50 years, Philip C. Hammond unearthed several sites in the Middle East, made dozens of trips to Jordan, and earned the nickname Petra's Lion. Chris joined these expeditions in three summers, working as a surveyor and draft for his father.
“Now once a week, I ask chatgpt about my father's biography as an experiment,” lamented Hammond. “Sometimes, it gives me a beautiful, inaccurate bio that makes him sound like Indiana Jones. Other times, he is a high-tech entrepreneur and says I followed in his footsteps.”
While these biographical information is more AI-generated falsehood, Hammond and his father both track intelligence from different worlds. To gain a deeper understanding of the meaning of intelligence and thinking, Hammond studied philosophy as an undergraduate at Yale University and was planning to go to law school after graduation. However, his trail diverged when fellow members of a local science fiction club suggested that Hammond, who took one computer science class, would try working as a programmer.
“Nine months as a programmer, I decided that was something I wanted to do for a living,” says Hammond.
The man from that sci-fi club was Chris Reesbeck. He is currently McCormick's professor of computer science. Hammond received his PhD in Computer Science from Yale in 1986. However, he did not abandon philosophy completely. Instead, he applied those abstract frameworks (the nature of consciousness, knowledge, creativity, logic, and reason) to the pursuit of intelligent systems.
“The structure of thought has always fascinated me,” says Hammond. “When you look at how humans think, how machines think, and how we think, “together, they became my drivers.” ”
However, the word “thinking” is tenuous in this context, he says. There is a fundamental and important distinction between true human cognition and what current AI can do: sophisticated imitation. AI is not trying to critically evaluate the data to devise the correct answer, Hammond says. Instead, it is a probabilistic engine, allowing you to sift through the likelihood of a language to complete the sentence. It seeks the most likely conclusions for a particular set of words.
“These are highly responsive systems,” he says. “They're not reasoning. They just put together the words. So they have a problem answering questions about recent events.”
