Joscha Bach (What to think about machines that think)

Joscha Bach explores the evolution of artificial intelligence (AI) and its potential implications for the future. He highlights that AI has made significant progress, and with advancements in hardware and learning paradigms, we are entering a new era of AI research. Bach acknowledges that while AI has not yet achieved the generality of human intelligence, … Read more

Chris DiBona (What to think about machines that think)

Chris DiBona presents a whimsical take on the limitations of biological intelligence and why we shouldn’t be overly concerned about the potential rise of biological intelligences, as illustrated by the 2UR-NG entry in the DeanGhemawat Conversational (DGC) artificial intelligence test. DiBona humorously emphasizes the drawbacks of biological intelligence, highlighting aspects like the slow speed of … Read more

Michael Shermer (What to think about machines that think)

Michael Shermer delves into the contrasting visions of a utopian and dystopian future associated with artificial intelligence (AI). He argues that both of these extreme visions are rooted in a flawed analogy between human nature and computer nature, as well as between natural intelligence and artificial intelligence. Shermer highlights that humans are thinking machines with … Read more

Jonathan Gottschall (What to think about machines that think)

Jonathan Gottschall explores the idea of teaching computers to tell and understand stories, raising questions about the implications of their potential success in storytelling. He emphasizes that learning to tell stories is a deeply human process that involves immersing oneself in great stories to develop an intuitive understanding of storytelling. Humans learn by embracing the … Read more

Peter Norvig (What to think about machines that think)

Peter Norvig discusses the capabilities and concerns surrounding artificial intelligence (AI). He emphasizes that the question “Can machines think?” is less helpful than evaluating what tasks machines can perform effectively. Norvig acknowledges the valid concerns raised by pessimists regarding the safe development of complex AI systems but points out that similar challenges exist in building … Read more

Paul Saffo (What to think about machines that think)

The advancement of artificial intelligence, particularly towards robust AI systems, raises concerns and intriguing possibilities, according to Paul Saffo. Saffo acknowledges that the complexity and rapid pace of technological innovation have made the world increasingly difficult to comprehend and manage. Narrow AI systems are already prevalent in various aspects of our lives, from art creation … Read more

Lawrence M. Krauss (What to think about machines that think)

Lawrence M. Krauss shares his perspective on artificial intelligence and its potential impact. He doesn’t share the concerns of some about AI and instead sees opportunities for improvement and insights into consciousness. Krauss begins by pointing out that creating thinking computers will require a digital architecture different from current computers and that they are unlikely … Read more

William Poundstone (What to think about machines that think)

William Poundstone reflects on the question of whether machines can think and the relevance of that question. He likens it to asking whether submarines can swim, emphasizing that the focus on how closely machine intelligence can duplicate human intelligence might not be the real point. Poundstone acknowledges that machine intelligence can take various directions and … Read more

Brian Knutson (What to think about machines that think)

Brian Knutson explores the concept of agency in machines and why it’s important for humans to consider machines as agents rather than automata. He discusses the distinguishing features of agents, which include the ability to act based on their own agendas, the ability to infer others’ feelings and thoughts, and the presence of specialized neural … Read more