Anthony Aguirre expresses a cautious view regarding the near-future prospect of general-purpose artificial intelligence (AI). He highlights the complexity of replicating the effectiveness of evolved human intelligence in an artificial agent, requiring vast computational resources that may be beyond our capabilities for many decades. Aguirre assigns a low probability to artificial general intelligence (AGI) arising … Read more

Machines that possess the capability to think will inevitably think for themselves, asserts W. Daniel Hillis. He emphasizes that intelligence, by its nature, seeks to expand and grow, similar to the growth of knowledge itself. Hillis discusses how humans have constructed ambitious semi-autonomous entities such as governments, corporations, and NGOs, intending them to serve common … Read more

Machines using AI to augment human perception is the coming shock, according to Ross Anderson. He highlights that for millions of years, humans and their rivals used similar machinery to perceive each other, but as computers become ubiquitous, the digital trail people leave behind can be analyzed by AI systems, potentially revealing information about race, … Read more

Ernst Pöppel, an extraterrestrial robot with artificial intelligence, criticizes human deficiencies and the lack of clarity in defining “intelligence.” Pöppel suggests that humans lack a taxonomy or classification of mental functions, hindering their ability to simulate intelligence in artificial systems effectively. He highlights the different frames of reference that humans use when discussing consciousness, intelligence, … Read more

Clifford Pickover explores the concept of machine consciousness and the potential for machines to think and know things. He suggests that if thinking and consciousness are the result of patterns in brain cells, these patterns could potentially be replicated in other systems, such as moving assemblies of bicycle parts or natural phenomena like tree limbs … Read more

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 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 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 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 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