AI Podcast Interviews Articles and Reports

Episode Summary: Cyber security is closely linked to advances in artificial intelligence. In this episode, we speak with Dr. Roman V. Yampolskiy about the cyber security factors and risks associated with AI. How is AI both causing risks, and how can AI be used to combat those risks? We dive briefly into the future to speak about some of the potential 'super' AI risks to cyber security and touch on what can be done now to help hedge known and unknown threats.

Episode Summary: It's common knowledge that scientists study the brain to understand how to replicate intelligence in machines; it's less commonly known that scientists also use machine models to understand how the mind works. In this episode, we talk with Dr. Ashok Goel, a researcher in the field of cognitive systems who sheds light on this idea. Dr. Goel also speaks about his perspective on where machines are becoming more creative, and what the future might look like if machines begin to reflect on their "identities" as humans do.

Episode Summary: Over 100,00 years ago, it may have been advantageous for human beings to be hyper aware of other living things for the purposes of survival. In the future, between the IoT and advances in AI, we once again find ourselves ever more aware. Erik Davis, the author of TechGnosis and a praised journalist and speaker, explores the intersection of the technical, spiritual, and often mystical. In this episode, we discuss how our gut reactions to AI often spring from evolutionary or cultural reasons, and how this shapes our reactions to technology and guides our development of it in the 21st century.

 
Episode Summary:
Most of us can admire AI such as Siri, Watson, and other agents shaping the fabric of future AI-powered entities, but it's also possible to admire them as a “dead end”. Dr. Alexei V. Samsonovich is one researcher who believes that we won't be close to perceiving AI as 'conscious' machines until we can grant them the necessary emotional intelligence. Though a lot of progress has been made in field of intelligent agents in the last 10 years, many researchers who are in the same camp as Samsonovich are now on a mission to develop human-like intelligence, cognitive abilities, emotional and social intelligence, and common sense reasoning.

Episode Summary: Dr. James D. Miller, an Economics and AI researcher who received his doctorate from the University of Chicago, sheds light on how economics factors into our increasingly automated world, where development is growing exponentially. We discuss how this acceleration may (or may not) help materialize the "Singularity", the theorized point at which society is so drastically revolutionized by technologies that we never return to our past ways of life.

Episode Summary: Dr. Danko Nikolic, a scientist at the Max-Planck Institute for Brain Research, asks and works to answer questions about how our physical neuronal connections create the mind's perceptions. In the realm of AI, Danko zones in on learning in a newborn human and compares that to a robot. He asks how we can take human lessons, what’s built into our genome, and apply that to construct a more generally intelligent AI, in a way that is not being done today.

Episode Summary: After receiving her PhD in Computer Science from the University of New York in 2002, Dr. Sheryl Brahnam's research interests steered her toward studying human abuse and misuse with computers, specifically conversational agents such as Siri, phone-based auto agent systems, and even chat support. Her research yields questions in relative new territory: Are AI prone to receiving misuse?; why do people misuse these agents in ways that they would not treat a human?; and, what types of regulations will we need as AI improves and becomes more intelligent?

Episode Summary: Dr. Joscha Bach is a software developer and researcher, who is currently developing a cognitive AI framework at  MIT Media Lab and the Harvard Program for Evolutionary Dynamics. In this episode, he speaks about the troubles in projecting when strong AI may be developed, and sheds light on the trends taking us there, including deep and reinforcement learning.