A link to the event WebEx will be provided to registered attendees via e-mail the day of the event.

There has been much talk over the last few years about the perils of the use of artificial intelligence in virtually everything we touch. From our phones to our cars, and everything in between, artificial intelligence is an integral part of our existence. Many prominent people, like Elon Musk and Stephen Hawking, have warned about the potential for machines to take over and cause havoc in the lives and very existence of humans. Hollywood has made untold billions of dollars painting doom- and- gloom scenarios about artificial intelligence and robots within our society today and in the future. But what is the true reality? We continually push to create increasingly intelligent systems/machines that attempt to learn, think, and reason like humans. Therefore, our first question becomes, when presented with this challenge is:

Which types of people do we want robots to learn, think, and reason like?

Do you want a Stephen Hawking? Do you want a Charles Manson? Do you want any of a host of past or current world dictators? All these people learn and think and reason, but all of them do it very differently from one another. To say you want a system that learns, thinks, and reasons like people is to say you want to give the computer/robot the ability to self-adapt, to create (through experience and learning) an adult intelligence and capabilities that is people-like in nature. No matter which “version” of human thinking and reasoning is desirable, the main question to be asked is:

“How do we test it to know if the AI system is working correctly?”

The fundamental problem with testing learning, thinking, reasoning, artificial intelligent systems is:

“What does it mean for it to work correctly?”

Upon reviewing the limitations of classical system test theory and implementations, we begin to understand the conundrums of applying these well-known processes for testing AI systems. This presentation will explore the new world of “AI Psychology” to understand where we may or may not be headed as we continually improve upon artificial intelligence technologies.