When AI is equated with human intelligence, innovation suffers. While artificial intelligence can help to improve our world, many people believe the myth that it can reach beyond the limits of its programming. Andrew McDiarmid, senior fellow at Discovery Institute, discusses the limitations and dangers of AI with Erik Larson, author of the new book The Myth of Artificial Intelligence. Read More ›
Here at Mind Matters, we have often covered the way that humans are used to supplement Artificial Intelligence. Artificial intelligence has generally been misunderstood as replacing human effort in society, while, in reality, it is usually leveraging it, instead. Whether using humans to find good training data, mining content for intentionality, or even using humans directly within machine learning algorithms, today’s most prominent “AI” systems are actually strange hybrids of humans and computers. As a matter of fact, the market for human supplementation of AI is so large that Amazon has an entire service built around it. While much of this work is done either for free (oftentimes through games on the Internet) or through traditional paid office work, a growing amount is being done through “microtasks,” through systems Read More ›
There’s a lot of exciting stuff going on in the world of artificial intelligence, and while it can be hard to pick a favorite, the Bradley Center Brain Trust rounded out 2020 by narrowing it down to their top ten. Join us as we revisit those top ten stories with Robert J. Marks, Jonathan Bartlett, and Eric Holloway. Show Notes Read More ›
To get the right answer to the question of whether artificial intelligence will ever become capable of replacing man we must get the ontology, epistemology, and metrology right. Ontology seeks to understand the essential nature of things and the relationships between different things. Epistemology looks at what we can know and how accurately we can know what is knowable. Finally, metrology explores how we make measurements and comparisons. To get the right answer we must measure the right things (ontology), select what we will measure (epistemology), and determine how we make our measurements and comparisons with accuracy, precision, and repeatability (metrology). Mistakes in any of these areas will lead to a bad outcome. A common mistake is to measure what Read More ›