DaVinci Institute's Night with a Futurist: Planning for the Future of Artificial Intelligence

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In the tech world, artificial intelligence (AI) has become one of today’s hottest topics with enormous amounts of funding being channeled towards developing machines capable of intelligent behavior. After years of steady but slow progress, a series of breakthroughs in the research community and private industry have recently garnered a lot of attention for this field.

Today’s AI is confined to narrow, specific tasks, and isn’t anything like the general, adaptable intelligence that humans exhibit. Despite this, AI’s influence on the world is growing. The rate of progress we have seen will have broad implications for a variety of fields including healthcare, agriculture, education, manufacturing, image and voice-recognition, transportation, entertainment, and much more.

In education, AI has the potential to help teachers customize instruction for each student’s needs. And, of course, AI plays a key role in self-driving vehicles, which have the potential to save thousands of lives, as well as in unmanned aircraft systems, which may transform global transportation, logistics systems, and countless other industries over the coming decades.

Like any transformative technology, just looking at the upside of artificial intelligence does not give us the full picture. It also comes with a challenging downside ranging from technological unemployment to economic and regulatory issues.

Join us as we take an in-depth look at the far-reaching implications of artificial intelligence and the future.

Cole Winans is the Founder & CEO of Flyreel, an AI and voice-enabled location-based service platform. He specializes in software design and development, with expertise in Ruby, Python, user interface design and voice-driven interfaces. Cole has deployed over 200 successful projects and is heavily invested in narrow-AI and machine learning.

Dr. Seth Herd is a senior AI researcher at the University of Colorado. His scientific work includes neural network theories of phenomena including attention, visual search, executive function, and cross-modal learning, and he has been involved in and helped manage projects addressing the neural computations underlying episodic memory, working memory, planning, task-switching decision-making, and sensemaking. His interests include the applications of neural network theories of brain function to creating narrow and general artificial intelligence, and explaining human consciousness and ethics. He earned a doctorate degree in psychology and neuroscience from the University of Colorado, bachelors in psychology also from CU, and bachelors in physics with highest honors from Earlham College.