machine learning tags

Bull Session

The Pitfalls of Predicting AI

November 2, 2018          

Episode Summary

This week on The Digital Life, we discuss the pitfalls of predicting AI. AI predictions range from the measured and meaningful to highly unrealistic and downright hysterical. But how can you tell the difference? In this episode, we dig into some rules of thumb for thinking through the AI predictions we encounter, as laid out in the article “The Seven Deadly Sins of AI Predictions” by Rodney Brooks, a founder of Rethink Robotics. From better understanding the properties of narrow AI to asking “how will it be deployed?”, questioning supposed magical properties without limit, to admitting, in the long term, we just don’t know, we’ll explore the many factors that counter the breathless hysteria of AI predictions. Join us as we discuss.

Resources:
The Seven Deadly Sins of AI Predictions

Bull Session

AI and Science

October 12, 2018          

Episode Summary

This week on The Digital Life, we discuss the intersection of artificial intelligence and science with special guest is Dany DeGrave, founder of Unconventional Innovation. AI and science are coming together in new and significant ways, including the use of cognitive and other innovative technologies in R&D — like NLP, machine learning, and advanced analytics. As bio-science companies rush to invest in AI, the implementation of scientific research, drug trials, and even personalized medicine is undergoing significant change. But with the potential to make erroneous decisions, and even be used for malicious purposes, it may be a long time before we fully trust AI to be used in such development.

Bull Session

Digital Disguises and Facial Recognition

July 6, 2018          

Episode Summary

On the podcast this week, we examine facial recognition software and digital disguises. It seems like AI-driven facial recognition systems are just about everywhere—from the face-scanning technologies for law enforcement and government to everyday social media tagging. Tools like these can be used for the public good or harm. And there’s no doubt that we’re concerned about facial recognition surveillance encroaching on our personal privacy. While clothing like glasses, hats, or even masks can somewhat inhibit facial recognition, it’s not a huge surprise that disguises of a digital nature, anti-facial-recognition systems, are on the rise as well. For example, researchers at the University of Toronto have developed software to hinder facial recognition using an algorithm that slightly alters the images. And while humans can’t really tell the difference, an AI that scans a photo altered in this way, won’t be able to identify a face. Join us as we discuss.

Resources:
This Filter Makes Your Photos Indecipherable to Facial Recognition Software

Bull Session

Automate

January 26, 2017          

Episode Summary

On this episode of The Digital Life, we discuss workplace automation and the technologies that will make it happen — from robotics to artificial intelligence (AI) to machine learning. The McKinsey Global Institute released a new study on the topic this month, “A Future that Works: Automation, Employment and Productivity”, which contains some interesting insights.For instance, almost every occupation has the potential to be at least partially automated, and it’s likely that more occupations will be transformed than automated away. However, people will need to work in conjunction with machines as a part of their day-to-day activities, and in this new age of automation, learning new skills will be critical.Add to this the fact that working-age population is actually decreasing in many countries, and we can see how the story of automation is multi-faceted. The path to automating the workplace is a complex one that could raise productivity growth on a global scale.

 
Resources:
Report – McKinsey Global Institute: Harnessing automation for a future that works