Rida Qadri ( ridaqadri@google.com) is a senior research scientist at Google Research, Mountain View, CA, USA. Michael Madaio ( madaiom@google.com) is a senior research scientist at Google Research, New York, NY, USA. Mary L. Gray ( mlg@microsoft.com) is a senior principal researcher at Microsoft Research, Cambridge, MA, USA.

This might sound like a hot take but it's not: In 50 years, when historians look back on the crazy 2020s, they might point to advances in artificial intelligence as the most important long-term development of our time. We are building machines that can mimic human language, human creativity, and human thought. What will that mean for the future of work, morality, and economics? Bestselling author Steven Johnson joins the podcast to talk about the most exciting and scary ideas in artificial intelligence and an article he wrote for The New York Times Magazine about the frontier of AI.

Everyone working in the autonomous vehicle space said it was inevitable. In America--and in the rest of the world--cars kill people, around 40,000 in the US and 1.25 million in the globe each year. Self-driving cars would be better. But no one promised perfection. Still, the death of Elaine Herzberg, struck by a self-driving Uber in Tempe, Arizona, two weeks ago, felt like a shock.

John Lynn is the Founder of the HealthcareScene.com These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn. It seems like these days every healthcare IT company out there is saying they're doing machine learning, AI, deep learning, etc.

Task instruction quality is widely presumed to affect outcomes, such as accuracy, throughput, trust, and worker satisfaction. Best practices guides written by experienced requesters share their advice about how to craft task interfaces. However, there is little evidence of how specific task design attributes affect actual outcomes. This paper presents a set of studies that expose the relationship between three sets of measures: (a) workers’ perceptions of task quality, (b) adherence to popular best practices, and (c) actual outcomes when tasks are posted (including accuracy, throughput, trust, and worker satisfaction). These were investigated using collected task interfaces, along with a model task that we systematically mutated to test the effects of specific task design guidelines.