Artificial Intelligence / Machine Learning

How can businesses protect sensitive user data to foster trust among consumers? How can they design products and tools that avoid racial, gender, and other biases towards users? How should they decide who uses their products, and for what purpose? The answers to these and other questions are especially pertinent to the developers of artificial […]

Technologists, managers, and policymakers all have a seat at the table here. Assembly, a collaboration of the Berkman Klein Center for Internet & Society at Harvard and the MIT Media Lab, is about creating space for cross-sector teams to crack the code to some of AI’s toughest ethical and governance problems — problems that would otherwise fall out of reach.

The current intense focus on machine learning’s biases is crucial because the issue is not only real, it’s rooted in machine learning’s essence: ML constructs models based on the data we feed it, and unless great care is taken, that data will reflect existing biases. But, focusing on fairness is not enough when addressing the […]

In India, approximately 74,000 women die from cervical cancer every year, accounting for 1/3rd of the burden of cervical cancer deaths globally. Less than 10,000 pathologists must service a population of 1.3 billion people. Efforts to increase the number of trained specialists has had limited success, leaving these cancers largely undiagnosed.

Machine learning is a popular topic in most industries these days, and it will come as no surprise that this is true for astronomy and astrophysics as well. University of Colorado PhD student Avery Schiff explores how a deep learning algorithm is being used to classify galaxy morphologies in this article from graduate student astronomy journal Astrobites.

Technological advancements have made it possible to imagine sports competitions of a very different variety than those we enjoy today. With so many avenues of entertainment open to us, it begs the question: in the future of sports who will the athletes be, human — or machine?

With the rise of AI-driven personal assistants like Siri and Alexa, chatbots are becoming increasingly ubiquitous, and the market value of chatbots is expected to reach $1.23 billion by 2025. What are the causes and implications of this chatbot boom, and what will it mean for the future of business? Carrie Epstein and Amy Sinensky of Viacom explore the question in this flash talk from Future Assembly 2018.

How can businesses navigate this AI-driven future that we’re all moving towards? In this keynote from our 2018 Digital Transformation Summit, Amy Yu recommends companies focus on three things: data, talent and ethics.

Big data…artificial intelligence…Internet of Things. These technologies have taken their shares of the headlines the past few years, but now machine learning is the buzz. Mike Teodorescu explains how it is changing the lives of consumers and businesses.

Artificial Intelligence is increasingly being deployed in content-related operations such as translation and transcription. Capturing value will depend on four key factors.