Algorithms are shaping our lives – here’s how we wrest back control

[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Kartik Hosanagar on the growing power and sophistication of algorithms. In this episode of the Data Show, I spoke with Kartik Hosanagar, professor of technology and digital business, and professor of marketing at The Wharton School of the University ofContinue reading “Algorithms are shaping our lives – here’s how we wrest back control”

You created a machine learning application. Now make sure it’s secure.

[A version of this post appears on the O’Reilly Radar.] The software industry has demonstrated, all too clearly, what happens when you don’t pay attention to security. By Ben Lorica and Mike Loukides. In a recent post, we described what it would take to build a sustainable machine learning practice. By “sustainable,” we mean projectsContinue reading “You created a machine learning application. Now make sure it’s secure.”

Why your attention is like a piece of contested territory

[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: P.W. Singer on how social media has changed, war, politics, and business. In this episode of the Data Show, I spoke with P.W. Singer, strategist and senior fellow at the New America Foundation, and a contributing editor at Popular Science.Continue reading “Why your attention is like a piece of contested territory”

How AI can help to prevent the spread of disinformation

[This post originally appeared on Information Age.] Our industry has a duty to discuss the dark side of technology. Yet many organisations — including some that wield enormous power and influence — are reluctant to acknowledge that their platforms are used to spread disinformation, foster hatred, facilitate bullying, and much else that makes our worldContinue reading “How AI can help to prevent the spread of disinformation”

The evolution and expanding utility of Ray

[A version of this post appears on the O’Reilly Radar.] There are growing numbers of users and contributors to the framework, as well as libraries for reinforcement learning, AutoML, and data science. In a recent post, I listed some of the early use cases described in the first meetup dedicated to Ray—a distributed programming frameworkContinue reading “The evolution and expanding utility of Ray”

The technical, societal, and cultural challenges that come with the rise of fake media

[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Siwei Lyu on machine learning for digital media forensics and image synthesis. In this episode of the Data Show, I spoke with Siwei Lyu, associate professor of computer science at the University at Albany, State University of New York. LyuContinue reading “The technical, societal, and cultural challenges that come with the rise of fake media”

Using machine learning and analytics to attract and retain employees

[A version of this post appears on the O’Reilly Radar blog.] The O’Reilly Data Show Podcast: Maryam Jahanshahi on building tools to help improve efficiency and fairness in how companies recruit. In this episode of the Data Show, I spoke with Maryam Jahanshahi, research scientist at TapRecruit, a startup that uses machine learning and analytics to helpContinue reading “Using machine learning and analytics to attract and retain employees”

How machine learning impacts information security

[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Andrew Burt on the need to modernize data protection tools and strategies. In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer and legal engineer at Immuta, a company building data management tools tuned forContinue reading “How machine learning impacts information security”