Follow this author to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Philip Colligan's greatest fear is that parents and educators will treat the AI revolution the way they treated the advent of the Internet--which is to say, they won't engage in teaching children how to responsibly use it until it's too late. "We are in the middle of those systems being introduced into healthcare, finance, criminal justice decisions, education decisions," the CEO of the Cambridge, U.K-based tech-literacy educational nonprofit Raspberry Pi Foundation says.

At the Raspberry Pi Foundation, we've been thinking about questions relating to artificial intelligence (AI) education and data science education for several months now, inviting experts to share their perspectives in a series of very well-attended seminars. At the same time, we've been running a programme of research trials to find out what interventions in school might successfully improve gender balance in computing. We're learning a lot, and one primary lesson is that these topics are not discrete: there are relationships between them. We can't talk about AI education -- or computer science education more generally -- without considering the context in which we deliver it, and the societal issues surrounding computing, AI, and data. For this International Women's Day, I'm writing about the intersection of AI and gender, particularly with respect to gender bias in machine learning.

AI is a broad and rapidly developing field of technology. Our goal is to make sure all young people have the skills, knowledge, and confidence to use and create AI systems. So what should AI education in schools look like? To hear a range of insights into this, we organised a panel discussion as part of our seminar series on AI and data science education, which we co-host with The Alan Turing Institute. You can also watch the recording below.

A recent Forbes article reported that over the last four years, the use of artificial intelligence (AI) tools in many business sectors has grown by 270%. AI has a history dating back to Alan Turing's work in the 1940s, and we can define AI as the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Four key areas of AI are machine learning, robotics, computer vision, and natural language processing. Other advances in computing technology mean we can now store and efficiently analyse colossal amounts of data (big data); consequently, data science was formed as an interdisciplinary field combining mathematics, statistics, and computer science. Data science is often presented as intertwined with machine learning, as data scientists commonly use machine learning techniques in their analysis.

Video: How to set up your Raspberry Pi 3 Model B . Besides putting a Raspberry Pi to work on a mini Mars rover, it's now going to be a lot easier to use Google's TensorFlow artificial-intelligence framework with the low-powered computer. Developers with Raspberry Pi have already been able to use TensorFlow in a variety of ways to add deep-learning models so that cheap or expensive hardware can do things like image classification. While TensorFlow can be used on Linux, Windows, Android, macOS, and iOS, it's hard to find cheaper hardware than the $35 Raspberry Pi. But as noted by Pete Warden, a software engineer and lead of the TensorFlow mobile and embedded team, running TensorFlow on Raspberry Pi "has involved a lot of work".

Last year Google partnered with the Raspberry Pi Foundation to survey users on what would be most helpful in bringing Google's artificial intelligence and machine learning tools to the Raspberry Pi. Now those efforts are paying off. Thanks to Colaboratory – a new open-source project from Google – engineers, researchers, and makers can now build and run machine learning applications on a simple single-board computer. Google has officially opened up its machine learning and data science workflow – making learning about machine learning or data analytics as easy as using a notebook and a Raspberry Pi. Google's Colaboratory is a research and education tool that can easily be shared via Google's Chrome web browser.

Google is planning to bring artificial intelligence and machine learning tools to the Raspberry Pi. The low-cost credit-card sized computer is widely used by schools and the maker community for programming devices. Google has asked makers to complete a survey about what smart tools would be "most helpful". And it suggests tools to aid face and emotion recognition, speech-to-text translation, natural language processing and sentiment analysis. Google has previously developed a range of tools for machine learning, internet of things devices, wearables, robotics and home automation.