Welcome to our April 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we hear from our latest new voice in AI, talk about AI images, investigate data justice, and watch an AI system play bridge.
In our latest episode of New voices in AI, we caught up with Maria De-Arteaga who told us about her work and journey into algorithmic fairness and human algorithm collaboration. You can find all episodes in the series here.
In this article, Thom Badings and Nils Jansen write about their work on controllers for autonomous systems that won them, and co-authors Alessandro Abate, David Parker, Hasan Poonawala, and Marielle Stoelinga, a distinguished paper award at AAAI 2022. They propose a method to compute safe controllers for autonomous systems in safety-critical settings under unknown stochastic noise. In contrast to existing methods, this one does not rely on any explicit representation of this noise. Instead, it predicts the outcome of actions based on previous observations of the noise.
The AIhub coffee corner captures the musings of AI experts over a short conversation. This month, we explored the topic of AI images. The representation of AI in the media has long been a problem, with blue brains, white robots, and flying maths featuring heavily. How can we source or design better images for AI? How should AI be represented pictorially in articles, blogs etc? What do we need to consider when thinking about portraying AI in images? Find out what our trustees thought here.
Are you a PhD student or researcher with an interest in science communication? We are recruiting AIhub ambassadors to help us write about the latest news, research, conferences, and more, in the field of artificial intelligence. Find out more here.
The 2022 International Conference on Learning Representations (ICLR) kicked off on 25 April, and the outstanding paper awards were announced shortly before the start of the event. You can find out who won these awards here.
Fans of The Radical AI Podcast will be pleased to know that the show has returned after a short break. In this minisode, hosts Jess and Dylan talk about what they’ve been up to, and look ahead to the new series. You can listen to the first episode of the new series, featuring Alexander Monea, here.
The Advancing Data Justice project is a Global Partnership on AI (GPAI) initiative, led by The Alan Turing Institute. Researchers around the world have been working to understand what data justice might look like in their distinct contexts. As part of the project, the team have recently launched the first instalment of a documentary series which tracks the work of the project partners. Find out more here.
At the end of March it was reported that an AI system from French startup NukkAI had beaten eight world champions at bridge. This has been heralded as an important step, as in bridge (as opposed to games such as chess and Go) players work with incomplete information. The system uses a hybrid of rules-based and deep learning methods. You can watch the recording of the livestream of the challenge in full here.
In this guest post (on Ben Recht’s blog), Deb Raji writes about data and distributions, and how any failure of deployed ML models is often inappropriately characterized as a “distribution shift”. This post forms part of an on-going series from Ben and Deb on validity in machine learning.
A new MIT Technology Review series AI colonialism investigates how AI is enriching a powerful few by dispossessing communities that have been dispossessed before. Karen Hao, Heidi Swart, Andrea Paola Hernández and Nadine Freischlad cover the topic in four articles:
South Africa’s private surveillance machine is fueling a digital apartheid
How the AI industry profits from catastrophe
The gig workers fighting back against the algorithms
A new vision of artificial intelligence for the people.