Since humans first envisaged the concept of an artificial intelligence – from Fritz Lang’s dystopian ‘Metropolis’, HAL 9000’s chilling homicidal tendencies in ‘2001: A Space Odyssey’, the cheeky Johnny 5 of ‘Short Circuit’ fame, to the kitsch Robin Williams in ‘Bicentennial Man’ and the more recent hosts of ‘Westworld’, and the synths of ‘Humans’, we’ve imagined a gamut of possible scenarios of how man and machine might evolve together.

While the storylines explores in each of these science fiction works differ, there is one element they have in common; artificial intelligence is going to leave an indelible mark across all of society. Those effects are likely to be seen sooner rather than later as advancements in machine learning, neural networks and related technologies gather speed. At the same time, the general understanding of people around artificial intelligence and machine learning remains rudimentary at best.

To address this, Mozilla, the makers of Common Voice and DeepSpeech, in collaboration with several philanthropic foundations, have recently announced significant funding for people and projects that examine the effects of AI on society. The total pool of funds available is $USD 225k, with up to $USD 50k on offer for each project. The funding is competitive, so if you’re interested, you should definitely read the Application Guide and sign up for the information seminar on June 18th.

In the words of Mozilla;

“Specifically, we’re seeking projects that explore artificial intelligence and machine learning. In a world where biased algorithms, skewed data sets, and broken recommendation engines can radicalize YouTube users, promote racism, and spread fake news, it’s more important than ever to support artwork and advocacy work that educates and engages internet users. We will consider projects that are at either the conceptual or prototype phases. All projects must be freely available online and suitable for a non-expert audience. Projects must also respect users’ privacy.”

So, what are you waiting for?

Perhaps you could explore gender representation in voice datasets? More than ever, women around the world are finding their metaphorical voice – is this change reflected in speech recognition software?

An artwork representing what role your voice assistant plays in your life?

A video showing the impacts of biased or skewed training data on machine learning algorithms?

These are just suggestions – we’re sure you’ve got plenty of your own ideas!

Contribute to the discussion on the forum.