Visualising AI with Google DeepMind
Shifting dated perceptions of AI in order for everyone to have a say on the future of the technology.
Visualising AI is a Google DeepMind initiative that aims to open up conversations around AI and make it more accessible to the general public by commissioning artists to create open-source imagery. The collection includes 3D works by world-class creators, exploring the roles and responsibilities of AI’s impact on society, from robotics and neuroscience to ethics and safety.
We first got involved with Visualising AI in June of 2022, and as AI continues to grow in popularity and capability, we are excited to share the next phase of the project.
The Project
Popular culture often associates AI with dystopian narratives that exclude the realistic risks and potential rewards of the technology. Visualising AI began as an effort to redress this by commissioning artists to create imagery representing a more multi-dimensional picture of how AI can impact society. The project aims to encourage wider conversations and, in turn, give more people a voice in how the tech is developed.
Visualising AI invites artists to contribute to the growing open-source collection. Each artist takes on a theme to transform into unique imagery. The subject matter includes robotics, neuroscience, ethics, safety, methods of machine learning and more. Experts in these fields are paired with the artists to offer further insight. Crucially, the artists’ process is interference-free. Each artist has the freedom to visualise the themes however they see fit, ensuring the final creations are an authentic reflection of the artist’s interpretation.
All final images are 3D renders by talented humans, not AI-generated.
The Artists
Ariel Lu
Berlin-based 3D-artist, Ariel Lu, visualised two different concepts in relation to AI: Bias Amplification and Data Labelling. Her first series of visuals was inspired by how AI tools can amplify bias and the importance of doing research to mitigate these risks. The second collection represents ethics research aimed at understanding human involvement in data labelling.
Linus Zoll
Linus Zoll is a Berlin-based designer specializing in computer-generated imagery and art direction. For this project, Linus visualised both Energy Efficiency, specifically the role of AI in computer optimization for reduced energy consumption, and Generative Image Models, exploring the process used by text-to-image diffusion models.
Martina Stiftinger
Martina Stiftinger is a designer and visual artist based across the UK & Austria. Martina’s images showcase the helpful capabilities of AI through the concept of Digital Assistance and Learning, specifically about how AI tools can support us and save us time and how AI-supported learning can provide learning resources across multiple subjects.
Nidia Dias
Nidia Dias is a passionate art director and designer from Portugal currently based in Porto. For this project she depicted Biodiversity and Genomics. Her final images show how AI could help us understand ecosystems and identify species, and assist in genomic studies and its applications.
Novoto Studio
Novoto Studio is a team of artists and storytellers who, for this project, depicted the potential of AI for Society.
Wes Cockx
Wes Cockx illustrates Language Models, which generate text, and Large Models that explore the prediction method used in these models.
XK Studio
XK Studio images on Unsplash depict how humans can creatively collaborate with AGI (Artificial General Intelligence) and how it can enrich lives, offer new points of view, speed up processes, and lead to new territories.
