AI material explorations for Google

Working with emergent AI technologies to develop prototypes and expose alternate product realities.

Google Hardware + AI: 4 months

Material exploration, advanced prototyping, applied technology, R&D, machine learning, product strategy, IP and patents, new markets

This is another internal project so the content of the work is highly confidential. But - here's an overview of how we worked.

We worked collaboratively as an extension of the newly formed Hardware+AI team at Google: building on previous experience exploring human:AI collaboration (specifically, trust and control) to question the role of AI-enabled technologies within our homes and workplaces, and how it should adapt for different actors and contexts.

Bottom-up invention

Our approach was based on the idea of ‘material exploration’. Understanding the ‘grain’ of new technologies—how they want to be used—exposes novel user experiences and interaction models. Explorations span machine learning, signal processing, data visualisation, physical and digital design, hardware fabrication and actuating devices. Working closely with AIUX and ATAP teams.

Soft AI

The heart of this work focussed on softer forms of human:AI interaction, how we might break away from single user models to more nuanced, multi-user dynamics, in a way that can be learned over time. A core challenge to designing social AI systems is how we offer personalised experiences without sacrificing privacy.

Speculative design and prototyping

These types of projects are speculative in their nature. We frame our research as a series of challenges to guide our thinking and ensure we maintain focus on what we think is most valuable. As designers and engineers, we believe the key to unlocking this potential value lies in prototypes that people can try for themselves, little video vignettes that zoom in on the most meaningful moments, with technical strategies to support a product concept's roadmap.

It’s about concepts, not products. Our approach to product invention is designed to surface value from recent advances in ML research, in a way that product teams can interpret and build on. We work to expose potential without being prescriptive, with the goal of establishing new user experiences, new interaction models, and ultimately new product-market fits.

‘The team at Nord really gets it. With a solid problem statement they were able to go from concept to testable prototype. This included a healthy ideation cycle which revealed unexpected and delightful results. Productive and competent, they are a pleasure to work with.’

Don Barnett, UX Lead, Google AI

Don Barnett
UX Lead, Google AI