IAC 2020
What does time feel like? A sense of duration? Speed? These factor in. But, to get to the heart of how our experience of time relates to design, we need to look at cadence. What the cadence of time feels like depends on the scale at which we are acting. Let’s call these cadence layers. When actors perform domain tasks with our designs, they are acting at one cadence layer that evokes a particular sense of time.
Now that we’re automating tasks (in an industrial or even personal context), we’re shifting our actors to a higher cadence layer, with different activities and a different sense of time. Offloading tasks to intelligent systems shifts our actors to an even higher layer, their engagement cadence and activities shifting again. We already design in these emerging scenarios for specific tasks, but we don’t have good ways to represent them at scale.
In this talk, I’ll introduce Cadence Layers as a new framework to make sense of our growing reliance on automations and intelligent systems, and the way business models are shifting for digital products. We’ll look at how the nature of domain activities changes at higher Cadence Layers, and what new information architectures help us guide our designs, finding structure in the flow of time. Time is an arrow, but maybe it’s not quite like a river we may only step into once after all.
Key takeaways from the session:
The audience will walk away understanding:
- Why emerging design scenarios require us to consider how actors feel time as engagement cadences.
- How a new framework, Cadence Layers, helps us make sense of emerging design scenarios.
- Characteristics of the three Cadence Layers: what scenarios shift actors into them, what engagement cadence feels like and is about at each layer, and information architectures we may use for representation and design guidance at each layer.
- Why we need new design tools to represent higher cadence layer scenarios, and encouragement to experiment and help fill the gap!
For more than 20 years, Marsha has valued the creative interplay of practicing and leading information architecture in industry (currently, 3D tools for making things at Autodesk), while at the same time pressing IA theory, applying thinking from other fields, proposing new approaches in journal articles and talks. She’s convinced that framing and debating what we find by following our collective curiosity about the structural aspects of meaning is a most practical need.