"To meet expectation you must meet ones perception of an experience. Perception is the direct reaction to an expression, and in the case of AI, this known complexity and nuance is what we aim to design for." 

 

The problem: When working with AI technologies, (especially with the influence and expectations that movies and television set), accountability for people's perception becomes key to the experience. As designers we tend to over-compensate for what the technology is, and what it can realistically and reliably do.

​

The purpose: Good design is (and should be) invisible. It doesn't need to be hidden behind over-exaggerated brand voices, marketing materials or distracted by look at me!, look at me! type moments. It can simply be a shining star on its own, waiting to be recognized for its brilliance and in the case of AI, zero recognition doesn't hurt anyones feelings as long as its users' benefit. What if we took a different, more nuanced and strategic approach to designing for AI? Focusing more on the subtlety of users' perception of the technology while applying relatable expressions that help us build delightfully trustful experiences.

 

Takeaways
 

• How we as humans tend to interpret expressions in the physical and digital world and why it's important to understand those subtle nuances as a designer when designing for AI

• What the different tiers of expression are, how to calculate for usage, and examples of the way they're used in real world scenarios

• Considerations and tactical guidance to use everyday when designing for augmented intelligence

• Sneak peak at IBM's common design language for AI moments

​