designing for AI, but also designing how
to design for AI.
This article explores how prototyping and developing tools specifically
for the design of AI can help advance
the emerging field of UX/Ix D for AI.
Using the author’s experimental Delft
AI Toolkit as an example (Figure 1), we
discuss several ways to think about the
needs and features of an AI toolkit.
Interaction designers face new challenges
with AI, in which the underlying
technologies are hard to master and it is
even more difficult to understand when,
how, and why they should be applied.
Our tools should help us create great,
thoughtful designs with AI.
Just as important, our tools
We are moving toward an era of pervasive
interactions with machine intelligence.
Consider that increasing numbers of
autonomous vehicles are mixing with
pedestrians and traditional vehicles.
Home Io T devices independently sense
and act on our behalf. Co-bots work side
by side with people.
These new types of interactions
are affecting our civic, domestic, and
work lives in significant ways. But the
tools for exploring potential effects
are at best lacking and, in many cases,
nonexistent. There is an urgent need
to develop generative and effective
methods that explore the consequences
of design choices when creating AI
systems, including consideration of the
new ecologies they create. This is an
interaction-design meta-task—not just
WInsights → Designers face new challenges with AI, and need tools for designing complex interactions and addressing ethics and civic responsibility. → Tools should allow fast, iterative experimental prototyping of autonomous behavior. → Designers need a hands-on understanding of AI to help influence the next generation
of AI technology and
Philip van Allen, ArtCenter College of Design