Design for Trust is a set of principles and methods to help designers and technologists include trust considerations in our processes.
We’re presently experiencing a major shift in technology led by developments in artificial intelligence (AI) in association with distributed sensing, computing, and robotics. As AI capabilities and capacities grow, so too does our responsibility to design safe, reliable, and ethical systems that people trust.
If we aren’t aligned with our audience’s expectations and perceived risks, no matter how useful our product or service is, we’re just going to build something that no one feels comfortable using.
We place our trust in technology everyday. But with AI, we’re starting to follow recommendations by machines. As a result, people have new questions that must be answered in order to allow these systems into their lives.
What does the system value?
Is it logical and predictable?
Is my personal information safe?
Recent follies and failures, even within our largest companies, have brought AI under scrutiny. The media has reported aggressively on these fallbacks. In response, thought leaders have spoken at a high level about the need for creating trusted systems and the design community has begun to share anecdotes of best practices. However, few have leveled-up these anecdotes to develop general methodologies for codifying success in order to leverage “lessons learned” for new design challenges.
We’ve distilled our learnings into three overarching principles with a common theme: to always approach solutions from the perspective of the user.
Understand your users’ mental models. User expectations and perceived risks drive trust requirements.
Trust is a dynamic relationship. It is tentatively granted, then tested over time. Manage users’ expectations and perceived risks throughout the product experience.
Ingrain visceral trust to minimize interactive friction. When building trust, motivation is more powerful than demonstration or explanation.
SRI has a long legacy of bringing new design solutions to the forefront—from the mouse to Siri (acquired by Apple) to the first robotic surgery system (Intuitive Surgical (ISRG)). Over the past five years, we’ve worked directly with dozens of large corporations and new startups in the areas relating to AI and robotic-driven systems—this toolkit represents the synthesis of learnings from our successes and failures.
We hope you find it useful.