Why do we trust AI systems so readily? Is it because the answers sound so good and professional? Is it because we’ve learned (kudos to the art of engineering) that computers are accurate (and because we lack the intuitive understanding that AI “ticks” in a completely different way than previous algorithmic systems)?
Why do we “trust” at all?
And what does it take for us to translate that into the digital realm?
So many questions…
Here are a few ideas on this topic:
We humans learn to trust from a very young age—our parents, family, friends, teachers, government agencies, professors, and so on. The circle keeps getting bigger, and we’re constantly passed along from people we already trust to others. Parents take you to school, so the teacher must be trustworthy in some way. Titles and roles do the rest—the doctor at the hospital, the judge, the professor at the university, and so on. We still trust books and scholarly articles (even if that might be getting dangerous these days) because they incorporate quality-assurance mechanisms.
Trust gets betrayed—sometimes. Sometimes even more often. Sometimes just a little, sometimes really badly. We learn that, too. And we also learn how to recognize it—at least when it comes to people. Certain behaviors make us wary; we often recognize “untrustworthy” people very quickly and very intuitively.
And so each of us has a context in which we can easily understand the “concept of trust” and also have a certain sense of it.
Then came the engineers and computer scientists, who built machines that produce reproducible results that are almost always correct. We trust calculators, computers, and many types of software and databases more than we trust ourselves. This laid the foundation for trust in an entire technology. Many of us grew up with computers as an integral part of our “trustworthy” environment.
AI is different here.
AI simulates trustworthiness through correct and well-crafted responses. There’s no obvious behavior or clear sign that makes us skeptical or cautious. No, everything sounds great. Everything sounds exactly as we’re used to hearing in our familiar environments—and yet it can still be wrong or dangerous.
The more we work with AI systems—and the better they become—the more important it becomes to figure out how to bring our intuitive concept of trust into this world. Sure, critical thinking, not believing everything, and AI literacy—all of that helps. But that tends to happen at the operational level.
Deep down, we need a new kind of intuition. And it must not be based on complacency.
Exciting times.