As members of UX teams, we have a responsibility to understand the inner workings of our apps and sites. Yet when it comes to building products and services that rely on artificial intelligence, this can prove challenging; while AI is not a new field in computer science (it formalized in the 1950s), it’s a new frame of reference for those of us practicing UX design and content strategy for consumer products.At Google, we’re committed to providing clear explanations on how AI systems work for both users and the general public. Depending on who you are—a novice, an expert, a researcher, a developer, a designer, a content strategist, or a policy advocate—the expectation of how the same AI terms might be used or applied is going to be very different. When everyone is on the same page (of the dictionary, if you will), we can have a shared, specific understanding of certain key terms used by ML and AI practitioners. This can help UX teams better communicate not only how to address user needs, but also build users’ trust in AI systems by explaining how these systems work clearly and simply.
Editorial