Microsoft’s Clippy showed the world that a computer can use context clues to determine when a person is writing a letter, but that it probably
should keep its digital mouth shut. In this talk, we’ll discuss
designing a query tool that offers contextualized suggestions (and even warnings) to help users write accurate and performant queries quickly… without making them want to force quit in fury—whether they're less-techy Excel folks or committed command line coders.
Over the course of this fast-paced and fun session we’ll
- incorporate learnings from Don Norman, Cliff Nass, and other HCI luminaries (using case studies from self-driving cars and a variety of software examples, both cutting-edge and totally familiar), as well as lessons from user research on beta releases
- geek out about predictive text (incorporating syntactic, semantic, and social clues)
- explore how to provide suggestions or interventions at just the right time and in just the right way to maximize utility and minimize frustration
- and much more…
