21 actions inaccurate. Google Death to Clippy’ to seethe extent to which smart user interface technology can get it wrong. Many intelligent user interfaces emerge from the machine learning community
, and especially Bayesian inference
techniques. Bayesian techniques are more appropriate to user interfaces than other techniques fora range of reasons
They don’t rely on large training sets (as is the case with neural net approaches, so they can adapt more quickly to individual users
Bayesian consideration of prior probabilities corresponds better to commonsense human reasoning under uncertainty.
Bayes formula provides a consistent way to combine data from user interactions with historical data and heuristic rules. The lecture will provide further practical examples (others will have been included in the lectures on advanced interaction techniques, where Bayesian inference is often used for gesture interaction, or vision-based augmented reality systems. An inference framework provides a valuable analytic perspective on many current trends in user interaction. For example, the behaviour of Google, or of recommender systems such as Amazon or Facebook friend finder
, use inference techniques to apply statistical data and guess what the user really wants. It remains the case that when the system makes inaccurate inferences, the results will be annoying, confusing, or even damaging. This means that some advanced research areas, such as Programming by Example
(where automated scripts or macros are created by inference
, after observing repeated actions) provide a major challenge for HCI. These are active areas of research in Cambridge at present, and a few advanced prototypes are available for experimental use, such as the Koala project at
IBM's Almaden Research Center (Allen Cypher, one of the Koala team, has worked in this area for many years – his Eager prototype at Apple Research was an early success.