Advanced User Assistance Systems

Information technology (IT) capabilities are increasing at an impressive pace, but users’ cognitive abilities are not developing at the same speed. Thus, there is a gap between users’ abilities and available IT. Handbooks or online help functions such as ‘‘F1 help’’ try to close this gap by providing explanatory information for the IT capabilities at hand. However, there is strong empirical evidence that traditional support structures are not as effective as intended (Sykes 2015); on the contrary, they distract users from their work (Barrett et al. 2004), which results in decreased efficiency and effectiveness as well as lower job satisfaction. Initial attempts to support users with more comprehensive integrated assistance functions failed miserably. A well-known example of such a dismal failure is ‘‘Clippy, the paperclip’’, a cartoon character developed by Microsoft that automatically popped up to assist users of Microsoft Office. However, instead of supporting the user with clear and precise guidance, studies show that Clippy ‘‘was considered to be annoying, impolite, and disruptive of a user’s workflow’’ (Veletsianos 2007, p. 374). In the end, Clippy, the ‘‘non-intelligent artificial intelligence assistant’’, was so despised that even Microsoft made fun of it. However, more recent attempts to support users, primarily in the private-life context (on mobile devices), are becoming more sophisticated and have been met with a more favorable response (e.g., Apple’s Siri and Google’s Google Now). Moreover, Microsoft has integrated its personal assistant, Cortana, into the latest version of the operating system Windows 10, which is available for private and business environments. One domain that is far more mature with regard to ‘‘user’’ support is the automotive sector. For more than 30 years there has been research into assistance systems that proactively support drivers (Bengler et al. 2014). Early driver assistance systems (DAS) only measured the parameters inside the car, for example with regard to vehicle stabilization (electronic stability control). Later on, sensors also captured the car’s external environment. The use of the collected data, navigation systems, adaptive cruise control, and parking assistance can assist drivers in avoiding hazardous situations and increasing driver comfort. Advanced DAS, considered to be the third phase of DAS evolution, are about to become commercialized as Accepted after three revisions by Prof. Dr. Sinz.