Section: Overall Objectives

Knowledge for Interaction

In the early 1960s, at a time where computers were scarce, expensive, bulky and formal-scheduled machines used for automatic computations, Engelbart saw their potential as personal interactive resources. He saw them as tools we would purposefully use to carry out particular tasks and that would empower people by supporting intelligent use  [35]. Others at the same time were seeing computers differently, as partners, intelligent entities to whom we would delegate tasks. These two visions still constitute the roots of today's predominant HCI paradigms, use and delegation. In the delegation approach, a lot of effort has been made to support oral, written and non-verbal forms of human-computer communication, and to analyze and predict human behavior. But the inconsistency and ambiguity of human beings, and the variety and complexity of contexts, make these tasks very difficult  [46] and the machine is thus the center of interest.

Computers as tools

Our focus is not in what machines can understand or do by themselves, but in what people can do with them. We do not reject the delegation paradigm but clearly favor the one of tool use, aiming for systems that support intelligent use rather than intelligent systems. And as the frontier between the two is getting thinner, one of our goals is to better understand what it takes for an interactive system to be perceived as a tool or a partner, and how the two paradigms can be combined for the best benefit of the user.

Empowering tools

The ability provided by interactive tools to create and control complex transformations in real-time can support intellectual and creative processes in unusual but powerful ways. But mastering powerful tools is not simple and immediate, it requires learning and practice. Our research in HCI should not just focus on novice or highly proficient users but should also care about intermediate ones willing to devote time and effort to develop new skills, whether for work or leisure.

Transparent tools

Technology is most empowering when it is transparent: invisible in effect, it does not get into your way but lets you focus on the task. Heidegger characterized this unobtruded relation to things with the term zuhanden (ready-to-hand). Transparency of interaction is not best achieved with tools mimicking human capabilities, but with those taking full advantage of them given the context and task. For instance, the transparency of driving a car “is not achieved by having a car communicate like a person, but by providing the right coupling between the driver and action in the relevant domain (motion down the road)”  [49]. Our actions towards the digital world need to be digitized and we must receive proper feedback in return. But input and output technologies pose somewhat inevitable constraints while the number, diversity, and dynamicity of digital objects call for more and more sophisticated perception-action couplings for increasingly complex tasks. We want to study the means currently available for perception and action in the digital world: Do they leverage our perceptual and control skills? Do they support the right level of coupling for transparent use? Can we improve them or design more suitable ones?