Hanna Schraffenberger

2papers

2 Papers

37.2HCMar 28
Supporting Reflection and Forward-Looking Reasoning With Data-Driven Questions

Simon WS Fischer, Hanna Schraffenberger, Serge Thill et al.

Many generative AI systems as well as decision-support systems (DSSs) provide operators with predictions or recommendations. Various studies show, however, that people can mistakenly adopt the erroneous results presented by those systems. Hence, it is crucial to promote critical thinking and reflection during interaction. One approach we are focusing on involves encouraging reflection during machine-assisted decision-making by presenting decision-makers with data-driven questions. In this short paper, we provide a brief overview of our work in that regard, namely: 1) the development of a question taxonomy, 2) the development of a prototype in the medical domain and the feedback received from clinicians, 3) a method for generating questions using a large language model, and 4) a proposed scale for measuring cognitive engagement in human-AI decision-making. In doing so, we contribute to the discussion about the design, development, and evaluation of tools for thought, i.e., AI systems that provoke critical thinking and enable novel ways of sense-making.

HCJul 29, 2021
One-press control: a tactile input method for pressure-sensitive computer keyboards

Staas de Jong, Jeroen Jillissen, Dünya Kirkali et al.

This work presents One-press control, a tactile input method for pressure-sensitive keyboards based on the detection and classification of pressing movements on the already held-down key. To seamlessly integrate the added control input with existing practices for ordinary computer keyboards, the redefined notion of virtual modifier keys is introduced. A number of application examples are given, especially to point out a potential for simplifying existing interactions by replacing modifier key combinations with single key presses. Also, a new class of interaction scenarios employing the technique is proposed, based on an interaction model named "What You Touch Is What You Get (WYTIWYG)". Here, the proposed tactile input method is used to navigate interaction options, get full previews of potential outcomes, and then either commit to one or abort altogether - all in the space of one key depress / release cycle. The results of user testing indicate some remaining implementation issues, as well as that the technique can be learned within about a quarter of an hour of hands-on operating practice time.