Multitasking while driving: a time use study of commuting knowledge workers to access current and future uses

Commuting has enormous impact on individuals, families, organizations, and society. Advances in vehicle automation may help workers employ the time spent commuting in productive work-tasks or wellbeing activities. To achieve this goal, however, we need to develop a deeper understanding of which work and personal activities are of value for commuting workers. In this paper we present results from an online time-use study of 400 knowledge workers who commute-by-driving. The data allow us to study multitasking-while-driving behavior of com-muting knowledge workers, identify which non-driving tasks knowledge workers currently engage in while driving, and the non-driving tasks individuals would like to engage in when using a safe highly automated vehicle in the future. We discuss the implications of our findings for the design of technology that supports work and wellbeing activities in automated cars

How does working from home during Covid-19 affect what managers do? Evidence from time-use studies

We assess how the sudden and widespread shift to working from home during the pandemic impacted how managers allocate time throughout their working day. We analyze the results from an online time-use survey with data on 1,192 knowledge workers (out of which 973 are managers) in two waves, a pre-pandemic wave collected in August/2019 (615 participants, out of which 506 are managers) and a post-pandemic wave collected in August/2020 (577 participants, out of which 464 are managers). Our findings indicate that the forced transition to WFH created by the COVID pandemic was associated with a drastic reduction in commuting time for managers, but also an increase in time spent in work rather than on personal activities. This included reallocating time gained from commuting into more time spent in meetings, possibly to recoup some of the extemporaneous interactions that typically happen in the office. This change is particularly pronounced for managers employed in larger organizations. We use the results from the time-use studies to discuss implications for the development of new technologies

Using Speech to Interrupt Complex Tasks

Interacting with computers using speech promises the benefit of multitasking while one’s hands and eyes are occupied by another task. Users of spoken dialogue sys- tems have not seen this technology as living up to its potential however, in part be- cause speech agents interactions largely behave like traditional interface interactions, initiated by the user. In order to harness the full multitasking benefit of speech as an interaction modality, speech agents must interactive proactively, but doing so means that agents will need to interrupt users engaged in other tasks. While general guide- lines have been proposed for the design of proactive agents in general, the design of proactive speech which interrupts has not been explored in specific. Interrupting speech from proactive agents can take design inspiration from the ways people use speech to interrupt other people, but human speech interruptions are likewise not well understood. The first study of this thesis uses a mixed methods approach to investi- gate the effect of the urgency on people’s timing and strategies for interrupting with speech. The second study complements that data by comparing the effect of urgency on interruption timings and strategies to the effect of the difficulty of the task which is interrupted. The third study uses a data-driven approach to classify the interruptible moments of a complex task in order to analyse the extent to which participants from the prior studies utilised these dynamic characteristics of the ongoing task to shape their interruptions. Finally, the fourth study applies findings from human speech inter- ruption to the design of a proactive agent to investigate the effects of human-inspired adaptivity to context on people’s perceptions of a proactive speech agent. Findings suggest that human speech interruptions are highly diverse and adaptive to context, but such adaptivity may be seen as inappropriate and inconsistent when applied to a speech agent. The implications of this research and its limitations are discussed in the closing chapter.Science Foundation Irelan