Habit and Skill in the Domain of Joint Action

Dichotomous thinking about mental phenomena is abundant in philosophy. One particularly tenacious dichotomy is between “automatic” and “controlled” processes. In this characterization automatic and unintelligent go hand in hand, as do non-automatic and intelligent. Accounts of skillful action have problematized this dichotomous conceptualization and moved towards a more nuanced understanding of human agency. This binary thinking is, however, still abundant in the philosophy of joint action. Habits and skills allow us agentic ways of guiding complex action routines that would otherwise overwhelm our reflective capacities. In this paper, I look at how theories of skill, habit, and know-how in individual action can inform a non-dichotomous account of joint action. I argue that a fuller understanding of joint agency has to understand not only group know-how, but also the role of attention and the highly integrated types of control that allow agents to act together.

On Pros and Cons and Bills and Gates: The Heist Film as Pleasure

This article tries to shed light on the multiple, but underrated pleasures of the heist film – a genre that has attracted numerous major directors from Jean-Pierre Melville and Stanley Kubrick to Michael Mann and Steven Soderbergh, but has received limited scholarly attention. I approach the genre from a, broadly, philosophical perspective and draw on thinkers such as Peter Sloterdijk, Georg Simmel, Paul Souriau and Bruno Latour to argue that their emphasis on (1) skillful action and kinaesthetic empathy, (2) smooth transgression of boundaries and (3) well-functioning social collaboration and we-connection, the genre's best exemplars satisfy, in fictional and quasi-utopian form, a number of real-life desires.

Agency plus automation: Designing artificial intelligence into interactive systems

Much contemporary rhetoric regards the prospects and pitfalls of using artificial intelligence techniques to automate an increasing range of tasks, especially those once considered the purview of people alone. These accounts are often wildly optimistic, understating outstanding challenges while turning a blind eye to the human labor that undergirds and sustains ostensibly “automated” services. This long-standing focus on purely automated methods unnecessarily cedes a promising design space: one in which computational assistance augments and enriches, rather than replaces, people’s intellectual work. This tension between human agency and machine automation poses vital challenges for design and engineering. In this work, we consider the design of systems that enable rich, adaptive interaction between people and algorithms. We seek to balance the often-complementary strengths and weaknesses of each, while promoting human control and skillful action. We share case studies of interactive systems we have developed in three arenas—data wrangling, exploratory analysis, and natural language translation—that integrate proactive computational support into interactive systems. To improve outcomes and support learning by both people and machines, we describe the use of shared representations of tasks augmented with predictive models of human capabilities and actions. We conclude with a discussion of future prospects and scientific frontiers for intelligence augmentation research.