Our keynote speakers are Melisa Stevanovic (University of Helsinki) and Saul Albert (Loughborough University).
Melisa Stevanovic: Joint decision making in a dyad: resources, practices, contingencies
Joint decision-making is a specific arena of social interaction where the participants’ collaborative management of the turn-by-turn sequential unfolding of interaction can have tangible consequences for the participants’ circumstances. In addition, joint decision making has implications for people’s social identities and democratic agency and is thus also of value in itself.
As an interactional phenomenon, joint decision-making draws on a range of resources, such as lexical choices, prosody, gaze, and body postures, and practices, such as displays of access, agreement, and commitment. Essentially, it necessitates a capacity to exercise control over the agenda of interaction and an ability to respond flexibly to others’ analogous attempts. This talk seeks to unravel the details of how joint decisions emerge in a dyad. I will work my way from the beginning of the decision-making process to its end, focusing on the following three questions: (1) How do participants initiate joint decision-making? (2) How do participants proceed from a proposal to a joint decision? (3) When is a joint decision established? Essentially, I argue that the emergence of any joint decision necessitates that, at each point of the process, the participants manage to construct symmetrically shared control over the unfolding activity.
To substantiate my argument, I draw on my previous conversation-analytic studies of sequences of naturally occurring joint decision-making interactions, as well as on statistical analysis of experimentally induced interactional data with eye tracking, motion capture, and physiological measurements.
Melisa Stevanovic is a university research fellow and lecturer at the Faculty of Social Sciences at the University of Helsinki. She conducts empirical social interaction research. She is currently involved in the projects ‘Social inclusion, interaction, and mental illness’ and ‘Participation, joint decision making and social interaction deficits’, and is director of the Master’s Programme in Contemporary Societies (COS)
Saul Albert: Three meeting points between conversation analysis and artificial intelligence
Sacks’ (1963) first published paper on ‘sociological description’ uses the metaphor of a mysterious ‘talking-and-doing’ machine, where researchers from different disciplines come up with incompatible, contradictory descriptions of its functionality. We may soon find ourselves in a similar situation to the one Sacks describes as AI continues to permeate the social sciences, and CA begins to encounter AI either as a research object, as a research tool, or more likely as a pervasive feature of both.
There is now a thriving industry in ‘Conversational AI’ and AI-based tools that claim to emulate or analyse talk, but both the study and use of AI within CA is still unusual. While a growing literature is using CA to study social robotics, voice interfaces, and conversational user experience design (Pelikan & Broth, 2016; Porcheron et al., 2018), few conversation analysts even use digital tools, let alone the statistical and computational methods that underpin conversational AI. Similarly, researchers and developers of conversational AI rarely cite CA research and have only recently become interested in CA as a possible solution to hard problems in natural language processing (NLP). This situation presents an opportunity for mutual engagement between conversational AI and CA (Housley et al., 2019). To prompt a debate on this issue, I will present three projects that combine AI and CA very differently and discusses the implications and possibilities for combined research programmes.
The first project uses a series of single case analyses to explore recordings in which an advanced conversational AI successfully makes appointments over the phone with a human call-taker. The second revisits debates on using automated speech recognition for CA transcription (Moore, 2015) in light of significant recent advances in AI-based speech-to-text, and includes a live demo of ‘Gailbot’, a Jeffersonian automated transcription system. The third project both uses and studies AI in an applied CA context. Using video analysis, it asks how a disabled man and his care worker interact while using AI-based voice interfaces and a co-designed ‘home automation’ system as part of a domestic routine of waking, eating, and personal care. Data are drawn from a corpus of ~500 hours of video data recorded by the participants using a voice-controlled, AI-based ‘smart security camera’ system.
These three examples of CA’s potential interpretations and uses of AI’s ‘talking-and-doing’ machines provide material for a debate about how CA research programmes might conceptualize AI, and use or combine it with CA in a mutually informative way.
References
Housley, W., Albert, S., & Stokoe, E. (2019). Natural Action Processing. Proceedings of the Halfway to the Future Symposium 2019, 1–4. https://doi.org/10.1145/3363384.3363478
Moore, R. J. (2015). Automated Transcription and Conversation Analysis. Research on Language and Social Interaction, 48(3), 253–270. https://doi.org/10.1080/08351813.2015.1058600
Pelikan, H. R. M., & Broth, M. (2016). Why That Nao? Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems – CHI \textquotesingle16. https://doi.org/10.1145/2858036.2858478
Porcheron, M., Fischer, J. E., Reeves, S., & Sharples, S. (2018). Voice Interfaces in Everyday Life. Proceedings of the 2018 ACM Conference on Human Factors in Computing Systems (CHI’18).
Sacks, H. (1963). Sociological description. Berkeley Journal of Sociology, 1–16.
Saul Albert is a lecturer in social sciences (social psychology) at Loughborough University. From 2016-2018, he was a postdoctoral associate at the Human Interaction Lab, working between psychology and computer science at Tufts University. His (2017) Ph.D was in Cognitive Science at Queen Mary, University of London’s Media and Arts Technology programme. Saul’s background is in the arts, where he worked in participatory culture, science and technology, co-founding The People Speak Network in 2006 to host open conversations in public spaces.