Call for Papers – Workshop
Do AI-based controls enable or subvert expected behaviour?
Chairs and organisers: Stefan Haefliger and Gianvito Lanzolla
haefliger@city.ac.uk and g.lanzolla@city.ac.uk
In-Person at Bayes Business School (formerly Cass) London, UK
09 December 2022, 9am – 5pm
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Stefan Haefliger and I are inviting contributions for a one-day workshop at Bayes Business School (formerly Cass) in London on 9 December 2022. If you are interested and available, please send your proposal (working paper or extended abstract) to both: haefliger@city.ac.uk and g.lanzolla@city.ac.uk by 25 October 2022. Notification of inclusion will be sent to the authors by 30 October 2022. The workshop will be co-hosted by the Bayes' Digital Leadership Research Centre.
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Keynote speakers:
Kalle Lyytinen, Case Western Reserve University
Christopher Tucci, Imperial College London
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Workshop context and aims
The emergence of AI-based control technologies (based, for instance, on machine learning and cloud computing) allows organizations to adopt and develop new practices of employee management. For instance, these practices may support internal controls and/or increase real time individual accountability of various actions including for behaviours not seen as compliant or even fraudulent (Currie and Seddon, 2021; Lyytinen et al., 2021).
However, controlling people may come with dark sides. For instance, Zuboff (2015) highlights the multifaceted impact of surveillance on consumers. Recent work in organization theory also demonstrates the enormous costs of algorithmic control in the workplace, for example in terms of organizational behaviour, such as frustration and subversive behaviour towards the algorithm (Rahman, 2021; Curchod et al., 2020; Pachidi et al., 2021). Other management research streams find similar patterns. For instance, the use of algorithms is by no means always positive and conducive to innovative behaviour or innovation (e.g., Lanzolla, Pesce, and Tucci 2021).
AI-based control technologies have become widely diffused in several industries ranging from pharma to transportation, financial services and manufacturing (see Uber, Deliveroo, RegTech, and other gig economy platforms). For instance, in the financial industry we have observed the diffusion of a particular type of algorithmic control technologies – hereafter, RegTech - to create compliance. RegTech has become very popular post financial crisis and during the last ten years several authors have explored its positive as well as dark side (Lyytinen et al., 2021; Currie et al, 2018; Siering et al., 2017; von Krogh et al., 2011). With this workshop we wish to expand our shared knowledge and take stock of:
· the ongoing – and inconclusive – debate on the mechanisms through which algorithmic control technologies affect behaviours;
· the (potential) divide between intended and realized behaviours, and the role that management has in initiating or moderating these behaviours.
· the (potential) side-effects of the use of these technologies on strategy, organization and organizing.
· Intended and side-effects on consumers or customers as well as on employees or complementors.
Within these broader goals, specific illustrative questions that we wish to address include (but are not restricted to):
· What are the processes / behaviours of adaptation among managers and broader stakeholder groups in the context of AI-based controls?
· Do AI-based control technologies enable or stifle innovation? What are the mechanisms that connect the control technologies with organizational behaviour and individual creativity?
· Managers vs. technology vs. employee: Who is controlling whom?
· Documenting subversion and improvisation or bricolage practices in the context of AI-based algorithmic controls
· What are the costs and benefits of applying AI-based control technologies in organisational settings?
· How is contemporary control enacted in organizations? What are the human-machine interaction protocols and interfaces that exert control in organizations?
By its very nature, the phenomenon of AI-based controls may speak to strategy, innovation, and information systems scholars working on, or curious about, the intersection of technology and organizational outcomes and behaviour. We are welcoming contributions of scholars with any disciplinary background sharing our curiosity.
Proposal (working paper or extended abstract) submission deadline: 25 October 2022 (please submit your proposal to both chairs and organizers: haefliger@city.ac.uk and g.lanzolla@city.ac.uk by 25 October 2022).
Notification of inclusion: 30 October 2022.
No registration fees (lunch and refreshments will be provided)
We apply a broad definition of AI for the purposes of this workshop: while algorithmic control includes some of the oldest management technologies such as double-entry bookkeeping, we are particularly interested in digital forms of algorithmic controls where automation plays an important role, such as through sensors, automated check-points, behavioural learning, image recognition, and more.