While the future of work is a broad topic, in this workshop we expect to focus on the following areas of interest.
Emerging and changing modes of work
Atypical and non-standard forms of work are becoming increasingly commonplace. Within HCI and CSCW, researchers have considered how the value proposition of non-standard knowledge workers is bound up with their expertise of particular applications , and have investigated the ramifications of the platform economy for both the experience of workers and for levels of productivity. For example, researchers have shown how crowd workers form collaborative networks outside of brick and mortar work environments , how rethinking the piece-work economic model on which crowd work is based could bolster yield , and how worker contributions might be optimized through the formation of experienced teams in complex tasks .
This work is set against a global backdrop in which the proliferation of micro- and gig work platforms has had diverse labor effects, which interact in complicated ways with older and continuous forms of inequality, exploitation, regional and class divides. Changing access to work platforms and personal technologies (e.g. smartphones, bodycams, self-monitoring devices) are enabling new workers to enter traditionally tight-knit local labor markets . Nevertheless, precarious conditions of work have been proliferating across class, race, and gender [16, 6]. In this contemporary moment of precarity, citizens are called upon to self-entrepreneurialize as a techno-economic fix, while technologists and tech researchers render more systemic change as something too large to tackle [12, 11, 13]. Yet, where explicit efforts to contextualize and design work platforms to facilitate access have been made, for example by reducing barriers for workers with limited literacy levels and constrained resources, participation in labor markets has been enabled .
In this workshop, we see an opportunity to consider forms of atypical work in addition to micro- and crowd work, to address how these non-standard modes of work intersect with existing forms of inequality and political economy, and to bring worker progression and development under consideration.
Automation and heteromation
A recent report by the McKinsey Global Institute  claims that we are living in “a new automation age”, in which machines are being developed to undertake not only routine physical work but also tasks requiring cognitive capabilities, including making tacit judgements and sensing emotion. Prominent and recent examples of machine capabilities include Google Duplex , an AI system for conducting tasks over the phone via ‘natural’ conversations, and self-driving Ubers, which are currently being piloted in Pittsburgh . While forecasts of the effects of automation on work are inconsistent, McKinsey reports that at least 30% of the activities that make up ~60% of today’s occupations could be automated, with highly structured physical activities and tasks involving the collection and processing of data being best suited to automation.
An important caveat here is that McKinsey assume people will work alongside machines to underpin productivity; they predict that in most cases work performed by humans will change rather than be replaced. Nevertheless, automation anxiety is highlighted in a recent survey by the UK’s Royal Society of Arts (RSA) , with 34% of respondents believing that new technologies will result in large job losses. The RSA take a more optimistic view, noting that automation could alternatively raise productivity and wages, as has been the case in the EU’s most automated country, Germany. However, they also acknowledge that the effects of automation will be differentially felt, with single-industry towns and specific trades, such as manufacturing, finance, and transport and logistics, being most heavily affected.
Within HCI, the requirement for human intervention in support of machines has been positioned as a shift to ‘heteromation’ . Humans form an essential component of heteromated workflows, dealing with critical tasks that machines cannot address. However, little attention has been paid within CHI as to the nature of heteromated work, or to the possibility that intelligent machines may ‘empower’ humans within the workplace, despite the emphasis on this within the technology industry . Relatedly, the possibility that new forms of brain-computer interaction may give rise to ‘augmented’ workers requires thoughtful discussion.
In this workshop, we see an opportunity to consider the role that new and intelligent technologies could play in work, how this intersects with the experience of workers, and the ethical and moral questions that are raised.
Changing temporal patterns and sites of work
A final topic of interest relates to the role of technology in where and when work is done. Salient here are new possibilities offered by mobile phones and the use of personally-owned devices for work. The space(s) of productivity are no longer singular – people work in and from multiple places, from traditionally non-work spaces (home) and whilst in transit.
This raises implications for the organization of work, for collaborative communication, and for work-life balance . There there is an increasing need to appear ‘always on’, and in response to this, Mazmanian and Erickson  have pointed to temporal division of labour as a means of managing an appearance of availability across an organisation, whilst individual workers disconnect backstage. Research has also pointed to the difficulties that shift and gig workers experience in managing the boundaries around work. For instance, Bakewell et al.  describe how the engineers they studied often started planning their day via smartphone apps well before they docked their phones into their vans to signal they had ‘started’ work, and work on ride-sharing has highlighted how vehicles need to be transformed from personal to service-oriented spaces .
Finally, while the platform economy has made extremely visible the role of smartphones in transforming sites of work, other technologies play a role in reconfiguring sites of work. Architects and workspace designers are increasingly incorporating pervasive sensing, context-aware automation and interactivity, with a view to optimizing built spaces for sharing and hot-desking , as well as to enhance the comfort and wellbeing of workers. Alternative applications of technology include embedded systems that track performance. As one example, Pritchard et al.  report how London bus drivers experienced technologies that monitored their driving, making efforts to alter their work but also to subvert the requirements of the system.
In this workshop, we see opportunities to explore how embedded and pervasive technologies intersect with how work is organized and experienced, and how workers manage temporal and spatial boundaries around work as these become more fluid.
1. Hamed S. Alavi, Himanshu Verma, Jakub Mlynar, and Denis Lalanne. 2018. The Hide and Seek of Workspace: Towards Human-Centric Sustainable Architecture. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18), Paper 75, 12 pages. DOI: https://doi.org/10.1145/3173574.3173649
2. Lyndsey L. Bakewell, Konstantina Vasileiou, Kiel S. Long, Mark Atkinson, Helen Rice, Manuela Barreto, et al. 2018. Everything We Do, Everything We Press: Data-Driven Remote Performance Management in a Mobile Workplace. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18), Paper 371, 14 pages. DOI: https://doi.org/10.1145/3173574.3173945
3. Wendy R. Boswell and Julie B. Olson-Buchanan, J. B. (2007). The Use of Communication Technologies After Hours: The Role of Work Attitudes and Work-Life Conflict. Journal of Management, 33:4, 592– 610. https://doi.org/10.1177/0149206307302552
4. Benedict Dellot and Fabian WS. July 6, 2018. Good Work in an Age of Radical Technologies. Retrieved 12 October 2018 from https://medium.com/@thersa/good-work-in-an-age-of-radical-technologies-52c7bc6b8cc2
5. Hamid Ekbia and Bonnie Nardi. (May 2014). Heteromation and its (dis)contents: The invisible division of labor between humans and machines. First Monday. DOI: https://doi.org/10.5210/fm.v19i6.5331
6. Christian Fuchs. 2014. Digital Labour and Karl Marx. Abingdon, UK: Taylor & Francis.
7. Google AI Blog. Google Duplex: An AI System for Accomplishing Real-World Tasks Over the Phone. May 8, 2018. Retrieved 12 Oct 2018 from https://ai.googleblog.com/2018/05/duplex-ai-system-for-natural-conversation.html
8. Mark Graham, Isis Hjorth, and Vili Lehdonvirta. 2017. Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods. Transfer: European Review of Labour and Research 23:2, 135-162.
9. Mary L. Gray, Siddharth Suri, Syed Shoaib Ali, and Deepti Kulkarni. 2016. The Crowd is a Collaborative Network. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW ’16), 134-147. DOI: https://doi.org/10.1145/2818048.2819942
10. Kazushi Ikeda and Michael S. Bernstein. 2016. Pay It Backward: Per-Task Payments on Crowdsourcing Platforms Reduce Productivity. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16), 4111-4121. DOI: https://doi.org/10.1145/2858036.2858327
11. Lilly Irani. 2015. Hackathons and the Making of Entrepreneurial Citizenship. Science, Technology & Human Values. Available on Sage OnlineFirst.
12. Silvia Lindtner. 2017. Laboratory of the Precarious. Methods of the Precarious: The Seductive Draw of Entrepreneurial Living. Women’s Studies Quarterly, 45:3&4, 287-305.
13. Silvia Lindtner and Seyram Avle. 2017. Tinkering with Governance: Technopolitics and the Economization of Citizenship. PACM of Human-Computer Interaction, 1: 2, Article 20.
14. Melissa Mazmanian and Ingrid Erickson. 2014. The product of availability: understanding the economic underpinnings of constant connectivity. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’14), 763-772. DOI: https://doi.org/10.1145/2556288.2557381
15. McKinsey Global Institute. January 2017. A Future that Works: Automation, employment, and Productivity. Retrieved 12 October 2018 from https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works_Full-report.ashx
16. Angela McRobbie. 2016. Be Creative: Making a Living in the New Culture Industries.
17. Apurv Mehra, Udayan Tandon, Sambhav Satija, and Jacki O’Neill. 2018. Prayana: Intermediated Financial Management in Resource-Constrained Settings. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA ’18), Paper D104, 4 pages. DOI: https://doi.org/10.1145/3170427.3186504
18. Midas Nouwens, and Clemens Nylandsted Klokmose. 2018. The Application and Its Consequences for Non-Standard Knowledge Work. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18), Paper 399, 12 pages. DOI: https://doi.org/10.1145/3173574.3173973
19. Gary W. Pritchard, Pam Briggs, John Vines, and Patrick Olivier. 2015. How to Drive a London Bus: Measuring Performance in a Mobile and Remote Workplace. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI ’15), 1885-1894. DOI: https://doi.org/10.1145/2702123.2702307
20. Noopur Raval and Paul Dourish. 2016. Standing Out from the Crowd: Emotional Labor, Body Labor, and Temporal Labor in Ridesharing. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW ’16), 97-107. DOI: https://doi.org/10.1145/2818048.2820026
21. Niloufar Salehi, Andrew McCabe, Melissa Valentine, and Michael Bernstein. 2017. Huddler: Convening Stable and Familiar Crowd Teams Despite Unpredictable Availability. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW ’17), 1700-1713. DOI: https://doi.org/10.1145/2998181.2998300
22. Hanna Schneider, Malin Eiband, Daniel Ullrich, and Andreas Butz. 2018. Empowerment in HCI – A Survey and Framework. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18), Paper 244, 14 pages. DOI: https://doi.org/10.1145/3173574.3173818 23. Self-Driving Ubers. Retrieved 12 Oct 2018 from https://www.uber.com/cities/pittsburgh/self-driving-ubers/