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10a.002.JYU_WP9 - IoB@work

Project - Summary

Internet-of-Things (IoT) is an established concept with many solution proposals and application domains. IoT deals with devices that are interconnected and exchange data and information. When the data becomes processed and stored in the cloud, customer behaviors, preferences and interests can be better understood; this is referred to as Internet-of-Behavior (IoB). IoB approaches the IoT from the human perspective, seeking to understand how the data should be understood. Lately, IoB has also been seen to increase interest in the workplace domain, but not much in academia so far. IoB utilizes IoT devices with digital services and entities to collect, analyze, and affect customers' habits and workers' behavior. The IoBAtWork project aims to find suitable models for predicting human behavioral events and passively encourage positive behavior. Behavior may have productivity and mental effects on knowledge workers. The project has been continued until the end of February 2023. Currently, the project is in its final analysis and documentation phase.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Pekka Abrahamsson PI 358 40 541 5929 University of Jyväskylä
Ville Vakkuri Researcher N/A N/A University of Jyväskylä
Joni Kultanen Researcher 358 40 628 1871 University of Jyväskylä
Juhani Risku Researcher N/A N/A University of Jyväskylä
Teemu Autto Student N/A University of Jyväskylä
Antti Kariluoto Student N/A 358 44 062 9059 University of Jyväskylä
Mikko Virtaneva Researcher 358 44 703 9200 Workspace Oy
Ilona Karlsson Mentor N/A N/A Workspace Oy
Jukka Lassila Mentor N/A N/A Workspace Oy

Project - Novelty of Approach

Human interaction and performance and business strategy execution data present new domains for Machine Learning applications. The problem is approached from an ethics viewpoint by using ECCOLA – a Method for Implementing Ethically Aligned AI Systems (Vakkuri, Kemell, Jantunen, et al., 2021) in the design and implementation phase of the work packages 8 and 9.

Current IoB capturing solutions are developed for consumer markets, and we need to experiment with how they can become operationalized in a workplace context without too much intrusion into employees' privacy. Therefore, we utilize the ECCOLA method and framework in the design and implementation phase, build the experimental data collection platform in a laboratory context, and use the privacy-preserving techniques, such as edge computing, local storage of data, and data anonymization at the earliest wherever possible. In an experimental setting, people's work behaviors are monitored, and (dis)incentives are applied to influence them to perform towards the desired set of operational parameters. IoB allows the transformation from only descriptive (analyzing behavior) to proactive influencing.

Further, our study distinguishes itself from other performance and productivity research by the longitudinal data we were able to gather from the beginning of the COVID-19 pandemic through changes in work customs – both in remote and office settings in different phases of the pandemic. Examining the factors identified in the existing literature to be affecting individual performance and productivity – such as work-related stress (Choo, 1986; Luxmi & Yadav, 2011; Shahu & Gole, 2008), teamwork (Gallie et al., 2009; Musriha, 2013; Stephany et al., 2020), and self-efficacy (Cherian & Jacob, 2013; Gist & Mitchell, 1992; Phillips & Russell, 1994) – through longitudinal data provides a unique view into how the pandemic may have changed the perception of work as a whole and how the significance of the previously identified factors to performance and productivity might differ from the past after the prolonged period of remote work.

Project - Deliverables

1 IoB-laboratory setting - estabishment (done) and iterative improvement and implementation of new interventions / stimuli in the experimental setting
2 Case study on the controlled IoB-experiment at Workspace Oy premises - preparation, execution and writing an article
3 ECCOLA case study - ethically aligned design of non-invasive measurement system
4 Longitudinal study: follow-up article for “COVID-19 Remote Work: Body Stress, Self-Efficacy, Teamwork, and Perceived Productivity of Knowledge Workers”
5 Article on the effects of the meeting space to interaction - comparison of interaction in more traditional meeting room and “phone booth” style meeting space
6 Article on the :Changes in the space“ experiment: how do a new overall design of office and added attractors change the use of space and the preferred locations for social interaction
7 Further publications/reports on the results and lessons-learned on detecting, measuring, quantifying, and (dis)incentivizing behavior with the means of IoB

Project - Benefits to IAB

Python 2 reached its end of life on 1/2020. As part of the research project, OpenBadge hub code and analysis library was ported to python 3 and is freely available on GitHub (see “Sociometric Badge”).

All the software and algorithms developed are available under an MIT license.

Project - Documents

projects/year10/10a.002.jyu_wp9.txt · Last modified: 2022/10/04 08:34 by sally.johnson