| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | August 17, 2017 |
| Latest Amendment Date: | July 27, 2021 |
| Award Number: | 1718121 |
| Award Instrument: | Standard Grant |
| Program Manager: |
William Bainbridge
IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2017 |
| End Date: | August 31, 2022 (Estimated) |
| Total Intended Award Amount: | $494,286.00 |
| Total Awarded Amount to Date: | $494,286.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
107 S INDIANA AVE BLOOMINGTON IN US 47405-7000 (317)278-3473 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
980 Indiana Ave Lockefield 2232 Indianapolis IN US 46202-2915 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | HCC-Human-Centered Computing |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Research advances have enabled innovations in collaborative work information systems that can keep track of employees and contractors in domains such as ride sharing. For instance, after drivers login to begin a work session, riding sharing computers keep track of cars, customers, and ride locations. Such systems enable accurate payments to drivers and create work histories that are shared among managers, drivers, and clients. In many other work domains, such as home care, delivery, farm work, and child care, transparent collaborative information systems do not exist, leaving work environments open to inaccurate compensation, conflict over work requirements or behavior, or even exploitation. This project will examine the needs of workers, employers, and managers for collaborative and shared reporting, and opportunities for innovative technology to create such systems. The project will lead to fundamental understanding of collaboration in work information for traditional and new forms of work that currently lack accurate and transparent measures of the work hours, effort, or performance on which compensation is based.
This project requires fundamental research and application development in three potential key intervention areas: (1) technologies to enable worker education concerning worker and employer rights and responsibilities; (2) systems that could collect shared work data for workers, employers, and managers while protecting individual privacy and confidentiality, and (3) empirical evaluations to assess effectiveness as well as understand potential risks or undesirable indirect consequences of work-related data collection. Researchers will prototype and test these systems mainly in work environments, such as farm work, custodial work, and restaurants services. The project will lead to a better understanding of the potential for technology to help create better jobs for workers, and aid managers and employers to create responsive, transparent, and equitable business and work environments.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The objective of this research was to uncover practices and challenges, establish design recommendations, and evaluate design strategies for collaborative, mobile, workplace computing technologies focused on low-wage workers’ needs and goals. To achieve that objective, we conduct multiple empiric and design-related studies focused on identifying challenges and concerns of various relevant stakeholders within the low-wage workforce. The rationale for our work is that many work-related and workplace computing technologies focus on the needs and goals of managers and employers but sometimes do not well attend to the needs of workers themselves. This is especially true for low-waged workers. This is a huge oversight as workers may have differing goals, needs, or insights and if attended to may enhance overall worker efficacy and productivity. Our work seeks to begin to address this research and design oversight. The project generated several key results and empiric insights and activities:
We conducted several studies empiric and design studies, including 1) interviews with designers and relevant stakeholders for computational tools aimed at alleviating social and economic inequality in the low-wage workplace; 2) interviews with low-wage workers and managers about how novel automation-related computing technologies impacted work, workers, and the workplace, and 3) design studies aimed at addressing key challenges addressed in earlier phases.
Identifying Challenges to Designing Pro-Social Computing Projects for Low-Wage Workers: We investigated why and how different work-focused computing technologies aimed at alleviating workplace social inequality for low-wage workers failed to flourish. In one research project, we focused on the issue of wage violations in the low-wage workplace. We spoke with computing technology designers, worker advocacy, policy advocates, and legal experts who were involved in design projects aimed at reducing wage violations. We uncovered that all independent wage violation-related computing technology design projects had failed because of three key reasons. First, we uncovered how user adoption and consistent use of certain computing technologies was difficult for low-wage workers. Second, we highlighted how economic ideological incompatibilities and political events impacted key social relationships for design collaborations. Lastly, we discussed how pervading large-scale institutions shaped the design and possibilities of such computing technologies. Such key results are crucial for understanding how to productively design computing technologies for workers.
Identifying Challenges with Automation-related Computing Technologies in the Low-Wage Workplace: We investigated how commonplace automation-related computing technologies impact the low-wage service workplace. We interviewed workers and managers to identify broad changes and challenges within the low-wage service sector from the perspectives of workers, including changes to work routines, relationship with other workers, managers, or customers, and perspectives on career longevity and economic mobility. Such knowledge is critical for understanding how to best design future workplace automation-related computing technologies that account for workers’ experiences, perferences, and goals.
Designing and Evaluating Collaborative Mobile Computing Technologies for Low-Wage Workers: We conducted design research investigations focused on collaborative mobile computing technologies aimed at wage violations for low-wage workers. In the design process, we designed prototypes focused on 1) using automated and semi-automated location and work-based data collection to aid in creating alternative work accounts that may help workers with documentation. These alternative work accounts can help workers understand their work situations and, when necessary, develop wage claims. 2) Using the collected data in the wage recovery processes; and 3) connecting workers with advocates, like lawyers, to aid in the wage recovery processes. This research developed design principles for designing future technologies that reflect the concerns and preferences of low-wage workers who deal with wage violations.
Practical Outcome Summary: The results of this project informed ten academic, peer-reviewed papers and five peer-reviewed conference workshops, and multiple scholarly presentations. The research opportunities outlined above provided advance technical and design training for many undergraduate and graduate students who may be typically underrepresented in STEM fields such as women of color. This project results and insights provide a solid research basis to understand how to design computing systems for and alongside marginalized workers in contemporary organizations.
Last Modified: 01/15/2023
Modified by: Lynn Dombrowski
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