Center for the Futures of Work, Information and Technology

The Center for the Futures of Work, Information and Technology promotes research on the interlinked transformation of work and dynamics of emerging technologies, and to translate research findings to inform practice, pedagogy and policy.

In 2018 the NSF identified the “Future of Work at the Human Technology Frontier” as one of its 10 “big ideas.” The objective of that effort is to encourage interdisciplinary research to understand how “constantly evolving technologies are actively shaping the lives of workers and how people in turn can shape those technologies.” In so doing, it aims to use those findings “to increase opportunities for workers and productivity for the American economy.”

Technology is a central focus, as its use enables and empowers certain types of work, displaces others and creates new kinds of work that were not previously possible. Information and communications technologies (ICTs) in particular have facilitated the development of new ways of working. ICTs have dramatically reduced transaction costs, making it possible to sell goods and services used and new to an entire nation and the world. ICT-enabled platforms opened the doors for contingent work that can be done by anyone with access to the Internet and some tools, providing flexibility at the cost of a lack of predictability and the protections of established modes of employment. These and other developments call out for research to document the current landscape of work and technology, to understand how work is changing and determine how best to deploy emerging technologies in order to inform policy and education.

The center provides a focal point to rally faculty across the school to advance research on the changing nature of work and to incorporate insights into new educational and outreach activities. The center provides a connecting point to industry, employers and alums and a space for researchers to share their research and turn it into value for students, employers and the broader community.

Talks

Ernest Kung (Associated Press) and Margaret Cronan (WCVB, Boston) will give a talk on “How AI Can Support Local Journalism” at 12:30pm on Tuesday 22 October 2024. They will explore the opportunities and challenges Al presents for journalists, focusing on how AI tools can enhance newsroom workflows. The talk also offered practical advice for covering Al in editorial contexts, providing insights into the evolving relationship between technology and journalism.

ERNEST KUNG

Ernest Kung is the Al Product Manager for The Associated Press, helping local newsrooms integrate artificial intelligence into their workflows. With 15 years of experience as an award-winning news producer and writer in Los Angeles, San Diego, and Portland, Ernest transitioned to the technology side of journalism after earning a Master of Business Information Systems with Distinction from the University of Canterbury, where his research focused on Al in journalism in
Aotearoa New Zealand. He also holds a BA in Broadcast Journalism from the University of Southern California.

MARGARET CRONAN

Margaret Cronan is the News Director for WCVB Channel 5 in Boston, leading one of the region’s top news stations. With over 20 years of leadership experience in major markets, she oversees more than 45 hours of weekly news programming, as well as the station’s digital and social media initiatives. Margaret previously held leadership roles at CBS and Hearst stations across the U.S., including KYW-TV in Philadelphia and WBAL-TV in Baltimore.
She holds a BA in English from the University of Pennsylvania.

Center Projects

The Future of News Work: Human-Technology Collaboration for Journalistic Research and Narrative Discovery

This project explores the future co-evolution of news work and computational tools. Journalists and news work are important to study because, even in the face of numerous challenges, news organizations remain a powerful force for keeping communities safe and healthy by providing information about events and trends to help people make better decisions about their lives. Journalism, as an information-based industry and profession, has always been impacted by new technologies, most recently by the rise of the Internet and loss of advertising revenue, as well as the long-standing tension between journalistic values and business interests. These pressures take a toll on journalistic processes and products. Some important stories are not getting told: they take too much time to discover, research, and craft into narratives, and time is increasingly in short supply. The project seeks to address these problems through a combination of fieldwork and user-centered development of interactive tools for supporting journalists in research and narrative discovery, i.e., finding the story that the data tell and interesting and relevant ways to convey that story to a reader.

This project will advance knowledge about technology and news work through field studies and user-centered development of interactive tools for supporting journalists in research and narrative discovery. The resulting technology-supported work processes will be evaluated in experiments with freelance journalists and through deployment in newsrooms. The proposed project is composed of several interwoven components, each with a specific focus, yet designed to be mutually supportive and to lead to research convergence: (1) focus on better understanding workers, their work and especially their current relationship to technology in newsrooms; (2) build and assess ways to support journalistic research, specifically finding relevant information in large document collections of different kinds, using deep learning techniques for entity extraction and coreference resolution (AllenNLP), semantic search (BERT) and common sense reasoning (COMET); and (3) build and assess ways to support narrative discovery. Resulting tools will be evaluated in field experiments and through their impacts on work examined in field studies. Both sets of tools will later be augmented by adding the ability to work on audio data. Assessment will be extended to consider alternative ways to divide tasks between human journalists and the computational tools. Running throughout the project will be work on evaluation, synthesis, dissemination of findings and tools, planning and project management.

The project is supported by an NSF grant, “The Future of News Work: Human-Technology Collaboration of Journalistic Research and Narrative Discovery”, 21-29047 (Syracuse), 21-28906 (Stevens) and 21-29020 (Columbia). The PIs are Kevin Crowston & Keren Henderson (Syracuse), Jeffrey Nickerson (Stevens) and Lydia Chilton and Mark Hansen (Columbia).

The Work in the Age of Intelligent Machines Research Coordination Network

The Work in the Age of Intelligent Machines (WAIM) Research Coordination Network (RCN) (https://waim.network/) brings together researchers working to develop the understanding needed to jointly design both sides of the human-technology frontier in work settings where people interact with intelligent machines.

Highlighted Publications

Artificial intelligence in information systems: State of the art and research roadmap (PDF)

Ågerfalk, P. J., Conboy, K., Crowston, K., Jarvenpaa, S. L., Lundström, J. Eriksson, Mikalef, P., & Ram, S.. (In Press). Artificial intelligence in information systems: State of the art and research roadmap. Communications Of The Association For Information Systems (Cais).

Communicating with the masses from isolation: What happened when local television journalists worked from home (PDF)

Henderson, K., Raheja, R., & Crowston, K.. (2022). Communicating with the masses from isolation: What happened when local television journalists worked from home. In Hawai’i International Conference on System Sciences. Presented at the Hawai’i International Conference on System Sciences, Virtual due to COVID.

Impacts of the Use of Machine Learning on Work Design (PDF)

Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070

The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning (PDF)

Harandi, M., Crowston, K., Jackson, C., & Østerlund, C.. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai’i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719

Impacts of machine learning on work (PDF)

Crowston, K., & Bolici, F.. (2019). Impacts of machine learning on work. In Proceedings of the 52nd Hawai’i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.719