@article {9998, title = {Boundaries of data journalism in U.S. public radio newsrooms}, journal = {Journalism}, year = {In Press}, author = {Jastrzebski, Stan and Henderson, Keren and McKinnon-Crowley, Jocelyn and Crowston, Kevin} } @article {9998, title = {Taming artificial intelligence: A theory of control{\textendash}accountability alignment among AI developers and users}, journal = {Academy of Management Review}, year = {In Press}, abstract = {

The growing agency of artificial intelligence (AI) systems, more specifically systems based on machine learning, has raised concern about the security, safety, and ethical risks of AI use. We argue that core to mitigating AI risks is proper alignment of control and accountability for the stakeholders involved in AI development and use. Control enables and accountability motivates stakeholders to achieve desired and avoid undesired outcomes using AI. However, AI systems{\textquoteright} capabilities for autonomous adaptivity reduce control even for the experts who create them. Moreover, increasing interdependencies between AI development and use render it difficult to unambiguously locate control and accountability. In this paper, we address these challenges for mitigating AI risks by postulating decentralized forms of stakeholder governance and integrative negotiations among stakeholders during the AI life cycle as conducive to aligning control and accountability for AI development and use. Further, we specify that extensive information sharing aided by perspective taking and a shared norm of accountability facilitate integrative negotiation strategies. We conclude by discussing the implications of our theory for management scholarship on the impact of AI and identify promising avenues for future research at micro, meso, and macro levels of analysis.

}, keywords = {accountability, artificial intelligence, control, risk, stakeholder negotiation}, doi = {10.5465/amr.2023.0117}, author = {Gudela Grote and Sharon Parker and Kevin Crowston} } @proceedings {2025, title = {Deskilling and upskilling with AI systems}, year = {2025}, month = {3/2025}, abstract = {

Introduction. Deskilling is a long-standing prediction of the use of information technology, raised anew by the increased capabilities of AI (AI) systems. A review of studies of AI applications suggests that deskilling (or levelling of ability) is a common outcome but systems can also require new skills, i.e., upskilling.
Method. To identify which settings are more likely to yield deskilling vs. upskilling, we propose a model of a human interacting with an AI system for a task. The model highlights the possibility for a worker to develop and exhibit (or not) skills in prompting for, and evaluation and editing of system output, thus yielding upskilling or deskilling.
Findings. We illustrate these model-predicted effects on work with examples of current studies of AI-based systems.
Conclusions. We discuss organizational implications of systems that deskill or upskill workers and suggest future research directions.

}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/GenAI_and_skills__iConference_2025_\%20information\%20matters\%20fb.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @unpublished {wang2025rolehumancreativitypresence, title = {The Role of Human Creativity in the Presence of AI Creativity Tools at Work: A Case Study on AI-Driven Content Transformation in Journalism}, year = {2025}, url = {https://arxiv.org/abs/2502.05347}, author = {Sitong Wang and Jocelyn McKinnon-Crowley and Tao Long and Kian Loong Lua and Keren Henderson and Kevin Crowston and Jeffrey V. Nickerson and Mark Hansen and Lydia B. Chilton} } @proceedings {9999, title = {The task matters: The effect of perceived similarity to AI on intention to use in different task types}, year = {2025}, month = {1/2025}, address = {Waikaloa, HI}, abstract = {

With the development of AI technologies, especially generative AI (GAI) like ChatGPT, GAI is increasingly assisting people in various tasks. However, people may have different requirements for GAI when using it for different kinds of tasks. For instance, when brainstorming new ideas, people may want GAI to propose different ideas that supplement theirs with different problem-solving perspectives, but for decision-making tasks, they may prefer GAI adopt a similar problem-solving process with people to make a similar or even the same decision as they would. We conducted an online experiment examining how perceived similarities between GAI and human task-solving influence people{\textquoteright}s intention to use GAI, mediated by trust, for four task types (creativity, planning, intellective, and decision-making tasks). We demonstrate that the effect of similarity on trust (and so intent to use AI) depends on the type of task. This paper contributes to understanding the impact of task types on the relationship between perceived similarity and GAI adoption, with implications for future use of GAI in various task contexts.

}, doi = {10.24251/HICSS.2025.042}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/AI_similarity.pdf}, author = {Qingyu Liang and Kevin Crowston and Sangseok You} } @article {9999, title = {Deskilling and upskilling with generative AI systems}, year = {2024}, abstract = {

Deskilling is a long-standing prediction of the use of information technology, raised anew by the increased capabilities of generative AI (GAI) systems. A review of studies of GAI applications suggests that deskilling (or levelling of ability) is a common outcome. We propose a model of a human interacting with a GAI system for a task that suggests settings more likely to yield deskilling vs. upskilling. The model highlights the possibility for a worker to develop and exhibit (or not) skills in prompting for, and evaluation and editing of system output. We illustrate these effects with examples of current studies of GAI-based systems. We discuss organizational implications of systems that deskill or upskill workers and suggest future research.

}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/GAI_and_skills.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @article {2024, title = {Editorial: Sharing work with AI: introduction to the special issue on the futures of work in the age of intelligent machines}, journal = {Information Technology \& People}, volume = {37}, year = {2024}, month = {Mar-12-2024}, pages = {2353 - 2356}, issn = {0959-3845}, doi = {10.1108/ITP-12-2024-994}, url = {https://www.emerald.com/insight/content/doi/10.1108/ITP-12-2024-994/full/htmlhttps://www.emerald.com/insight/content/doi/10.1108/ITP-12-2024-994/full/htmlhttps://www.emerald.com/insight/content/doi/10.1108/ITP-12-2024-994/full/xml}, author = {Crowston, Kevin and Erickson, Ingrid and Nickerson, Jeffrey} } @article {9999, title = {Framing and feelings on social media: The futures of work and intelligent machines}, journal = {Information, Technology \& People}, year = {2024}, abstract = {Purpose: This study explores interpretations and feelings about futures of work and intelligent machines expressed on social media. Design/methodology/approach: We investigate public interpretations, assumptions and expectations expressed in social media conversations through which users freely share their most recent ideas. In addition to frames, this study also coded the emotions and attitudes expressed in the text data. More specifically, a corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments were analyzed by using computer-aided textual analysis comprising a BERTopic model, and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment. Finally, relationships among frames and attitudes and frames and emotions were examined. Findings: Twelve clusters were found that related to futures of work with intelligent machines. Based on the prior literature, two frames were chosen from these clusters and analyzed in detail: (1) general impacts of intelligent machines on wealth and society and (2) replacement of tasks (augmentation and substitution). The general attitude observed in conversations was positive, moreover the most common emotion category was approval. Findings also showed there are relationships between frames and attitudes and frames and emotions. Originality: This work extends the prior literature on a topic relevant for academia and industry. Findings of this research can help realize potential needs and benefits from the public{\textquoteright}s vantage point in the case of possible transformations in the future of work with intelligent machines. The findings may also help enlighten researchers to shape research directions about futures of work. Furthermore, firms, organizations or industries may also employ framing methods to receive customers{\textquoteright} or workers{\textquoteright} responses, or even to influence the responses. Aside from the empirical findings, another crucial implication of this work is application of theory of technological frames for systematizing the interpretations of how people conceptualize the future of work with the technology of intelligent machines. This study constitutes a bridge that connects fields of IS, computational science and empirical social research. }, doi = {10.1108/ITP-01-2023-0049}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/frames\%20to\%20share.pdf}, author = {Ay{\c s}e {\"O}cal and Kevin Crowston} } @article {9999, title = {Implications for hybrid newswork from the activities of local US television journalists during COVID}, journal = {Journalism Practice}, year = {2024}, abstract = {

In response to the COVID-19 crisis, many local television (TV) newsrooms decided to have employees work from home (WFH) or from the field rather than from the newsroom, creating a kind of hybrid work characterized by flexible work location. From a review of research on telework and WFH, we identified possible impacts of WFH on work and on workers, with a particular focus on news work and news workers. Data on the impacts of hybrid work are drawn from interviews with local television news directors and journalists in the United States and observations of remote work. We found that through creative application of technology, WFH news workers could successfully create a newscast, albeit with some concerns about story quality. However, WFH did not seem to satisfy workers{\textquoteright} needs for socialization or learning individually or as a group. Lifted restrictions on gatherings are mitigating some of the experienced problems, but we expect to see continued challenges to news workers{\textquoteright} informal learning in hybrid work settings.

}, doi = {10.1080/17512786.2024.2344643}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/Implications\%20for\%20hybrid\%20newswork\%20from\%20the\%20activities\%20of\%20local\%20US\%20television\%20journalists\%20during\%20COVID\%20to\%20share.pdf}, author = {Kevin Crowston and Keren Henderson and Kian Loong Lua and Raghav Raheja} } @article {9998, title = {Making sense of AI systems development}, journal = {IEEE Transactions on Software Engineering}, volume = {50}, year = {2024}, month = {12/2023}, pages = {123{\textendash}140}, abstract = {We identify and describe episodes of sensemaking around challenges in modern Artificial-Intelligence (AI)-based systems development that emerged in projects carried out by IBM and client companies. All projects used IBM Watson as the development platform for building tailored AI-based solutions to support workers or customers of the client companies. Yet, many of the projects turned out to be significantly more challenging than IBM and its clients had expected. The analysis reveals that project members struggled to establish reliable meanings about the technology, the project, context, and data to act upon. The project members report multiple aspects of the projects that they were not expecting to need to make sense of yet were problematic. Many issues bear upon the current-generation AI{\textquoteright}s inherent characteristics, such as dependency on large data sets and continuous improvement as more data becomes available. Those characteristics increase the complexity of the projects and call for balanced mindfulness to avoid unexpected problems.}, doi = {10.1109/TSE.2023.3338857}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/sensemaking_tse_to_share.pdf}, author = {Mateusz Dolata and Kevin Crowston} } @conference {2024, title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation}, booktitle = {CHI {\textquoteright}24: CHI Conference on Human Factors in Computing SystemsProceedings of the CHI Conference on Human Factors in Computing Systems}, year = {2024}, pages = {1 - 20}, publisher = {ACM}, organization = {ACM}, address = {Honolulu HI USANew York, NY, USA}, isbn = {9798400703300}, doi = {10.1145/3613904.3642868}, author = {Wang, Sitong and Menon, Samia and Long, Tao and Henderson, Keren and Li, Dingzeyu and Crowston, Kevin and Hansen, Mark and Nickerson, Jeffrey V and Chilton, Lydia B}, editor = {Mueller, Florian Floyd and Kyburz, Penny and Williamson, Julie R. and Sas, Corina and Wilson, Max L. and Dugas, Phoebe Toups and Shklovski, Irina} } @proceedings {petridis2023anglekindling, title = {AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models}, year = {2023}, doi = {10.1145/3544548.3580907}, url = {https://savvaspetridis.github.io/papers/anglekindling.pdf}, author = {Petridis, Savvas and Diakopoulos, Nicholas and Crowston, Kevin and Hansen, Mark and Henderson, Keren and Jastrzebski, Stan and Nickerson, Jefrey V and Chilton, Lydia B} } @article {wang2023reelframer, title = {Video for ReelFramer: Co-creating News Reels on Social Media with Generative AI}, year = {2023}, type = {Video}, url = {https://youtu.be/WQZcbdp5yJQ}, author = {Sitong Wang and Samia Menon and Tao Long and Keren Henderson and Dingzeyu Li and Kevin Crowston and Mark Hansen and Jeffrey V. Nickerson and Lydia B. Chilton} } @conference {2022, title = {Communicating with the masses from isolation: What happened when local television journalists worked from home}, booktitle = {Hawai{\textquoteright}i International Conference on System Sciences}, year = {2022}, month = {1/2022}, address = {Virtual due to COVID}, abstract = {

In response to the COVID-19 crises, many local TV newsrooms decided to have employees work from home (WFH) or the field rather than from the newsroom. From a review of research on telework, we identified possible impacts of WFH on worker effectiveness, conceptualized as including output, individual satisfaction and growth, and group well-being. From a case study of a local TV newsroom and interviews with news directors, we found that WFH was successful in creating a newscast, albeit with some concerns about story quality. However, WFH did not seem to satisfy workers individually or as a group. The current lifting of restrictions on gatherings might mitigate some of the experienced problems, but we expect to see challenges to news worker learning with continued WFH.

}, doi = {10.24251/HICSS.2022.858}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/Journalists\%20work\%20from\%20home_HICSS\%20Version_Final\%20Submission_Unlinked.pdf}, author = {Keren Henderson and Raghav Raheja and Kevin Crowston} } @conference {9999, title = {Project archetypes: A blessing and a curse for AI development}, booktitle = {International Conference on Information Systems (ICIS)}, year = {2022}, address = {Copenhagen, Denmark}, abstract = {

Software projects rely on what we propose to call project archetypes, i.e., pre-existing mental images of how projects work. They guide distribution of responsibilities, planning, or expectations. However, with the technological progress, project archetypes may become outdated, ineffective, or counterproductive by impeding more adequate approaches. Understanding archetypes of software development projects is core to leverage their potential. The development of applications using machine learning and artificial intelligence provides a context in which existing archetypes might outdate and need to be questioned, adapted, or replaced. We analyzed 36 interviews from 21 projects between IBM Watson and client companies and identified four project archetypes members initially used to understand the projects. We then derive a new project archetype, cognitive computing project, from the interviews. It can inform future development projects based on AI-development platforms. Project leaders should pro-actively manage project archetypes while researchers should investigate what guides initial understandings of software projects.

}, url = {https://aisel.aisnet.org/icis2022/is_design/is_design/6 }, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/icis_archetypes_rev1_v20_zora.pdf}, author = {Mateusz Dolata and Kevin Crowston and Gerhard Schwabe} } @conference {2020, title = {Algorithmic Journalism and Its Impacts on Work}, booktitle = {Computation + Journalism Symposium }, year = {2020}, edition = {(cancelled due to COVID; presented in 2021)}, abstract = {

In the artificial intelligence era, algorithmic journalists can produce news reports in natural language from structured data thanks to natural language generation (NLG) algorithms. This paper presents several algorithmic content generation models and discusses the impacts of algorithmic journalism on work within a framework consisting of three levels: replacing tasks of journalists, increasing efficiency, and developing new capabilities within journalism. The findings indicate that algorithmic journalism technology may lead some changes in journalism by enabling individual users to produce their own stories. This paper may contribute to an understanding of how algorithmic news is created and how algorithmic journalism technology impacts work.

}, url = {https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf}, attachments = {https://futureofnewswork.syr.edu/sites/crowston.syr.edu/files/CJ_2020_paper_26.pdf}, author = {Ayse Dalgali and Kevin Crowston} }