@conference {osterlund2024,
	title = {Mutual learning in human-AI interaction},
	booktitle = {Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference},
	year = {2024},
	address = {Honolulu, HI},
	abstract = {<p>We explore the bi-directional relationship between human and machine learning in citizen science. Theoretically, the study draws on the Zone of Proximal Development concept, which allows us to describe the augmentation of human learning by AI, human augmentation of machine learning and how tasks can be designed to facilitate co-augmentation. Methodologically, the study utilizes a design-science approach to explore the design, deployment, and evaluations of the Gravity Spy citizen science project. The findings highlight the challenges and opportunities of co-augmentation, where both humans and machines contribute to each other{\textquoteright}s learning and capabilities.\&nbsp; The research contributes to the existing literature by emphasizing the role of ZPD in citizen science projects, showcasing how the concept supports ongoing learning for volunteers and keeps machine learning aligned with evolving data.</p>},
	attachments = {https://waim.network/sites/crowston.syr.edu/files/TREW_Workshop_Paper.pdf},
	author = {{\O}sterlund, Carsten and Crowston, Kevin and Jackson, Casey B. and Takou-Ayaoh, Marlene and Wu, Yunan and Katsaggelos, Aggelos K.}
}
@article {2020,
	title = {Artificial intelligence and the world of work, a co-constitutive relationship},
	journal = {Journal of the Association for Information Science and Technology},
	year = {2020},
	abstract = {<p>The use of intelligent machines{\textemdash}digital technologies that feature data- driven forms of customization, learning, and autonomous action{\textemdash}is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information profes- sionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination net- work (note: https://waim.network).</p>},
	issn = {2330-1635},
	doi = {10.1002/asi.24388},
	author = {{\O}sterlund, Carsten and Jarrahi, Mohammad Hossein and Willis, Matthew and Boyd, Karen and Wolf, Christine}
}
