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Call for Abstracts: AI and the Future of Citizen Science

CITIZEN SCIENCE: THEORY AND PRACTICE

Special Collection: AI and the Future of Citizen Science

Issue Editors: Lucy Fortson 1a, Kevin Crowston 2,  Laure Kloetzer 3 , Marisa Ponti4.

1 School of Physics and Astronomy, University of Minnesota, USA; lfortson@umn.edu 

2 School of Information Studies, Syracuse University, USA, crowston@syr.edu

3 Institute of Psychology and Education, University of Neuchâtel, Switzerland; laure.kloetzer@unine.ch

Department of Applied Information Technology, University of Gothenburg, Sweden; marisa.ponti@ait.gu.sea Corresponding editor

Citizen Science: Theory and Practice is an open-access, peer-reviewed journal providing a central space for cross-disciplinary, scholarly exchanges aimed at advancing the field of citizen science by providing a venue for citizen science researchers and practitioners to share best practices in conceiving, developing, implementing, evaluating, and sustaining projects that facilitate public participation in scientific endeavors in any discipline.



ISSUE OVERVIEW

The application of artificial intelligence (AI) technologies, including Machine Learning, computer vision, and Natural Language Processing, in citizen science is growing rapidly. AI approaches are becoming more efficient and complex as they develop, and a number of fields, including astronomy, history and literature, environmental justice, ecology and biodiversity, biology and neuroimaging, use them in varying combinations with citizen scientists. This can include collecting meaningful data from critical locations or sorting through large datasets to help solve problems ranging from the hyperlocal to the scale of the Universe. Concerns are being raised, though, about how AI tools may negatively affect volunteer motivation and engagement over time. AI may also reduce the need for human contributions, particularly from less skilled volunteers, depriving them of opportunities to learn and improve. Furthermore, AI can often reproduce systemic biases in our social systems. As scientific and social challenges become more complex, human-machine systems must be designed to maximize their complementary capabilities. Citizen science needs to use AI tools thoughtfully and meaningfully to contribute to both science and society. This special collection will explore how AI technologies and citizen science have been combined in different domains and in different regions of the world, lessons learned, and a glimpse at what the future holds. The collection will also explore the social systems aspects of citizen scientists working alongside AI to provide guidance on the many critical challenges arising in this field, including educational, motivational, ethical and policy issues. As a whole, in addressing both successes and challenges, this special issue will provide both a reference point for practitioners interested in incorporating AI techniques into their citizen science projects and signposting the ways in which AI needs careful consideration by the overarching citizen science community. We therefore seek contributions from across the disciplines including domain researchers, educators, social scientists, ethicists and policy makers.

ARTICLE TYPES

In this special collection, we seek a range of papers including research papers, review and synthesis papers, case studies, and essays, as described by Citizen Science: Theory and Practice. 

We invite proposals for manuscripts about the use of AI technologies in citizen science, which we broadly define to encompass (among other activities) AI analyzing, coding, and classifying data provided, for example, by cameras and telescope images; verifying the accuracy and consistency of volunteers’ submissions; improving volunteers’ training and communication; filtering out repetitive tasks allowing citizen scientists to focus on more interesting tasks; solving complex problems like protein-folding or discovering rare or unknown objects in large datasets.

We will consider articles directed to a broad range of topics relevant to the use of AI in citizen science. We encourage contributions from researchers and practitioners from the global South. Our goal is to provide a safe space for diverse perspectives and contributions to a more inclusive and comprehensive body of knowledge. Citizen science initiatives focusing on issues specific to regions and underrepresented communities, such as monitoring wildlife populations, studying the impact of climate change on agriculture, tracking disease outbreaks, or mapping urban development, are very welcome. We are particularly interested (although not exclusively) in articles that address one or more of the following categories:

  • Practice and process: e.g., forms of human-AI integration in citizen science, including examples specific to a given field; distribution of tasks; reskilling of citizens to leverage AI tools or vice versa.  
  • Human-AI interaction: e.g., documented impacts (both positive or negative) of humans working alongside machines in citizen science.
  • Epistemology: e.g., distributed expertise among humans and machines; trust in the results of algorithmic procedures; the role of explainable AI in citizen science.
  • Ethics, legal aspects, and policy: e.g., responsible use of AI; data ownership; transparency; embedded or inserted bias; potential liability; research informing policy.
  • Learning: e.g., examples of how AI contributes to human learning through citizen science; and conversely, examples of how citizen science may contribute to learning about AI.
  • System design and development of specific AI methods.

We encourage manuscripts that represent diverse disciplines, including (but not limited to) educational sciences, computer science, cognitive science, law, science and technology studies, philosophy and ethics, policy studies, and application domains such as astronomy, biology, history, and environmental science, as well as empirical manuscripts that use a diverse range of methods.

DEADLINES AND LOGISTICS

The preferred method for submitting an abstract is via this Google form link: https://forms.gle/5Uk3Y5rxki1zS7Ma9. However, if you are unable to access or complete the form, please send a query via email to: aifuturecitizenscience@gmail.com (please use the subject line “Abstract Query”). 

The timeline for the special collection is as follows:

  • Abstracts will not be accepted after September 8, 2023 extended to September 18, 2023.
  • Authors of submitted abstracts will be informed whether they will be invited to submit full papers on a rolling basis through October 15, 2023.
  • Papers will be due no later than February 1, 2024. Earlier submission is encouraged to allow time for revision(s). 
  • Papers will be sent for peer review once received. All papers will be reviewed by two reviewers and at least one editor.
  • If accepted for publication, papers will be published in Fall 2024.

When developing your abstract for submission, please consider the following: 

  1. Word count for submitted abstracts:
    1. Maximum 1000 words (not counting title, authors or references)
    2. Maximum 1 figure or table.
  2. Information that you should make sure is covered in your abstract:
    1. General nature of your work – for example:
      1. Is your work theoretical or empirical or both
      2. What types of AI? What tasks specifically?
      3. What types of citizen science (e.g., data collection/data analysis/online citizen science/other)
      4. Which data/projects/domain 
      5. Where is the work in the research life cycle
        1. If it’s empirical, does it have any findings yet
        2. If it’s theoretical, is it grounded in evidence (i.e., arguments should not be just speculation). 
    2. Goals of work including research questions (which category of call, see above)
      1. Process/Practice
      2. Human/AI interaction
      3. Epistemology
      4. Learning
      5. Ethics, Legal Aspects, and Policy
      6. System design and development of specific AI methods
    3. Domain papers must not focus on domain results (e.g., species distributions) but on how AI + volunteer inputs were used to achieve those results.
  3. CSTP-specific information:
    1. Of the following paper types accepted by the journal, please indicate which is intended for your submission:
      1. Research
      2. Review and Synthesis
      3. Case studies
      4. Methods

If you have questions, please email aifuturecitizenscience@gmail.com 

Please review in advance the journal’s scope, author guidelines, and information on publication fees at http://theoryandpractice.citizenscienceassociation.org.

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