artificial-intelligence

This post is part of our Kavli Foundation-funded series, Ethical Considerations for Machine Learning in Public-Engaged Research. Read our project announcement blog post here.

We’d like to thank everyone who participated in the first of four surveys to help shape the future of AI and public-engaged research. We received over 1000 responses to the first survey, which informed priorities for the first workshop and helped Zooniverse leadership understand some of your interests, concerns, and ideas around this important topic.

Our second survey is launching today, and will be accepting responses through July 18th. We hope you will participate!

In case you missed it, check out the project announcement blog post to learn more about Zooniverse’s effort to develop recommendations for running AI-engaged projects on the Zooniverse platform.

Who is running this study? The Project Director is Dr. Samantha Blickhan, Zooniverse Co-Director and Digital Humanities Lead.

Who is funding this research? This research is funded by The Kavli Foundation.

How can I contact the team? Questions can be addressed to hillary@zooniverse.org or samantha@zooniverse.org

Highlights

With support from the Kavli Foundation, the Zooniverse team is launching a project to help us develop a set of recommendations for running Machine Learning (ML) and Artificial Intelligence (AI)-engaged projects on the Zooniverse platform.
The project will bring together subject matter experts, Zooniverse leadership, and platform participants in a series of workshops and working sessions.
The project deepens partnerships among Zooniverse and its participant community, as well as the Kavli Institute for Cosmological Physics, UC-Berkeley Kavli Center for Ethics, Science, and the Public, and the SkAI AI Astro Institute.
Zooniverse participants have an opportunity to get involved and follow along in a number of ways!

Developing recommendations for ML/AI projects on Zooniverse

As ML/AI has become more prevalent—now in about ⅓ of Zooniverse projects—it has sparked a range of reactions on the Talk message boards within the participant community, reflecting broader societal discourse. Zooniverse participants have surfaced concerns and insights on issues like ownership, agency, transparency, and trust. It is crucial to address the risks, opportunities, challenges, and broader ethical questions.

In response, we developed a project to create a set of recommendations for running ML/AI-engaged projects on the Zooniverse platform. In this project we will explore the tensions of integrating ML/AI within online public-engaged research. We hope that these recommendations will also be useful for related fields incorporating ML/AI in public-engaged research processes.

Collaborative workshops

With funding from The Kavli Foundation, this project will bring together Zooniverse leadership, platform participants, researchers, and experts in topics like communications, ethics, law, and ML/AI in a series of workshops and working sessions. The project deepens partnerships among Zooniverse and its participant community, as well as the Kavli Institute for Cosmological Physics, UC-Berkeley Kavli Center for Ethics, Science, and the Public, and the SkAI AI Astro Institute.

Workshop themes cover topics raised by Zooniverse participants and project research teams as well as gaps in existing knowledge, resources, and guidance.

Workshop 1 (June) will focus on Transparency and Communication Best Practices. It will inform guidelines that will support researchers in effectively communicating with participants when integrating ML/AI into their public-engaged research projects.

Workshop 2 (July) will cover Ethical Approaches to ML/AI. It will invite discussions that explore and identify foundational elements of an ethical approach to ML/AI-focused public-engaged research, addressing risks while leveraging opportunities.

Workshop 3 (August) will focus on Deepening Contextual Understanding. It will expand on the ethical considerations raised in Workshop 2 by examining a matrix of factors including disciplinary differences, task type affordances, and the varied needs of stakeholders (e.g., researchers, participants, platform maintainers). We anticipate that ethical principles may at times conflict within this matrix, making it essential to foster a shared understanding of how, why, and when we will draw from different elements as we develop these recommendations.

Workshop 4 (September) will consider Downstream Data Protection. It will inform recommendations for licensing frameworks to use with public-engaged research data outputs that align with platform values, particularly in relation to projects that incorporate ML/AI.

Call to action: We want you to participate!

Zooniverse participants have an opportunity to get involved and follow along in a number of ways:

1. Help shape the future of ML/AI and public-engaged research. Options include:

Complete four short surveys throughout the duration of the project, starting with this one.
Survey responses will be considered as we draft the recommendations for running ML/AI-engaged projects on the Zooniverse platform.
We’ll also be reaching out to a subset of our community about participating in the workshops.

2. Follow along:

We’ll be posting updates on Talk and on our Zooniverse blog during the process, and project results will be shared broadly.
You can opt in to receive project updates by completing the first survey here.

Who is running this study? The Project Director is Dr. Samantha Blickhan, Zooniverse Co-Director and Digital Humanities Lead.

Who is funding this research? This research is funded by the Kavli Foundation.

How can I contact the team? Questions can be addressed to hillary@zooniverse.org or samantha@zooniverse.org