This assignment, by Erin Burns, is from the ACRL Framework for Information Literacy Sandbox.
The summary from the site explains:
- Learn how to recognize and mitigate biases in AI algorithms and data and to evaluate and ensure fairness in AI systems, including demographic parity and equal opportunity.
- Understand the ethical issues surrounding data collection, storage, and usage in AI applications.
- Learn about ethical guidelines for AI creators and users.
Key Features of This Assignment
- Bias Mitigation and Fairness in AI
- This workshop teaches participants how to recognize and mitigate biases in AI algorithms and data, ensuring fairness in AI systems by addressing issues such as demographic parity and equal opportunity.
- Ethical Issues in Data Handling
- Participants will examine the ethical concerns surrounding data collection, storage, and usage in AI applications, promoting responsible and ethical handling of data.
- Ethical Guidelines for AI
- The workshop covers ethical guidelines for AI creators and users, providing a framework for developing and deploying AI technologies in a manner that aligns with ethical standards and social justice principles.
Find the full version of this resource on the ACRL Framework for Information Literacy Sandbox website.