Critical AI Literacy for Action Researchers - Kimberly Becker, Moxie
30th May
In a recent gathering, key stakeholders from various organizations explored diverse applications and significant implications of AI technology within their fields. Moderated by Bruce Goldstein and Nick Graham, the session featured an insightful presentation from Kimberly Becker. The discussions spanned practical AI implementations, ethical considerations, and plans for future sessions.
Recording:
Slides:
Kimberly Becker
Ph.D., Co-Founder & COO, is an applied linguist specializing in disciplinary academic writing and English for research publication purposes. She holds a Ph.D. in Applied Linguistics and Technology, has a strong background in teaching, and has published work on ethical AI in academic research.
Key Takeaways:
Moxie focuses on augmentation rather than automation, providing AI tools for research/writing while prioritizing ethics
Introduced a framework for AI literacy: functional, critical, and rhetorical
Highlighted issues of bias and “weirdness” in AI models due to training data
Emphasized environmental impacts of AI and promoting sustainable practices
Discussed the potential for collaborative, community-based AI platforms
Summary:
Topics:
AI Literacy Framework
Functional: Tools, prompting, limitations
Critical: Accuracy, bias, ethics
Rhetorical: Patterns, style, human-AI writing
Bias and "Weirdness"
Bias from training data (Western, educated)
Complexity of neural networks
Racial and gender bias examples
Environmental Impacts
Energy/resource consumption
Monitoring token usage, reducing waste
Sustainability through education
Collaborative Platforms
Community-based, discipline-specific platforms
AI integration with databases like Semantic Scholar
Addressing biases in academic databases