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:

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