In the last decade, a great number of organizations have produced documents intended to standardize, in the normative sense, and promote guidance to our recent and rapid AI development. However, the full content and divergence of ideas presented in these documents have not yet been analyzed, except for a few meta-analyses and critical reviews of the field. In this work, we seek to expand on the work done by past researchers and create a tool for better data visualization of the contents and nature of these documents. We also provide our critical analysis of the results acquired by the application of our tool into a sample size of 200 documents.
The database of AI ethics guidelines they used: https://inventory.algorithmwatch.org/
Professor at George Washington University
I am a Professor with Human-Technology Collaboration and Educational Technology programs at George Washington University in Washington DC. I have written 12 books and more than 100 articles, and I co-host of the Parsing Science podcast where scientists tell the stories behind their research. I am also the developer of the WeShareScience.com online platform for sharing research videos, and SciencePods.com where researchers can create free podcasts about their science. My research interests include human interactions with intelligent machines, needs, needs assessments, and instructional design.
Latest posts by Ryan Watkins (see all)
- Observing many students using difference-in-differences designs on the same data and hypothesis reveals a universe of uncertainty - June 8, 2025
- Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks - June 7, 2025
- Neural and Cognitive Impacts of AI: The Influence of Task Subjectivity on Human-LLM Collaboration - June 5, 2025