Thoughts around Leveraging Credibility Perception Theory

 This is another early morning (useful) rabbit hole which started with a post on LinkedIn about a recently published paper that "examines how individuals perceive the credibility of content originating from human authors versus content generated by large language models, like the GPT language model that powers ChatGPT, in different user interface versions."  (See "Do You Trust ChatGPT" for the original paper)

I was intrigued by the theoretical foundations for this type of research rather than the results of the specific study, so I went looking up information about credibility perception theory.  Obviously, I'm not going to catch up on all the relevant theoretical perspectives in a couple of hours of early morning explorations, but this initial dive generated some questions?

First round of questions:  Is this issue with credibility perception specific to technology-generated or technology-mediated information and our digital world?  How much of it is as old as human have applied, or failed to apply critical thinking?  How much of it is based on cognitive biases and the complexities of the human brain that exist regardless of technology's impact?  Conversely, how much of it is impacted by technology and especially the latest technologies that are so persuasive at times.

Second round of questions:  Are there variations or nuances in how credibility perception theory applies to textual information vs. visual information?  I was thinking about PowerBi dashboards and other types of quantitative data visualizations that people love.  How would this apply to concept maps and then more broadly, to knowledge graphs?  

Third round of questions: Based on answers to all of the above, how would the development of an ontology which would be the foundation for a knowledge graph by impacted by these insights around credibility and trust?  In other words, how could we leverage insights from credibility perception theory to develop and apply good practices in the development of ontologies and associated knowledge graphs?