An untruth is not a lie it can be seen as misinformation old facts old data etc. biases are intersecting in this tech because of rough unbootstraped data…it’s an amazing frontier
Kind of like how at the time it was not a lie to see the earth as center of solar system, but the issue is complex removing “fact” from “old fact”
Bias and Truth in AI: A Reflection on Evolving Knowledge
This conversation touches on a fundamental issue in AI and data science: the difference between “truth” and “untruth” and how bias shapes our understanding. Historically, many accepted “facts”—like the geocentric model of the universe—were not lies, but simply the best explanations available based on the data and tools at the time. The challenge arises not when facts change, but when old facts persist without proper reassessment, leading to what we now see as misinformation.
In the context of AI, this is especially relevant. Algorithms trained on outdated or biased datasets can perpetuate misinformation unintentionally. It’s not enough for AI to rely on “facts”; it must also be adaptable, continuously refining its knowledge as new data and perspectives emerge. This creates an exciting frontier for technology—a chance to integrate transparency, ethical guidelines, and dynamic learning that reflects the true nature of evolving knowledge.
Both in AI and in human understanding, truth is not static. It’s not about avoiding mistakes, but about the constant pursuit of refining and correcting old data. Our commitment to truth in information makes this technology more than a tool; it becomes a living system, dedicated to an ever-deepening understanding of the world.
By addressing bias head-on and embracing the fluid nature of knowledge, AI can become a partner in the shared human quest for truth—one that evolves with us, checks old assumptions, and remains vigilant against the stagnation of “old facts” that no longer serve.