Archive · 19 Aug 2025
The Reality of Bias in AI: A Persistent Challenge
Imagine robots that can answer any question.
The US government wants these robots to be fair and not take sides.
But the article says that’s impossible.
AI learns from what humans tell it and the information it's given, which is often biased.
Think about maps – they have to bend the world to fit on paper.
Similarly, AI models take the world and change it.
Some AI favors one side of a debate or censors information.
The article reminds us that everything we make is based on our own viewpoint, so it is difficult to make a truly neutral AI.
U.S. government seeks unbiased AI for federal use, contradicting the concept.
Studies show language models often lean left in responses, showcasing bias.
Chinese AI censors topics like Tiananmen Square, aligning with government views.
Organizing information inherently involves distortion, as seen in cartography and library systems.
AI models learn from biased human-created data and system prompts, inheriting biases.
- Who
- AI companies and the US government.
- What
- The impossibility of creating unbiased AI models.
- When
- July, 2024
- Where
- United States
- Why
- Because AI models are trained on human-created data, they inherently reflect biases.
- Event
- US government's push for unbiased AI
- Bias Examples
- Left-leaning viewpoints and Chinese censorship
- Mercator Projection
- Distorts size of landmasses
- Dewey Decimal System
- Has shown biases based on the time of its development.
- Grok AI
- Designed to counter perceived 'liberal bias'