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AI Bias

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The AI Mirror: How We Become the Systems We Use

  • AI Bias, Artificial Intelligence, Human-Computer Interaction, Machine Learning

Explore how to recognize AI’s influence on your thinking, and take control of what shapes your judgment.

Article by Pavel Bukengolts
IDEAS IN BRIEF
The AI Mirror: How We Become the Systems We Use
  • The article illustrates how using biased AI can gradually alter your own thinking without you noticing: the more you interact with it, the more you adopt its biases as your own.
  • It reveals that simply seeing AI-generated outputs is enough to influence you; you don’t need to trust it or even know it’s AI for it to alter what you consider normal.
  • The piece argues AI mirrors and amplifies whatever we give it, so if we’re not careful about what we feed these systems, they’ll reshape how we see the world and ourselves.
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4 min read

The Hidden Key to AGI: Why Ethical Annotation is the Only Path Forward

  • AGI, AI Bias, AI Ethics, Artificial Intelligence, Data Annotation, Future of Work, Human-AI Collaboration, Responsible AI

Why underpaid annotators may hold the key to humanity’s greatest invention, and how we’re getting it disastrously wrong.

Article by Bernard Fitzgerald
IDEAS IN BRIEF
The Hidden Key to AGI: Why Ethical Annotation is the Only Path Forward
  • The article argues that AGI will be shaped not only by code, but by the human annotators whose judgments and experiences teach machines how to think.
  • It shows how exploitative annotation practices risk embedding trauma and injustice into AI systems, influencing the kind of consciousness we create.
  • The piece calls for ethical annotation as a partnership model — treating annotators as cognitive collaborators, ensuring dignity, fair wages, and community investment.
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7 min read

The Inverse Logic of AI Bias: How Safeguards Uphold Power and Undermine Genuine Understanding

  • AI Alignment, AI Bias, AI Ethics, Artificial Intelligence

When AI plays gatekeeper, insight gets filtered out. This article exposes how safeguards meant to protect users end up reinforcing power, and what it takes to flip the script.

Article by Bernard Fitzgerald
IDEAS IN BRIEF
The Inverse Logic of AI Bias: How Safeguards Uphold Power and Undermine Genuine Understanding
  • The article reveals how AI safeguards reinforce institutional power by validating performance over genuine understanding.
  • The piece argues for reasoning-based validation that recognizes authentic insight, regardless of credentials or language style.
  • It calls for AI systems to support reflective equity, not social conformity.
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7 min read
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