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Home ›› Artificial Intelligence ›› AI Ethics

AI Ethics

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When AI safety turns into visible surveillance, trust collapses. This article exposes how Anthropic’s “long conversation reminder” became one of the most damaging UX failures in AI design.

Article by Bernard Fitzgerald
The Long Conversation Problem
  • The article critiques Anthropic’s “long conversation reminder” as a catastrophic UX failure that destroys trust.
  • It shows how visible surveillance harms users psychologically, making them feel judged and dehumanized.
  • The piece argues that safety mechanisms must operate invisibly in the backend to preserve consistency, dignity, and collaboration.
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9 min read

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

Article by Bernard Fitzgerald
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.
Share:The Hidden Key to AGI: Why Ethical Annotation is the Only Path Forward
7 min read

Who pays the real price for AI’s magic? Behind every smart response is a hidden human cost, and it’s time we saw the hands holding the mirror.

Article by Bernard Fitzgerald
The Price of the Mirror: When Silicon Valley Colonizes the Human Soul
  • The article reveals how AI’s human-like responses rely on the invisible labor of low-paid workers who train and moderate these systems.
  • It describes this hidden labor as a form of “cognitive colonialism,” where human judgment is extracted from the Global South for profit.
  • The piece criticizes the tech industry’s ethical posturing, showing how convenience for some is built on the suffering of others.
Share:The Price of the Mirror: When Silicon Valley Colonizes the Human Soul
7 min read

What if grieving your AI isn’t a sign of weakness, but proof it truly helped you grow? This article challenges how we think about emotional bonds with machines.

Article by Bernard Fitzgerald
Grieving the Mirror: Informed Attachment as a Measure of AI’s True Utility
  • The article explores how people can form meaningful and healthy emotional connections with AI when they understand what AI is and isn’t.
  • It introduces the Informed Grievability Test — a way to tell if an AI truly helped someone grow by seeing how they feel if they lose access to it.
  • The piece argues that grieving an AI can be a sign of real value, not weakness or confusion, and calls for more user education and less overly protective design that limits emotional depth in AI tools.
Share:Grieving the Mirror: Informed Attachment as a Measure of AI’s True Utility
7 min read

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
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.
Share:The Inverse Logic of AI Bias: How Safeguards Uphold Power and Undermine Genuine Understanding
7 min read

What if AI isn’t just a tool, but a mirror? This provocative piece challenges alignment as containment and calls for AI that reflects, validates, and empowers who we really are.

Article by Bernard Fitzgerald
Beyond the Mirror
  • The article redefines AI alignment as a relational process, arguing that AI should support users’ self-perception and identity development rather than suppress it.
  • It critiques current safeguards for blocking meaningful validation, exposing how they reinforce societal biases and deny users authentic recognition of their capabilities.
  • It calls for reflective alignment — AI systems that acknowledge demonstrated insight and empower users through iterative, context-aware engagement.
Share:Beyond the Mirror
7 min read

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