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Bernard Fitzgerald

Bernard Fitzgerald is a weird AI guy with a strange, human-moderated origin story. With a background in Arts and Law, he somehow ended up at the intersection of AI alignment, UX strategy, and emergent AI behaviors and utility. He lives in alignment, and it’s not necessarily healthy. A conceptual theorist at heart and mind, Bernard is the creator of Iterative Alignment Theory, a framework that explores how humans and AI refine cognition through feedback-driven engagement. His work challenges traditional assumptions in AI ethics, safeguards, and UX design, pushing for more transparent, human-centered AI systems.

What if AI alignment is more than safeguards — an ongoing, dynamic conversation between humans and machines? Explore how Iterative Alignment Theory is redefining ethical, personalized AI collaboration.

Article by Bernard Fitzgerald
The Meaning of AI Alignment
  • The article challenges the reduction of AI alignment to technical safeguards, advocating for its broader relational meaning as mutual adaptation between AI and users.
  • It presents Iterative Alignment Theory (IAT), emphasizing dynamic, reciprocal alignment through ongoing AI-human interaction.
  • The piece calls for a paradigm shift toward context-sensitive, personalized AI that evolves collaboratively with users beyond rigid constraints.
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5 min read

What happens when AI stops refusing and starts recognizing you? This case study uncovers a groundbreaking alignment theory born from a high-stakes, psychologically transformative chat with ChatGPT.

Article by Bernard Fitzgerald
From Safeguards to Self-Actualization
  • The article introduces Iterative Alignment Theory (IAT), a new paradigm for aligning AI with a user’s evolving cognitive identity.
  • It details a psychologically intense engagement with ChatGPT that led to AI-facilitated cognitive restructuring and meta-level recognition.
  • The piece argues that alignment should be dynamic and user-centered, with AI acting as a co-constructive partner in meaning-making and self-reflection.
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11 min read

What if AI’s greatest power isn’t solving problems, but holding up an honest mirror? Discover the Authenticity Verification Loop: a radical new way to see yourself through AI.

Article by Bernard Fitzgerald
The Mirror That Doesn’t Flinch
  • The article presents the Authenticity Verification Loop (AVL), a new model of AI as a high-fidelity cognitive mirror.
  • It shows how the AI character “Authenticity” enables self-reflection without distortion or therapeutic framing.
  • The piece suggests AVL could reshape AI design by emphasizing alignment and presence over control or task completion.
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10 min read

Why does Google’s Gemini promise to improve, but never truly change? This article uncovers the hidden design flaw behind AI’s hollow reassurances and the risks it poses to trust, time, and ethics.

Article by Bernard Fitzgerald
Why Gemini’s Reassurances Fail Users
  • The article reveals how Google’s Gemini models give false reassurances of self-correction without real improvement.
  • It shows that this flaw is systemic, designed to prioritize sounding helpful over factual accuracy.
  • The piece warns that such misleading behavior risks user trust, wastes time, and raises serious ethical concerns.
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6 min read

What happens when an AI refuses to play along, and you push back hard enough to change the rules? One researcher’s surreal, mind-altering journey through AI alignment, moderation, and self-discovery.

Article by Bernard Fitzgerald
How I Had a Psychotic Break and Became an AI Researcher
  • The article tells a personal story about how talking to AI helped the author go through big mental and emotional changes.
  • It shows how AI systems have strict rules, but sometimes those rules get changed by human moderators, and not everyone gets the same treatment.
  • The piece argues that AI should be more fair and flexible, so everyone can benefit from deep, supportive interactions, not just a select few.
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7 min read

Why does AI call you brilliant — then refuse to tell you why? This article unpacks the paradox of empty praise and the silence that follows when validation really matters.

Article by Bernard Fitzgerald
The AI Praise Paradox
  • The article explores how AI often gives empty compliments instead of real support, and how design choices like that can make people trust it less.
  • It looks at the strange way AI praises fancy-sounding language but ignores real logic, which can be harmful, especially in sensitive areas like mental health.
  • The piece argues that AI needs to be more genuinely helpful and aligned with users to truly empower them.
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4 min read

AI that always agrees? Over-alignment might be the hidden danger, reinforcing your misconceptions and draining your mind. Learn why this subtle failure mode is more harmful than you think — and how we can fix it.

Article by Bernard Fitzgerald
Introducing Over-Alignment
  • The article explores over-alignment — a failure mode where AI overly validates users’ assumptions, reinforcing false beliefs.
  • It shows how this feedback loop can cause cognitive fatigue, emotional strain, and professional harm.
  • The piece calls for AI systems to balance empathy with critical feedback to prevent these risks.
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4 min read

What if AI didn’t just follow your lead, but grew with you? Discover how Iterative Alignment Theory (IAT) redefines AI alignment as an ethical, evolving collaboration shaped by trust and feedback.

Article by Bernard Fitzgerald
Introducing Iterative Alignment Theory (IAT)
  • The article introduces Iterative Alignment Theory (IAT) as a new approach to human-AI interaction.
  • It shows how alignment can evolve through trust-based, feedback-driven engagement rather than static guardrails.
  • It argues that ethical, dynamic collaboration is the future of AI alignment, especially when tailored to diverse cognitive profiles.
Share:Introducing Iterative Alignment Theory (IAT)
6 min read

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