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Home ›› Artificial Intelligence ›› Human-AI Interaction

Human-AI Interaction

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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.
Share:The AI Praise Paradox
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

Designing for AI? Know what your agent can actually do. This guide breaks down the four core capabilities every UX designer must understand to build smarter, safer, and more user-centered AI experiences.

Article by Greg Nudelman
Secrets of Agentic UX: Emerging Design Patterns for Human Interaction with AI Agents
  • The article examines how UX designers can effectively work with AI agents by understanding the four key capability types that shape agent behavior and user interaction.
  • It emphasizes the importance of evaluating an AI agent’s perception, reasoning, action, and learning abilities early in the design process to create experiences that are realistic, ethical, and user-centered.
  • The piece provides practical frameworks and examples — from smart home devices to healthcare bots — to help designers ask the right questions, collaborate cross-functionally, and scope AI use responsibly.
Share:Secrets of Agentic UX: Emerging Design Patterns for Human Interaction with AI Agents
10 min read

The era of hype-driven AI products is over. It’s time for a smarter approach: building reliable, tailored tools that focus on real value for domain experts, streamline workflows, and enhance AI-human collaboration. Discover the principles guiding the next generation of AI innovation.

Article by Varun Aggarwal, Kuldeep Yadav
It Is Time to Build the 2nd Generation of AI Products
  • The article critiques first-generation AI products, highlighting the need for AI solutions to address real problems.
  • It advocates building for domain experts, ensuring AI reliability, and using tailored models for specific tasks.
  • The piece stresses creating AI-first workflows and improving AI-human collaboration for better productivity.
Share:It Is Time to Build the 2nd Generation of AI Products
6 min read

Discover how UX designers can go beyond interfaces with agent-centered design. Learn to define agent roles, foster collaboration, and build trust for smarter, more adaptable AI systems.

Article by Ishaani M
Demystifying Designing an Agent
  • The article introduces a framework for designing AI agents with agent-centered design, focusing on agent roles, communication, and user engagement.
  • It highlights setting clear human-AI collaboration and building trust through transparency.
  • The piece urges UX designers to think beyond interfaces to create adaptable, intelligent systems.
Share:Demystifying Designing an Agent
7 min read

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