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Artificial Intelligence

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AI is changing the way we design — turning ideas into working prototypes in minutes and blurring the line between designer and developer. What happens when anyone can build?

Article by Jacquelyn Halpern
The Future of Product Design in an AI-Driven World
  • The article shows how AI tools let designers build working prototypes quickly just by using natural language.
  • It explains how AI helps designers take on more technical roles, even without strong coding skills.
  • The piece imagines a future where anyone with an idea can create and test products easily, speeding up innovation for everyone.
Share:The Future of Product Design in an AI-Driven World
4 min read

Forget chatbots — Agentic AI is redefining how work gets done. Discover the myths holding businesses back and what it really takes to build AI with true agency.

Article by Josh Tyson
Five Myths Debunked: Why Agentic AI Is Much More Than Chatbots
  • The article reframes Agentic AI not as a tool, but as a strategic approach to automating high-value tasks through orchestration and dynamic objectives.
  • It argues that success with Agentic AI lies in starting small, experimenting quickly, and integrating agents around outcomes — not traditional workflows.
  • The piece emphasizes the need for open, flexible platforms that enable multi-agent collaboration, rapid iteration, and seamless integration with legacy systems.
Share:Five Myths Debunked: Why Agentic AI Is Much More Than Chatbots
8 min read

AI won’t take the blame — you will. In the age of automation, real leadership means owning the outcomes, not just the tools.

Article by Anthony Franco
The AI Accountability Gap
  • The article reveals how AI doesn’t remove human responsibility — it intensifies it, requiring clear ownership of outcomes at every level of deployment.
  • It argues that successful AI adoption hinges not on technical skills alone, but on leadership: defining objectives, managing risks, and taking responsibility when things go wrong.
  • It emphasizes that organizations able to establish strong human accountability systems will not only avoid failure but also accelerate AI-driven innovation with confidence.
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4 min read

How is AI really changing the way designers work, and what still depends on human skill? This honest take cuts through the hype to show where AI helps, where it falls short, and what great design still demands.

Article by Oleh Osadchyi
The Real Impact of AI on Designers’ Day-To-Day and Interfaces: What Still Matters
  • The article explores how AI is reshaping designers’ workflows, offering speed and support across research, implementation, and testing.
  • It argues that while AI is useful, it lacks depth and context — making human judgment, critical thinking, and user insight indispensable.
  • It emphasizes that core design principles remain unchanged, and designers must learn to integrate AI without losing their craft.
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9 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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