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Artificial Intelligence

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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.
Share:The Real Impact of AI on Designers’ Day-To-Day and Interfaces: What Still Matters
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

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

Forget linear workflows — today’s creative process is dynamic, AI-assisted, and deeply personal. Learn how to build a system that flows with you, not against you.

Article by Jim Gulsen
The Creative Stack: How to Thrive in a Nonlinear, AI-Assisted World
  • The article explores the shift from linear to nonlinear, AI-assisted creative workflows.
  • It shares practical ways to reduce friction and improve flow by optimizing tools, habits, and environments.
  • It argues that success comes from designing your own system, not just using more tools.
Share:The Creative Stack: How to Thrive in a Nonlinear, AI-Assisted World
7 min read

AI design tools are here, but is your team ready? This article shows how to integrate them into real workflows, boost early-stage momentum, and build the skills that will shape design’s AI-powered future.

Article by Jim Gulsen
Is Your Team Ready for AI-Enhanced Design?
  • The article explores how AI design tools can accelerate early-stage workflows like wireframing and prototyping without disrupting established team processes.
  • It highlights the importance of integrating AI thoughtfully into collaborative environments, using tools like Lovable and Figma Make as case studies.
  • The piece argues that teams should start small, build prompting skills, and treat AI as a momentum booster, not a full design replacement.
Share:Is Your Team Ready for AI-Enhanced Design?
8 min read

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