Insights

The Trust Journey Framework

The Trust Journey Framework maps how trust forms, breaks, and recovers in AI systems. A practical five-stage design framework for building trustworthy AI experiences.

AI Burnout — The Silent Erosion

AI burnout isn’t dramatic collapse — it’s silent erosion. Designers report feeling like project managers rather than creators, experiencing “boundless responsibility without control.” Riley Coleman diagnoses what makes AI burnout different from regular burnout and offers evidence-based strategies for protecting the pause where creative value lives.

How Public Humiliation Made Figma Stronger

Deep dive into Figma's Make Designs crisis and recovery using the Trust Journey Framework. Learn how accountability, expectation calibration, and community collaboration transformed a public AI failure into stronger customer relationships.

3 Reasons Strategic Friction is Key to AI

Why deliberate slowness is essential as AI accelerates everything. Strategic friction protects ethics, creativity, and trust—three elements that require intentional pauses to flourish in an AI-powered world.

When NOT to Use AI Decision Making: 5-Question Framework

A practical framework for identifying when human judgment must override AI recommendations. The 5-Question Framework helps leaders navigate high-stakes decisions involving direct harm, missing context, trust, equity, and precedent.

How Microsoft's Design Team Transformed Their Practice with AI

How Microsoft UX teams restructured workflows to integrate generative AI as a collaborative partner. Learn about their Three-Tier Integration Model and why 85% of designers now reach quality first drafts faster.

AI Design Community Learning

Why community-driven learning is essential when individual learning is mathematically impossible for AI design mastery. Mastering AI design requires 200+ hours while technology advances monthly, making solo learning obsolete faster than acquisition.

Business Case for Trustworthy AI Design: ROI & Implementation Guide

Why trustworthy AI design is a strategic imperative, not just an ethical choice. Learn how to build the business case with proven ROI frameworks, addressing the 70% of AI initiatives that fail due to poor user adoption and trust issues.

Designing Friction in AI Systems: UX Patterns for Better Experiences

A framework for strategically incorporating deliberate friction in AI systems. Learn the Four Types of Meaningful Friction and why the trust paradox (66% use AI but only 46% trust it) demands intentional pauses.

12 Months Teaching AI Adoption: Lessons on Business Risk and Design Talent

Lessons from building AI competencies within design teams. Features the Three-Stage AI Integration Framework (Skills → Tools → Trust) and three fundamental elements for success.

AI's Impact on Design

AI as a new creative medium for designers, not a replacement. Emphasizes that design value lies in human judgment and lived experience—qualities AI cannot replicate, as shown when AI misses essential human considerations.

The Goldilocks Formula: Privacy Preserving Prompt Writing

Balancing AI utility with privacy protection using the Two-Step Abstraction Method. Learn the three information-sharing zones and a 5-step privacy check for protecting proprietary information while getting useful AI outputs.

5 Critical Moments That Make or Break Trust in AI Design

How trust forms and breaks across five critical interaction moments in human-AI relationships. Learn five actionable strategies for mapping trust journeys, auditing signals, and designing recovery patterns.

Short Runway for Action on Ethical AI

Organizations have only 6-12 months to establish ethical safeguards before biases become permanently embedded. Learn the STOP Framework—implementable within 3 months—for Stakeholder mapping, Transparency, Outcome fairness, and Pathways for appeal.

A Trustworthy AI Assessment of DeepSeek

Ethical assessment of DeepSeek's breakthrough cost-efficiency against human-centered AI principles. Despite R1's innovative "thinking process" transparency, scores low on privacy (1/10), security (2/10), and fairness (1-2/10).

Major Companies Removing AI Ethical Guardrails

Systematic dismantling of AI safety protections by major tech companies and ethical alternatives. Documents OpenAI's military permissions, Meta's reduced moderation, and X's mandatory data rights—contrasted with Anthropic and Mistral's responsible approach.

5 AI Predictions from Hollywood That Came True in 2025

Hollywood's fictional AI scenarios manifesting in reality: emotional AI dependency (Her), predictive policing (Minority Report), and workplace surveillance (1984). Features EU AI Act response with fines up to €35M.

AI Design Leadership: 2nd Wave of AI is Already Here

Autonomous AI agents require a "director's mindset" for effective collaboration. Features assessment of Salesforce AgentForce (79/100) and five principles for leading AI agents: define purpose, establish boundaries, enable autonomy, provide guidance, take responsibility.

4 New AI Work Habits – For Healthy Balanced Use

Personal journey of integrating AI tools and developing healthy habits to prevent cognitive overload. Features the 24-Hour Rule, Pen and Paper Revival, and AI Time Boundaries—especially valuable for neurodivergent professionals.

My Journey From Design Leader to Founder of AI Flywheel

Riley Coleman's origin story: from redundancy to founding AI Flywheel after discovering critical gaps in responsible AI education. Features research findings from 130 professional interviews revealing 79% stuck in experimental phases.

Strategies for Designing Transparent AI

Practical strategies for building AI systems that are powerful yet understandable. Features six transparency strategies including progressive disclosure, confidence indicators, and explainable AI techniques like LIME and SHAP.

Why AI Ethics is Personal – Not Philosophical

AI ethics as a practical, immediate concern affecting employment, creditworthiness, and security decisions—not abstract philosophy. Features seven ethical pillars and seven actions for "Team Human."

10 Reasons I Am So Conflicted About AI

A balanced exploration of AI's dual nature—transformative opportunities versus serious societal risks. Features five positive and five concerning impacts from a design leader's perspective.

10 Mental Models for Effective AI Use

Mental frameworks for individuals and organizations to thrive in AI-enhanced workplaces while maintaining human agency. Features the most powerful question for continuous learning with AI.

The One Thing AI Can't Fake (And Why Hiring Managers at Google & Anthropic Are Testing For It)

State of AI in Design 2025

AI for UXR – why it’s more vital than ever

Human-Centred Trustworthy AI assessment of Miro’s AI

Human-Centred AI means knowing when to use AI is just as important as when NOT to use AI.

Effective Human Oversight of AI Isn’t As Straight Forward As You Think

US govt AI legislation Spells the End of Global AI Cooperation

3 Game Changers to using AI in your next Design kickoff While Protecting Privacy

AI Design Practice Transformation : How IBM Designers Adapted to AI Workflows

The Future of Human + AI Collaborative Experiences: Trust Building Design

Webinar : Design AI users actually TRUST.

Your Team’s AI Adoption Is Missing An Ingredient