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How can universities overcome their unique challenges to create amazing digital experiences in an AI-driven world?
In this episode of Edtech Connect, host Jeff Dillon sits down with Nick Cawthon, a seasoned UX strategist with over two decades of experience working with giants like Adobe and Visa, and a professor at the California College of the Arts. Nick pulls from his rich background in the first dot-com boom to draw powerful parallels between then and now, arguing that we are in a similar era of transformative potential with AI. He offers a candid look at why higher ed struggles with UX—citing complexity, siloed departments, and slow-moving governance—and provides a fresh perspective on how to navigate it.
They dive into the ethical integration of AI, the irreplaceable value of human creativity, and why mastering the humble spreadsheet is more important than ever. For any leader, educator, or designer looking to build more intuitive and impactful digital products, this conversation is packed with practical wisdom and strategic insight.
Key Takeaways
- Design Thinking is a Personal Productivity Tool: The principles of design thinking are not just for work. They can be applied to manage personal life, transforming scattered thoughts into a tangible, actionable plan.
- Higher Ed's UX Problem is a Governance Problem: The struggle to create great digital experiences isn't due to a lack of ideas, but often because of organizational complexity, siloed departments, and a lack of trust that prevents unbiased user research and streamlined decision-making.
- AI Resets the Starting Line for Everyone: Just as the internet and tools like QuarkXPress once leveled the playing field, AI is doing the same today. It’s not about replacing skills but augmenting them, allowing those who embrace it to move from idea to deployed application at an unprecedented speed.
- Embrace AI with Amnesty and Transparency in Education: Instead of treating AI as "cheating," educators should grant "amnesty" and encourage its use, with the requirement that students document their process and prompts. This fosters mentorship and transparency, turning AI into a collaborative learning tool.
- Ethical AI Considers More Than Output: Ethical integration requires looking beyond the "magic" of the output. Consider the human labor used to train models, the intellectual property sourced, the mental health of content moderators, and the environmental impact (carbon footprint) of running AI processes.
- Foundational Data Skills Are Still Critical: In an age of sleek SaaS interfaces, the fundamental skill of manipulating data in a spreadsheet (e.g., pivot tables, VLOOKUPs) is more important than ever. It teaches the crucial process of normalizing and analyzing data, which is the bedrock of any data-driven narrative or AI application.
- Prototype and Validate AI Ideas Rapidly: The speed of AI tools allows teams to prototype and test complex product ideas quickly. This enables rapid iteration and "failing fast," helping to validate usability and refine the target user profile before making significant investments.
Find Nick Cawthorn here:
https://www.linkedin.com/in/nickcawthon-ux-digital-agency-product-design-leadership/
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