The Human Touch(point): Recommendations for Thoughtful AI Feature Design

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Sierra Shell

Abstract

This article examines the evolving responsibilities of designers in an era of explosive AI growth. AI is a horizontal technology affecting nearly all industries, and designers must position themselves as stewards of the “human in the loop” to balance technological capabilities with human needs. Three core principles can guide ethical AI design: First, AI features should solve specific user problems rather than being implemented for novelty or marketing purposes. Second, strategic friction can serve as a beneficial design element when deployed at consequential decision points, encouraging users to engage thoughtfully with AI-generated content. Third, robust user feedback mechanisms should be prioritized to ensure continuous improvement based on real-world usage. Generative AI should facilitate — never replace — human expertise to avoid the centralization of ideas and displacement of creativity. Drawing from industry examples, the article demonstrates that successful human-AI collaboration depends not on technological sophistication alone, but on thoughtful design that empowers users as active participants rather than passive consumers of AI outputs. Eight recommendations are provided to ensure that the three core principles discussed are incorporated into a product’s design.

Article Details

Section

Dispatches from Industry

Author Biography

Sierra Shell, SAS Institute (United States)

Sierra Shell is a technologist and UX designer with experience in trustworthy AI design and governance, ethical design strategy, and data visualization design. She has nearly a decade of experience creating complex enterprise products, and currently works with a small team focused on expanding SAS’s already robust trustworthy AI capabilities. She received her Master’s of Digital Technology Policy from University College London, where she partnered with the British Standards Institution conducting and publishing research on the future of responsible AI standards. Her work required that she develop a deep understanding of common hurdles and disincentives organizations face in implementing AI governance strategies. This has led to a special empathy for organizations and users adopting AI tools and models. As a result, she has a drive to design streamlined solutions that facilitate effective governance and address business concerns intuitively and responsibly.

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