This video is featured in the AI and UX playlist.
Summary
What we design is changing; therefore, how we design is also changing. Design innovation is being affected by emerging AI technologies. In this talk, I will set the context for the role of design in creating purposeful and pragmatic technology, both historically and today. I will talk about some of the problems with AI innovation and I will show some examples from our research showing the impact of design in creating, developing, and deploying AI systems, with the goal of creating better social systems, better economic relations, and a better world in which to live.
Key Insights
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AI is transforming not only products but entire service ecologies, blending tangible and intangible elements via datafication.
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A large majority of AI products fail due to poor model performance, lack of clear service value, low desirability, or ethical risks.
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Designers often join AI product development too late, after data and models are already chosen, limiting innovation potential.
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New design methods are needed that start with AI data sets or capabilities instead of user-centered approaches alone.
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Algorithmic management in hospitality reduces worker autonomy and risks poor task assignment without contextual understanding.
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Involving workers in co-design processes can increase their sense of agency, improve transparency, and lead to better AI tool adoption.
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AI performance does not need to be perfect; moderately accurate AI applied wisely can create significant user value.
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Privacy and ethical risk management in AI development is often unassigned but should be integral and early in product design.
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There is a taxonomy of AI capabilities that can serve as design patterns to help translate technical possibilities into user interactions.
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The hospitality industry’s complexity—multiple management entities and social-emotional labor—makes AI implementation especially challenging and in need of holistic design thinking.
Notable Quotes
"Data has been described as the new oil, and AI has been likened to electricity, poised to transform everything."
"We should think of AI as our ancestor encountered fire: managed well it’s a force for good, deployed recklessly it will burn us."
"You would never implement an algorithm on a doctor without consulting them, yet in hospitality, workers face algorithmic managers daily."
"AI products typically fail because teams can't achieve model performance or the data is poor or unavailable."
"Sophisticated AI isn’t always needed; sometimes what’s really needed is a better website, not a fancy chatbot."
"Moderately good AI can add real value, like voicemail transcription that doesn't have to be perfect to be useful."
"Technology is often blamed, but many issues come from uneven training, misunderstandings, and poor configurations."
"Designers are becoming managers, ethicists, and advocates as the complexity of AI products grows."
"Empowering workers in AI design can help them develop new skills and increase satisfaction."
"AI ethics teams at Facebook and small companies will look very different; there’s no one size fits all approach."
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