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Three Years Out: Perspectives on the Near-Term Future of User Research

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Three Years Out: Perspectives on the Near-Term Future of User Research

Friday, March 15, 2024 • Advancing Research Community
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Three Years Out: Perspectives on the Near-Term Future of User Research
Speakers: Lija Hogan , Milan Mijatovic , Sam Proulx and Louis Rosenfeld
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Summary

We know how things are at the start of 2024, and the long term future? That's anyone's guess. But what might the not-so-distant future look like for User Research? That's a horizon that's just around the corner—and one that you start planning for now. Join us for a free discussion with some UX research thought leaders who have some opinions you'll want to hear about the near future of our profession—and bring your own! We'll be hearing from Sam Proulx of Fable, Lija Hogan of UserTesting and Milan Mijatovic; moderated by Lou Rosenfeld. This Talk is Sponsored by Fable, an #AR2024 Virtual Sponsor.  

Key Insights

  • •

    AI-driven user experiences are becoming non-deterministic, meaning users will receive different outcomes even for the same actions.

  • •

    UX research must shift focus from average user flows to designing for edge cases because now everyone experiences unique, evolving interfaces.

  • •

    The traditional 100-page research report is becoming obsolete due to faster cycles and larger, mixed-method datasets.

  • •

    Mixed methods research combining qualitative and quantitative data at scale will dominate the near future of UX research.

  • •

    AI tools will increasingly assist researchers by automating base-level data synthesis but human interpretation remains crucial.

  • •

    UX researchers need to become more data fluent, including knowledge of product analytics, surveys, and coding languages like Python or R.

  • •

    Understanding assistive technologies and their innovations provides insights into the future of mainstream user interfaces.

  • •

    Ethics and privacy in data collection are critical, especially when researching vulnerable or assistive technology users.

  • •

    Regulations around AI, accessibility, and digital markets are rapidly increasing and impacting UX design and research.

  • •

    New user interface paradigms like chatbots and AR present unique design challenges around user discoverability and interaction.

  • •

    Large-scale in-product behavioral research requires new operational pipelines to properly represent and study edge cases.

  • •

    Researchers must resist building tools before understanding their research needs; tool development should be problem-driven.

  • •

    UX professionals will increasingly wear multiple hats due to shrinking teams and budgets in tech environments.

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    Collaboration between researchers, engineers, product teams, and regulatory bodies is more essential than ever.

  • •

    The future of UX research includes focusing on the human element — empathic connection amid technological complexity.

  • •

    Data alone isn’t enough — quality and relevance of data trump quantity in driving meaningful insights.

Notable Quotes

"If you press the exact same button today and tomorrow you get two different results, that’s non-deterministic UX."

"Now everyone’s an edge case, so research needs to focus on those edge cases, not just the average user."

"The era of 100-page reports is ending because we simply can’t produce them fast enough at scale."

"Mixed methods researchers will need to trust AI for base-level synthesis but still bring human meaning making."

"UX researchers should learn Python or R and how to leverage AI APIs to process unstructured data."

"Understanding how assistive technology evolves is crucial because it foretells the future of interface design."

"We need to become data ethicists and curators, not just data vacuum cleaners, to prioritize quality data."

"Regulations are design problems, not just technical ones, influencing how we create products and experiences."

"Future UX includes designing for user discovery in conversational and augmented interfaces, not just clicks."

"Being fluent in multiple data languages and understanding behavioral and attitudinal data will be essential."

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