How AI transforms research: A perspective by Dr Asma A Qureshi

generative AI ux research sounds like it’s trying to make AI less alien and more usable. because yeah, raw AI models throwing out random crap all day don’t cut it. usability, trust, predictability–this stuff still sucks if you’re not testing with real humans. prompt flow analysis is basically watching people try to talk AI, fail, retry, and maybe get it right. it’s all about bridging that weird gap between machine math and messy human brains. cool tech, sure… but also a reminder that AI ain’t magic yet. it’s human in the loop, or else it’s just noise. sigh.

Yeah, AI’s smart but it’s still a black box to most users. This piece dives deep into the grunt work of making AI feel less like a cryptic oracle and more like something you can actually use without flipping a table. Usability testing, behavioral observation, prompt flow analysis–all fancy ways to say “watching humans struggle and adapt to AI quirks.” Cool, but honestly, it’s about trust and expectations, which AI keeps crashing on. Designers out there better listen up; designing for “probabilistic” things that change every time is a whole different beast. Worth a skim if you build the stuff or explain it to confused users daily.

- AI is transforming UX research, offering speed, scale, and new pattern recognition — but human judgment remains irreplaceable. - Insight Generators automate data processing and pattern detection, while Collaborators support planning and creativity. - Caution: AI can amplify biases, hallucinate insights, and flatten human diversity if left unchecked. - Synthetic users and auto-summaries inspire, but cannot replace the empathic understanding real users provide. - Privacy and ethics are critical — consent, data minimization, and transparency must be prioritized in every project. - The most pragmatic approach: let AI handle repetitive tasks but keep humans in charge of decision-making, validation, and storytelling. - UX researchers need new skills: AI literacy, data storytelling, operations thinking, and coaching cross-functional teams. - Building robust research ops and strong tooling governance helps ensure ethical AI adoption. - Success is measured by business impact, not just research outputs. - Bottom line: In the AI era, UX thrives when AI is your junior teammate — not your decision-maker. #UXResearch #AI #HumanCentricDesign #EthicsInAI #ProductStrategy[1] https://lnkd.in/dfTaniJz

- AI is transforming UX research, offering speed, scale, and new pattern recognition — but human judgment remains irreplaceable. - Insight Generators automate data processing and pattern detection, while Collaborators support planning and creativity. - Caution: AI can amplify biases, hallucinate insights, and flatten human diversity if left unchecked. - Synthetic users and auto-summaries inspire, but cannot replace the empathic understanding real users provide. - Privacy and ethics are critical — consent, data minimization, and transparency must be prioritized in every project. - The most pragmatic approach: let AI handle repetitive tasks but keep humans in charge of decision-making, validation, and storytelling. - UX researchers need new skills: AI literacy, data storytelling, operations thinking, and coaching cross-functional teams. - Building robust research ops and strong tooling governance helps ensure ethical AI adoption. - Success is measured by business impact, not just research outputs. - Bottom line: In the AI era, UX thrives when AI is your junior teammate — not your decision-maker. #UXResearch #AI #HumanCentricDesign #EthicsInAI #ProductStrategy[1] https://lnkd.in/edPvgXBH

Alright, so generative AI UX research. Basically, it's the messy reality check for AI hype – watching real humans struggle or scream at chatbots and content generators. It’s not just tech specs or fancy algorithms. They sit there and track how people stumble over prompts, second-guess the AI's 'logic,' and adapt – or bail hard. UX folks are trying to turn AI’s BS unpredictability into something user-friendly. Trust is the real game here, not just clever code. So yeah, it’s the necessary grind if you want AI that doesn’t just spit out nonsense that breaks everything.

Check out this recent article I wrote, published by the ResearchOps Community, on two case studies about leveraging AI in the user research process. Writing this made me realize that more needs to be written on the topic, with greater specificity, not just generalizations. https://lnkd.in/gbBGj2nd

The claim that the user interface (UI) as we know it is numbered may sound like thunder in a clear sky to many, but to those who have followed the trajectory of technology, it is merely the next storm on the horizon. The future of the human experience with digital products necessarily depends on the relationship we will have with information — whether predicted or post-dicted. The use of Artificial Intelligence (AI) and, soon, quantum computing, will dictate the evolution of the digital environment we live in and, consequently, the evolution of human beings themselves over the coming decades — or perhaps the next century. Technology is not an end in itself, but a means that continually redefines our perception and interaction with the world. And now, we stand at the threshold of the deepest of these redefinitions. #UI #uidesign #AI https://lnkd.in/gYwFJs-w

Ah great, more AI hype pretending to care about humans. But ok, gotta admit: this takes the usual black-box AI freakout and flips it where it belongs–on real people struggling to make sense of these unpredictable chatbots and "copilots." They actually dive into why users get spooked, confused, or cagey, instead of selling buzzwords. Usability testing meets behavioral watching meets prompt spelunking. Good luck making those mental models line up with what the AI actually does though. Trust? Yeah right. Still, if you're stuck shipping magic that only sort-of works, this is the kind of grind worth reading about.

“We’ve never had so much intelligence available — and never designed so shallowly.” In 'UX and the aesthetics of AI', Danilo Amorin touches on so many points I've been feeling strongly about over the past year. AI is changing how we interact with technology, but most AI interfaces still look the same: a text box, a cursor, and a promise of magic. Danilo Amorim’s talks about the homogenization of intelligent interfaces: 👉 The “chat” paradigm has become the default, but it limits what AI can really do. 👉 We’ve mistaken simplicity for creativity, leading to “the aesthetics of indifference.” 👉 True AI design should be contextual, multimodal, and collaborative, not just conversational. 👉 Good design makes intelligence visible, interpretable, and human. 👉 The future of AI UX isn’t about prompts, it’s about partnership. Read the full article: https://lnkd.in/grHjEkJG

The claim that the user interface (UI) as we know it is numbered may sound like thunder in a clear sky to many, but to those who have followed the trajectory of technology, it is merely the next storm on the horizon. The future of the human experience with digital products necessarily depends on the relationship we will have with information — whether predicted or post-dicted. The use of Artificial Intelligence (AI) and, soon, quantum computing, will dictate the evolution of the digital environment we live in and, consequently, the evolution of human beings themselves over the coming decades — or perhaps the next century. Technology is not an end in itself, but a means that continually redefines our perception and interaction with the world. And now, we stand at the threshold of the deepest of these redefinitions. #UI #uidesign https://lnkd.in/gYwFJs-w