As we develop new products with AI built into them, the capabilities and uniqueness of each experience expands dramatically. Given that, how should our research methods change to adapt to this new technological shift?

At Instagram, Sheana is a researcher who's done extensive research on Meta's new AI experiences, and joins us to share some of the new and innovative methods their team has designed to get at the heart of how to make great AI features.

AI has been around for a lot longer than you think - it just hasn't be advancing quite as quickly in the past as it has recently.

As a UXR, what do you have to do with the history of AI development? As it turns out, it's probably more than you think. Ricardo joins us to explain.

As UX researchers, we're often doing work on new features. New additions to the product, new products for new users... new, new, new, and add, add, add.

But, what if we could make our products better by taking things away? That'd be a novel idea. Here to explore that idea with you, is Emily.

When dealing with individuals from marginalized or disadvantaged communities, it's important to be extra cautious with how you recruit, look, and behave. Not just for the benefit of the participant, but also to make sure you limit the bias you introduce into your research.

If you're not from a low-income community yourself, understanding the right way to interact with low-income folks might feel a bit foreign. Luckily, Daniela is here to share her advice for doing research with low-income communities.

More than ever before, humans are going to be interacting with robots and AIs in a human-like way. As researchers, now is the time to start thinking about how it feels to interact with these machines.

Lauren leads research at iRobot, where she thinks a lot about how humans interact with machines. Join her as she explores how to research the personalities of machines in automated experiences.

One of the greatest levers for impact within a company is making improvements to monetization. Updating pricing, repackaging the product, etc. But, where does research fit in to this conversation?

In this talk, join Jordan as she shares her learnings from her time doing monetization research at Adobe.

AI is going to change the research game, there's no doubt about that. The questions we have on the forefront are now: how will research change, and where will our careers end up?

Savina is a UXR at Meta working directly with AI engineers, and she's here to tell you what to expect from new AI tooling and how research will change in the coming years.

For UX researchers, our work can be an emotional sink. That makes career planning extra hard, when you're constantly worrying about relationships with managers, stakeholders, and the customers you work with.

Heather has dealt with this first-hand. Today, she's here to help you reflect and reorient towards building a values-aligned career in research.

There has never been more choice for researchers when it comes to tooling than there is today. Tools are more powerful, convenient, and cost-effective than ever before.

But, that leads us to some important questions: are we too dependent on tools, and could we do our work without them? In this talk, Josh is here to ask the question, do we have too many tools?

Often, when it comes to executive stakeholder relationships, we feel like we're speaking a different language. And most of the time, we are.

Executives love to talk numbers. But how do we do that, when our qualitative work has little that's quantitatively measured? Hannah from AWS is here to unpack how to use metadata from your qualitative research to speak the language of executives.