The Quirk’s Event – New York 2026
Booth #803 • July 29-30 • New York, NY
Quirk’s Media will hold its Quirk’s New York Event on July 29-30, 2026, in New York City.
AmeriSpeak® is helping organizations navigate one of today’s biggest research challenges: generating trustworthy insights in an era of AI-driven research, growing survey fraud, and increasing concerns about respondent authenticity. Built on a probability-based foundation, AmeriSpeak combines rigorous recruitment, representative sampling, and robust quality controls to help researchers collect high-quality data from real people and make decisions with confidence.
Join AmeriSpeak at The Quirk’s Event – New York 2026. Visit booth #803 to meet with NORC and AmeriSpeak experts, learn how leading organizations are strengthening data quality, and explore approaches for reaching authentic, representative audiences. We’re also excited to share insights during our conference presentation on sampling, AI-enabled research, and the importance of reaching the right respondents to generate trustworthy results.
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NORC AmeriSpeak Panel
Representative Samples. Trusted Respondents. Stronger Decisions.
AmeriSpeak is NORC’s probability-based panel, built using rigorous recruitment methods and random sampling to reach households across the United States—including audiences that are often missed by traditional online research approaches. Researchers can conduct omnibus surveys, fully custom studies, or targeted studies among audiences defined by demographics, geography, behaviors, and more.
But reaching respondents is only part of the equation. Today’s researchers must also protect studies from fraudulent activity, professional respondents, bots, and other threats to data quality. AmeriSpeak combines its probability-based foundation with ongoing quality controls and panel management practices designed to help researchers collect insights from authentic participants and make decisions with greater confidence.
NORC Presentation at Quirk’s
Who’s Missing from Your AI Research? Richer Responses, Better Samples, Smarter Decisions
- Presenter: Alex Chew, Director, Amplify AAPI, AmeriSpeak
- Presenter: Alex Anwyl-Irvine, Senior Research Scientist, Surgo Health
- Thursday, July 30, 2026, 1:30-2:00 pm ET
- Room 4
This session explores a practical question facing many insight teams as AI-driven quantitative and qualitative tools become more common: how do you make sure richer feedback also leads to better, more trustworthy insight? The core argument is not simply that conversational AI can generate more text or more nuance. It is that the value of AI-based interviewing depends heavily on who is being reached, how comfortable they are engaging with AI, and whether the sample reflects the broader audience researchers actually need to understand.
Using a real-world case study from Surgo Health and NORC as one proof point, the presentation will show how an AI interview approach surfaced 4.1 times more topics per person than a single free-text response and uncovered deeper structure beneath broad survey concepts such as communication and trust. The session will also highlight emerging differences across both demographic and psychobehavioral segments, including variation in trust in health care, trust in AI and willingness to engage with AI moderators.
Framed from the NORC perspective, this becomes a broader lesson about what it means to study AI interviewing with a high-quality panel that includes people who may or may not already be familiar with AI, including harder-to-reach groups who are often underrepresented in standard online samples. It also underscores the growing importance of recruitment approaches rooted in probability-based samples, which can help ensure qualitative conversations are grounded in real, verified people rather than only those easiest to reach.
Attendees will leave with a practical framework for evaluating AI-enabled research not just by speed or volume, but by insight quality, representativeness and the ability to capture perspectives that might otherwise be missed.
Key takeaways:
- Evaluate AI research based on insight quality, not just volume. Attendees will learn a practical framework for assessing AI interviewing beyond speed and word count. The session shows how conversational AI can surface significantly more topics and uncover deeper structure within complex concepts like trust, enabling more actionable, decision-ready insights grounded in real, verified participant voices.
- Pair AI interviewing with high-quality, representative samples. The presentation demonstrates how combining AI tools with high-quality panels, including probability-based samples, improves representativeness and trustworthiness. Attendees will learn why it matters to engage real, known populations rather than only opt-in respondents, and how differences in trust in health care, trust in AI and comfort with AI moderators shape participation, along with ways to include harder-to-reach and less-AI-comfortable audiences.
- Use AI to uncover hidden drivers and missed segments. Attendees will gain a repeatable approach for going beyond predefined survey questions. The case study illustrates how AI interviewing reveals unprompted themes, clearer prioritization of drivers and meaningful differences in sentiment that traditional methods often miss, especially when drawing from samples designed to reflect the full population, helping teams identify insights that lead to better decisions.
View the full online program.
