Shanon Adams

Topics Shanon shaped

AI & technology, Researcher craft & identity, Industry, profession & meta, Insights function & business, Methods, methodology & rigor, Consumer behavior & culture

What Shanon said — indexed claims

• The data quality problem resembles the antivirus industry's problem: the work is never done because new threats and bad actors emerge continuously, and AI is now both the attack vector and a source of defenses; the same technology that erodes data quality can be used to spot and improve it. — Ep. 49 · 33:10 · cl-50th-006
• Counterintuitively, LLMs excel at querying unstructured data (PDFs, transcripts, open ends) but struggle with structured data; properly querying structured data on the fly is a tremendously harder technical challenge than reading verbatim, and remains the holy grail for the next generation of systems. — Ep. 49 · 28:47 · cl-50th-004
• AI is changing insights work in two distinct categories: handling chores (volume tasks like transcript reading and open-end coding that LLMs natively do well), and enabling work that was previously impossible without a team of specialists. — Ep. 49 · 06:54 · cl-50th-002
• Researchers should apply the same empathy to survey respondents that they apply to the consumers they are studying — translating questions into the respondent's language and generation, and remembering that some bad actors are economically desperate humans rather than fraud-bots. — Ep. 49 · 40:12 · cl-50th-007
• Insights work can no longer rely on hindsight or real-time alone; foresight has become the center of gravity, and every insights professional must now operate as a futurist — even though the accelerating pace of change makes 5- and 10-year planning nearly impossible. — Ep. 49 · 46:18 · cl-50th-009
• Job transformation driven by AI is not a generational or ten-year event — it is near-term and will require current workers to embrace entirely different roles and ways of working within a compressed timeframe. — Ep. 49 · 55:05 · cl-50th-011

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