Using AI To Quantify & Size META Trends

Earlier this year Sarah DaVanzo and I published the fifth annual 2022 META Trend analysis, a distillation of 40+ industry trend reports to ultimately identify the most frequently reported (i.e. noteworthy) trends for the year. Fourteen (meta) trends were identified to represent what the entire trends industry was collectively forecasting.

During this time we also announced that for the first year, we’d quantify each of these META Trends to more precisely size and evaluate their cultural influence. It’s been a moment, but we finally crunched the data...

To get here though, we first had to answer a series of very thorny questions: How do we define the criteria or “borders” of each META Trend, which sources of data should be leveraged to score each, should we study these trends’ influence within a U.S. or global data set, how do we even collect and analyze this data at scale, and how do we complete this exercise without adding any human interference, tipping the scales of objectivity?

Once answering those could we then shine light on the larger questions at hand:

* By leveraging cultural data, would AI rank the META Trends differently than how the humans did?

* Left on its own, could AI identify similar or different (perhaps missing, overlooked) META Trends?

* And conclusively, what are the best tasks and roles for humans versus AI in order to develop a successfully orchestrated cultural intelligence system?

While asking ourselves all of these questions, we formed a partnership with the team at NWO.ai. The NWO.ai platform, which was amongst the finalists for LVMH's Innovation award, and an Industry Cloud partner of SAP, was formed in 2020 to identify consumer signals before they become exponential. Its AI algorithms learned over the last 2.5 years, and now boasts statistical trend prediction accuracy. They effectively quantify culture. With Sarah’s previous experience collaborating with them earlier this year, we determined their platform would be the perfect tool for our quantitative META Trend analysis.

Experiment 01.2022 META Trend Scoring & Ranking_ Humans vs. AI

As for our first question: If AI was to collect cultural data against each of the META Trends and then score their importance to rank each of them, would the AI ranking match or produce different results from the original human rank?

Answer: Different.

As a reminder, our “human ranking” was completed by Sarah and myself manually counting the frequency of similar trend mentions throughout the 40+