How to Study Meaning at Scale: AI and Big Data Ethnography, Microcultures and the Future of Innovation w/ Ujwal Arkalgud
Artificial Intelligence. Natural Language Processing. Machine Learning. Big Data. If you've studied Anthropology at all, you'll likely notice these terms don't often get use, unless you happen to be studying one of these areas, like doing an ethnography on artificial intelligence. Yet if these tools are used everyday across millions of applications and software lines of code to make our world run, how might they help us understand ourselves better? Big data often gets used to understand patterns people's behavior and thinking at a high level, and it is common to see people split into segments from this data.
So in the world of market and consumer research you may know that people are commonly categorized into segments or generations - you've likely seen people written about as Millennial or Baby Boomers (OK, Boomer). But what limitations to understanding people are present when putting them into segments and generations and only seeing them from a high level? That's often where ethnography comes in, and where anthropologists like to live with and get to know people on their terms. But there's a huge stretch between massive Big Data sets and individual ethnography, right?
What if there were a way to do ethnography with big data? That is, what if there were a way to be able to understand the nuances of cultural meaning people assign to things from big data sets? What this entails is, in essence quantifying ethnography. And turns out, the key has to do with focusing on meaning. That and some computer science wizardry.
I'm excited today to have on the show one of the pioneers in this field, Ujwal Arkalgud, CEO, cultural anthropologist, and co-founder of Motivbase, a global tech research firm that has cracked the cultural code and developed software and research tools that bring together the analytical power of anthropology and the wide reach of big data.
We’ll dig into
- the concept of micro cultures, which are are a set of meanings that make up a market space,
- the need to study of meaning and behavior in business, why don’t companies think about meaning as a primary mover?
- why traditional market research doesn’t effectively get at meaning,
- how the internet has changed the way we make culture and meaning and that betting on cultural homogenization is a trap
Checkout Movitbase here
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