EPIC 2013 kicked off on a sunny but brisk September morning in Mayfair, possibly the only borough in London where you’re guaranteed to feel underdressed no matter what you wear. Here’s a summary of the first speakers and their talks.
Tricia Wang – Keynote
Tricia Wang’s keynote address argued of the dangers of relying on data, without the the context that ethnography provides. We’ve constantly mistaken data for knowledge and when businesses make this mistake, they end up like Kodak, relying on the data without the wider human context. And this understanding of humans is a creative skills, it should be creative work and not based on measurements.
Tricia also spoke about the challenge of making Ethnography visible. Much of the work ethnographers do doesn’t make the public eye because much of it’s output is invisible, it’s what doesn’t happen to a service or product. Ethnographers need to get better at telling stories.
Finally, Trica argues that Big Data is great for generating questions, but Thick Data (ethnography and qual research), is the only way to get answers to those questions.
Theodore Pollari & Kim Erqin, IIT Institute of Design – Small Packages for Big (qualitative) Data
Kim presented on the her research paper which identified the issue researchers have when faced with large data sets. Effectivly, data collection tools have developed faster than data processing tools, so we now have a situation where we have enormous data sets and few ways to deal with them. Her teams idea is for researchers to develop ‘Small Packages” or toolkits for researchers to use to help process this data.
Erin Taylor, Institute for Social Sciences & Heather Horst, Royal Melbourne Institute of Technology – From street to satellite: meixing methods to understand mobiel money users
Erin’s research project showed how mobile money services were changing from the expected use case. Mobile money covers 192 companies across the world and uses local agents (hairdresser, shops etc) instead of traditional bank institutions.. In Haiti after the 2010 earthquake, it was seen as a development tool for NGOs to give cash grants to help the community. At the time, it was the only way to get money distributed quite help the quick adoption of mobile money. Their research programme unearthed some key issues. One of these key insights was trust for the users. Previous to the earthquake, the populous trusted mobile phone operators considerably more than the Haitian government (68% vs 8%), particularly the main operator Digi-Cell. This helped the swift uptake.
Another insight what the growth of ‘me-to-me’ transactions. In a city which isn’t very safe, people would pay money to the mobile money agent, travel across the city and then withdraw the funds from another agent.
Abby Margolis, Claro Partners – Five misconceptions about Personal Data: Why we need a people-centred Approach to “Big” data
Abby asked how ethnography can help us understand big data, and in particular, what can ethnography offer to help us understand how people use Big Data in their everyday lives. Essentially, how can we give the user’s data back to them to use in interesting ways. Some products which do this are well known (Nest thermostats for instance).
Abby’s top 5 misconceptions about Personal Data:
- Big Data is the new oil: Personal data is only relevant to the initial user. It’s not a universal commodity like oil.
- Personal data is all about privacy: People don’t necessarily want to lock data away, they want to know what their data can do for them.
- The value of personal data is in it’s sale: We’re used to big organisations making money from the selling of data (i.e. Google’s advertising). Valuable experiences and services can be created which use personal data to benefit the user.
- Personal data is for data scientists: Personal data empowers people, it’s accessible and doesn’t have to be complicated if the tools are available. User’s aren’t just generating the data, they’re using and benefiting from it.
And how can ethnography help this process?:
John Curran, JC Innovation & Strategy – Big Data or ‘Big ethnographic data’? Positioning big data within the ethnographic space.
John’s talk focused on how s big data is finding a place within society and where this might take us. For instance, Tesco tried to understand the purchase patterns of new parents. They used big data to try to understand these purchase behaviours and amusingly discovered that the biggest purchased with nappies was beer. John used this example to demonstrate how sense must be made of this insight. Ethnographers are talented at understanding why parents purchased these products together, but ‘Big Data’ wouldn’t.
That’s all for this morning!
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