Presented By O'Reilly and Cloudera
Make Data Work
31 May–1 June 2016: Training
1 June–3 June 2016: Conference
London, UK

Objectivity is a myth: Your data is not objective, and neither are you

Rachel Shadoan (Akashic Labs)
10:00–10:30 Wednesday, 1/06/2016
Data 101
Location: Capital Suite 15 Level: Non-technical
Average rating: ****.
(4.00, 2 ratings)

Prerequisite knowledge

Attendees should be familiar with structured data.

Description

We often treat data as an impartial representation of reality—an unbiased delivery mechanism for “ground truth.” Data collection and analysis systems, however, are designed by people: our knowledge, experience, and beliefs influence the design decisions we make and thus the data we collect. The layers upon layers of choices and assumptions we make in collection and analysis render data subjective, subtly imbuing it with a perspective of its own.

It’s straightforward to identify the particularly grievous examples of data’s subjectivity. To give just one example, the only federally collected data on homicides by police officers in the US, the FBI’s Supplementary Homicide Report, includes only self-reported justifiable homicides. But more subtle bias is present in apparently innocuous assumptions—for instance, that all usage of an Android phone is by the same user.

Given, then, data’s lack of objectivity, how do we use data responsibly to reason about the world we live in?

Rachel Shadoan explores how to adapt our processes to account for data’s lack of objectivity.

Topics include:

  • Why you and your data are not objective
  • Techniques for understanding the perspective of data you’ve already collected
  • Strategies for collecting data with a broader perspective
  • Methods to illuminate the blind spots in your data’s perspective
Photo of Rachel Shadoan

Rachel Shadoan

Akashic Labs

Rachel Shadoan is the cofounder and CEO of Akashic Labs, a Portland-based research and development consultancy, where she specializes in combining research methodologies to provide rich and accurate answers to technology’s pressing questions. Questions about people are her favorite kinds of questions to answer. Prior to founding Akashic Labs, Rachel worked with Intel exploring both how people use their phones in cars and how the ability to convert to a tablet impacts laptop use. She has also collaborated with Stanford digital humanities scholars and Oxford data archivists to develop a visual graph query language to allow researchers to form queries on complex multidimensional data. Originally from Oklahoma, Rachel holds an MS in computer science from the University of Oklahoma, as well as an MS in design ethnography from the University of Dundee in Scotland. As is thematically appropriate for her adopted home of Portland, she likes cruciferous vegetables (especially kale) and occasionally brews beer.