Data & Society

lil defs, look for a deeper dive on Notion and BS slides

Data

Data is/are the material produced by abstracting the world into categories, measures and other representational forms which constitute the building blocks from which information and knowledge are create (Kitchin, 2014)

Why is “raw” data an oxymoron? (book title by Gitleman & Jackson (2013)

It always carries a meaning. No data is an objective, independent element.

Datafication

The transformation of human life into data through processes of quantification and the generation of different kinds of value from data (Mejias & Couldry, 2019)

How can data be created?

It can be direct, indirect or inferred.

What is direct data creation?

the process of generating original data at the primary source. e.g. surveys

What is indirect data creation?

the process of gathering or generating information through secondary means. e.g. using your credit card (time, location, account details, etc.)

What is inferred data creation?

“the process of using computer analytics to predict x y z about someone based on their everyday online actions.” shows hints, patterns. e.g. schedule, tends to buy coffee with their credit card every two days, so really likes coffee. which type? oat milk? lactose intolerant?

What are the potential benefits to society of Datafication?

Census data, Smart cities, Mapping climate change, Health

Black Box

We’re fed an algorithmic thing, but not another. Still obscure about how tf that’s done. They know more about us than we know about them. (Ex Amazon, UCD, Uni in the US)

What are some critical considerations?

Data is unnatural, humans are behind its abstraction. Obscure. Asymmetry of knowledge and power. Discrimination. (more about it on notion)

What is NOT datafied?

Digital inequality when you compare different regions, omission / selection (more on Notion)

Where globally is the most data coming from

the US

What is Classification? + types

Process of organizing data into categories that make it is easy to retrieve, sort and store for future use.

Context – location, demographic

User based - Personal Identification (ex Faye, shows how it can be annoying, or disease)

Race, Gender, Class.

Personality (Political positions, social opinions)