1. Living in Data
- Necessity of closing the loop btw data abs people from who it comes from
- Reality that data is often collected from us but not for us— how can we turn this around, make data into two-way streets?
We are coming to an end of the epoch of rights. We have entered the epoch of responsibilities, which requires new, more socially-minded human beings and new, more participatory and place-based concepts of citizenship and democracy. — Grace Lee Boggs, The Next American Revolution (2011)
2. I Data You, You Data Me (We All Data Together)
- Data derives from Latin from “a thing having been given, a gift sent”
- Idea that data is somehow divinely generated, given by God, can be dangerous, bc overlooks how biases are perpetuated (ex. word association programs with gender and racial biases)
- We can use data to investigate a particular model of, say, language, but not language itself
-
Issue is often more about authorship, exclusion than bias
Authorship, after all, is not only what is created but also what is selected. — Teju Cole
- Proposal by Johanna Drucker: replace the term data with capta, derived from “to take” rather than “to give” → incorporates active role of collection and construction
- Alternatively, turn “data” into a verb— reveals power structures of who is the actor, who is object
3. Data’s Dark Matter
- Library of Missing Datasets → project by Mimi Onuoha to collect datasets that should exist, but don’t— ex. people excluded from public housing bc criminal record, how much Spotify pays an artist per play
- Many reasons why they don’t exist (hard to collect, not any incentive, too big or ambiguous), but often for political reasons
- Also refers to missing people within existing datasets— ex. undercounting of Native Americans in the census
4: By Canoe and Caravan
To become oriented, to find their way and fill their maps, venturers from Europe needed Native people’s knowledge of the land. Maps and names would then obscure that knowledge from its context, as Indigenous people themselves were removed from the land. — Lauret Savoy
- Writings of so many explorers = bizarre alternation between brief moments of appreciation for the naturalist attention to detail and long stretches of horror at outright racism
-
Data systems are anchored in real places, reliant on real people:
[There is] a complex structure of supply chains within supply chains, a zooming fractal of tens of thousands of suppliers, millions of kilometers if shipped materials and hundreds of thousands of workers included within the process even before the product is assembled on the line. — Kate Crawford
- Crucial questions to ask when collecting data:
- Who is it benefitting?
- How might the data put people, animals, and data at risk?
- Do the benefits of collection outweigh potential harm?
5: Drunk on Zima
- In the time it takes to load a website, massive amount of things occur: request to fill as spaces sent out with your data (via cookies) on 100+ variables; if there isn’t a match in default collection, info sent to ad exchange → real time auction to show you an ad occurs
- Use Vickrey auction model: each bidder blind to other bids, winner is the one who offers the most, but pays second-highest price → encourages “truthful bidding”
- Even when explicit biases in ad placement disallowed (ex. showing certain housing ads based on demographic), still widespread— learned implicitly by algorithms
6: Number of Grown Sheep That Were Sheared
- Precision of data in computers clashes with murky nature of reality…
- Even small minutae like what form a variable takes can have a big impact, affects what information is being captured/recorded
- Jacob Harris essay on coding status of prisoners
7: do/until
- Algorithms can magnify omissions of data into sinkholes
8: A Lossy Kind of Alchemy
- [Data viz]
9: The Rice Show
- Human brain is not great at comprehending large numbers → how can data visualization help?
- Of All the People in All the World exhibit → represents population with grains of rice— adds up to 100s of tons for world, but we still see each grain as a person (kooky comparisons)
10: Paradox Walnuts
- Displaying data in forms beyond digital: sounds of a glacier, growth of trees
11: St. Silicon’s Hospital and the Map Room
- “Public” data often still has many barriers to access
- When we say open or public data, who exactly are we referring to?
- Evaluate based on comprehensible documentation, background/context availability, ability to be used by nonprogrammer, documentation in other languages, etc.
- Think about people who are not you, beyond the computer
- Map Rooms
12: Te Mana Raraunga
- Questions of data sovereignty when the cloud is in play, for travelling citizens…
- Also has political ramifications
- Work among indigenous peoples to map, pass along, take ownership of traditional knowledge and history
- Non-Western knowledge systems often invert our classical pyramidal hierarchy of Data → Information → Knowledge → Wisdom
- Reconceptualize as a prism, with wisdom as the widest piece; perhaps with different refractive index
- Intended to sit alongside, not replace, the DIKW pyramid
13: An Internet of What
- Recent efforts to develop new web system based on what rather than where (with URLs, servers, etc.)
- Relies on hashing: reducing data of diff sizes to fixed size
- Easy to obtain, but hard to backtrack
- Very sensitive to changes to input
- Kind of guarantees that correct data arrived
- Allows for much more distributed, peer-to-peer networks/exchanges → more secure, more efficient
14: Here in Dataland
- The future of data…