Data Together's reading group is a set of conversations on themes relevant to information and ethics. Learn more and consider joining!
See blog posts of previous conversations at datatogether.org's blog. Previous semesters' syllabi are also available.
Once a month, we'll host a 1.5 hour discussion of one of our themes. Everyone should try hard to read the core reading (~30 pages), and once or twice sign up to facilitate discussion.
đź“… During session, we meet once a month at 17:30-19:00 ET on a Tuesday (Data Together Calendar)
🎯 Participation link (recorded): https://edgi-video-call-landing-page.herokuapp.com/https://zoom.us/j/847315566
Join the Data Together reading group!
What is the role of an individual in a system where we hold civic roles both in political and in digital contexts? What are the implications of one’s polity not aligning with one’s national or governmental state?
- Algorithmic Racism & Environmental Data Justice (March 17)  🎬 Recorded Call  🗒 Notes Â
- Content Moderation and Consent (April 7)  🎬 Recorded Call  🗒 Notes Â
- Data Monopolies (May 12)  🎬 Recorded Call  🗒 Notes Â
- Trust (Cryptographic and Human) (June 9)  🎬 Recorded Call  🗒 Notes Â
- Private Data & Policies (September 22)  🎬 Recorded Call  🗒 Notes Â
- Polity (November 3)  🎬 Recorded Call  🗒 Notes Â
March 17
How do choices in technology design and implementation reflect and impact broader social structures? Let's explore, starting with readings from environmental data justice and studies of algorithmic racism.
Readings:
- EDGI EDJ group, 2019: EDJ Syllabus
- Sasha Constanza-Chock, 2018: Design Justice: Towards an Intersectional Feminist Framework for Design Theory and Practice
- EDJ (Lourdes Vera, Dawn Walker, and many more, EDGI), 2018: extractive logic paper
- Mark Wilkinson, Michel Dumontier, and many more authors, 2016: FAIR principles for scientific data management and stewardship
- Research Data Alliance International Indigenous Data Sovereignty Interest Group, 2019, in The Global Indigenous Data Alliance: CARE principles for Indigenous Data Governance
- Max Liboiron, 2017: Pollution is Colonialism
- Dan Robitzsky, 2019: TikTok Secretly Hid Videos by Fat, LGBTQ, Mentally Disabled Users
- Edward Ongweso Jr, 2019: Racial Bias in AI Isn’t Getting Better and Neither Are Researchers’ Excuses
- Rebecca Heilweil, 2020: Why algorithms can be racist and sexist
April 7
This topic covers factors that impact the content that we see. How do platforms balance freedom of expression versus consent to avoid offensive content, navigate algorithmic versus human moderation and curation, or incentivize different types of interaction? What are downstream effects of these choices?
Readings:
- Bijan Stephen for The Verge: "Something Awful's Founder Thinks Youtube Sucks at Moderation" (2019) - strategies for moderation from Something Awful's founder
- Casey Newton for The Verge: "Bodies in Seats" (2019) - around outsourced content moderation & its impacts on the humans who have to view & judge the content. Would recommend:
- From the beginning to "But for the first time, three former moderators for Facebook in North America agreed to break their nondisclosure agreements and discuss working conditions at the site on the record."
- NOT RECOMMENDED: the middle of the article for this group– it's good reporting but needs a content warning for graphic descriptions (and the intro gets the points across)
- Jussi Passanen: "Human centred design considered harmful" – how good design principles applied to business sense can be harmful for humans, especially in the context of a livable planet
- Choose one of the following (their lengths vary):
- Mark Scott for Politico EU: "Why Banning Political Ads on Social Media Misses the Point" (2019) - argues that beginning to moderate content for advertising is the beginning of social media companies taking ownership/responsibility over user content generally
- Niam Yaraghi for Brookings: "Twitter's Ban on Political Advertisements Hurts Our Democracy" (2020) - discusses the unequal impact of the ban on more vs less-well funded political groups and pushes for more detailed transparency measures
- Kate Conger for the New York Times: "Twitter Will Ban All Political Ads, C.E.O. Jack Dorsey Says" (2019) – contrasted with the Facebook hands-off approach and Google's selective approach
- Choose one of the following (their lengths vary):
- Clint Pumphrey for HowStuffWorks: "How Do Advertisers Show Me Custom Ads?" (2012) – cookies and retargeting, notice tone
- Cade Metz for the New York Times: "How Facebook's Ad System Works" (2017) – targeting factors that Facebook uses for ads, the inception of ads into a content stream, some treatment of the Russia issue
- Cole Nemeth for Sprout Social: "How the Twitter Algorithm Works in 2020" (2020) before "How to turn off the Twitter algorithm" – a really short one just highlighting the factors involved
- Will Oremus for Slate: "Twitter's New Order" (2017) – much more in depth (not just how but why and future directions) but pretty long
- Josh Constine for TechCrunch: "How Facebook News Feed Works" (2016) before "An Updated List Of News Feed Algorithm Changes"
Optional bonus readings
- Naomi Wu's experience with media manipulation & being "content moderated" off of several funding platforms she had used to make a living: part 1 and part 2 – this is very interesting and topical but too long to include in the required reading
- Flame Warriors, if you'd like a lighter take, is a tongue-in-cheek characterization of the various types of people moderators encounter
- The end of the Casey Newton "Bodies in Seats" article, from "Last week, I visited the Tampa site with a photographer." to the end, interesting additional perspective re trying to figure out how this stuff should be done
May 12
Most of our data and information is controlled by a handful of companies. How did this come to be, what are examples of responsible and irresponsible holding of this power, and how do we imagine we might slip the trap of data monopolies?
Readings: Anti competitiveness, and how did we get here?
- Modern day monopolies: Matt Stoller, Wall Street Journal (2019): Why U.S. Businesses Want Trustbusting
- Adam Davidson, New Yorker (2017): Teddy Roosevelt Would Not Understand the E.U.’s Antitrust Fine Against Google
- Prof. Dr. Wernhard Möschel (2007): US vs EU Antitrust Law: pdf download
What are the things we worry about with monopolies?
- Economic / social / political bads as outcomes of monopolistic power: Ron Amadeo, Ars Technica (2018): Internet rages after Google removes "view images" button, bowing to Getty
- Getty (2016): Getty Images to file competition law complaint against Google
Data Monopolies in a COVID era?
- Contact tracing and privacy? Kim Lyons, The Verge (May 2020): Senators’ plan for reining in contact tracing apps doesn’t make a lot of sense
- Data Privacy bill in response: U.S. Senate Committee on Commerce, Science, and Transportation, Press Release (Apr 2020): Wicker, Thune, Moran, Blackburn Announce Plans to Introduce Data Privacy Bill
- Contact tracing proposal from Apple / Google: Google Blog (2020): COVID-19 Exposure Notification Using Bluetooth Low Energy
Optional bits to play around with for discussion:
- Can data monopolies be a force for good? Facebook Data for Good: Disease Prevention Maps
- Google/FB/Apple reports about data movement: Facebook Data for Good Mobility Dashboard
- More reading on modern monopolies: Harry Lambert, NewStatesman (2019): Matt Stoller's Goliath: the rise of big tech
June 9
New technologies attempt to free us from (data) monopolized spaces, but does cryptographic trust truly map onto or enable better human-to-human (or human-to-company or human-to-technology) trust?
Readings:
- [Optional] doteveryone. (2020). Executive Summary only from People, Power and Technology: The 2020 Digital Attitudes Report for a take on trust in the technology context more broadly
- Wikipedia contributors. (2020, May 15). Trust (social science)
- Satoshi Nakamoto. (2009). Introduction only from Bitcoin: A Peer-to-Peer Electronic Cash System for the thing that kicked off this wave of trust-free technology
- Libra Association Members (2020). Cover Letter (pp. 1-3) and Libra Association (pp. 24-26) only from Libra White Paper v2.0 for a view on gatekeeping and trust
- David Cohen and William Mougayar (2015, Jan 18). After The Social Web, Here Comes The Trust Web
- Finn Brunton (2019). Chapter 3 (pp. 33-46) and "The Trust Bulb" in Chapter 10 (pp. 165-170) only from Digital Cash: The Unknown History of the Anarchists, Utopians, and Technologists who created Cryptocurrency
September 22
How have particular implementations of data privacy policies impacted humans, economics, and legal systems? What are appropriate expectations around data privacy, and who should inform, create, or enforce policies?
Readings:
Grounding
- Brookman & Hans, Center for Democracy & Technology (2013) Why Collection Matters: Surveillance as a De Facto Privacy Harm on why data collection matters
- (optional) Hochfellner, Lane, and Kreuter, Responsible Data Science, NYU Center for Data Science (2019) Privacy and Confidentiality slides 1-9, 14, 18-19, 35-37 definitions and introductions to challenges and tools
Attempted and proposed solutions
- Sobers, Varonis (a cybersecurity company) (2020) A Year in the Life of the GDPR: Must-Know Stats and Takeaways a review of one year of GDPR implementation
- Office of the Press Secretary, The White House (2012) We Can’t Wait: Obama Administration Unveils Blueprint for a “Privacy Bill of Rights” to Protect Consumers Online Obama White House proposed approach
- O'Connor, Digital and Cyberspace Policy Program, Council on Foreign Relations (2018) Reforming the U.S. Approach to Data Protection and Privacy a critique of current U.S. approach and suggestion for path forward
- (optional) Balkin & Zittrain, The Atlantic (2016) A Grand Bargain to Make Tech Companies More Trustworthy on applying the legal concept of a fiduciary to information as well as to finances (intersection with Trust conversation)
Other optional readings
- (optional) FTC (2017) Informational Injury Workshop insight on how the U.S. government collects public comment on this topic
- (optional) Challenging algorithmic profiling: The limits of data protection and anti-discrimination in responding to emergent discrimination
November 3
Who are the groups of people to whom we are connected in systems of governance? To whom do we owe allegiance?
Readings:
- Grounding (volunteerism and polities in technology):
- Microstructures and Design Elements of Liberating Structures
- 🎬 Democracy --> Sociocracy (un)learning individual and group patterns [whole video encouraged!]
- The Catalan Integral Cooperative: an organizational study of a post-capitalist cooperative, focus on 1. Introduction, 3. CIC in a nutshell, 9. Summing up...
Other material:
Here are some guidelines about preparation in order to facilitate a session:
- Before the session:
- Have read and thought about the texts
- Identify and write 2-4 "themes" or questions you are interested in from the readings
- We use the same shared notepad: https://hackmd.io/oEcuKALCTi-PbawLmT_Ixw#, which uses a template for notes
- During the session:
- Arrive on time (call should auto record as the first person enters)
- Ensure the call is recorded (it should auto-record as the first person enters, but always make sure someone presses the record button if not)
- Ask for someone to take notes
- Keep time and gently wrap us up
- After the session:
- Copy the notes and open a pull request in this repository
We maintain a shared bibliography in the datatogether Zotero group, which includes potential readings.
Anyone can request an invite on a call or by creating a github issue in this repository with their Zotero username.
Data Together Reading Group Materials are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
See the LICENSE file for details.