A Samuel Pottinger and
Varsha Gopalakrishnan
Re-Empower the People with
Data Visualization
and Game Design

👋 Hello!
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We are sending out a Workflowy where you can introduce yourself and answer the
first question: what most worries you about AI / ML?
We will get rolling at 3 minutes after. Note that this recording and notes may be
released Creative Commons later.
Music: Leave a Legacy by Poor Legacy under CC-BY-3.0

👋 Hello!
Sam Pottinger
Varsha
Gopalakrishnan
What makes
for meaningful transparency?
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*Views our own and not reflective of another organization. See notice.
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🗺️ Overview
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Introduction Challenge
Data system
You should care about data
collection because the
information can be personal
and revealing or creates a
power imbalance between you
and some other organization.
Transparency
Transparency is often used as
a “solution” but we have to
ensure that transparency
efforts are actually meaningful
and empowering.
Participation
We believe “designing for
participation” can ensure
transparency is meaningful.
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🏔️ The Challenge: analysis
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What is meaningful publication of data?
Data may be fully disclosed but not useful unless
there are public tools available to analyze them.
Asymmetry: Tools available to one party to make data
useful are not available to another party.
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🏔️ The Challenge: participation
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What consent is really given?
Data can inform solutions but disclosure
isn't meaningful unless the tools used to
make those solutions are inclusive.
Asymmetry: Different parties’ ability to
decide if / how they want to participate in
a system.
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🏔️ The Challenge: context
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What does disclosure really mean?
Data requires contextualization and tooling to make it
actionable otherwise the disclosure isn't meaningful.
Asymmetry: One party has access to contextual or
distributional data while the other does not.
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🏔️ The Challenge: representation
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What does data access provide?
Data may be publicly disclosed but must be
contextualized for an individual in order to activate
advocacy. Data asymmetry can be caused by data
aggregation resulting in lack of representation.
Asymmetry: One party becomes more represented
than another.
Median income: $139k
Number of sensors per 10,000 people: 15.4
Median income: $87k
Number of sensors per
10,000 people: 4.3
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Introduction Challenge Discussion
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🗺️ What’s going on?
Data in systems
The fields of systems design and game design offer some help
in understanding what’s going on here.
Differences between actors in a system creates asymmetric
design.
This systems lens helps us see common issues for AI
transparency efforts and what might be done to help.
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Conversation

🛝 What’s next
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We have some examples
For you to explore and play with before we have some
group conversation.
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Examples

⭐️ Solution Example: participation
Introduction
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FoodSim: San Francisco
Data can inform solutions but disclosure isn't
meaningful unless the tools used to make those
solutions are inclusive.
Pattern: Lower the barrier for entry, allowing a broader
group of people to choose to participate.
Tool: Game design
Demo
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⭐️ Solution Example: analysis
Introduction
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Colorado TRACER Analysis
Data may be fully disclosed but not useful unless there are
public tools available to analyze them.
Pattern: Provide the same capabilities to all actors for
deriving value from data.
Tool: Machine learning
Link
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⭐️ Solution Example: representation
Introduction
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Interactive hyperlocal air quality
Data may be publicly disclosed but must be
contextualized for an individual in order to activate
advocacy. Data asymmetry can be caused by data
aggregation resulting in lack of representation.
Pattern: Allow for individualization in advocacy.
Tool: Information design and Machine Learning
Link
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Conversation

⭐️ Solution Example: context
Introduction
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Start-Up Options Bot
Data requires contextualization and tooling to make it
actionable otherwise the disclosure isn't meaningful.
Pattern: Offer tools for contextualization of data to
reduce information asymmetry.
Tool: Information design
Demo
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Conversation

🛝 What’s next
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Let’s play
Let’s look at the food simulation as an example in
breakout rooms.
Question: What do you get from this tool versus a
spreadsheet with the same data?
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Examples

🗣️ Conversation
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Let’s talk:
What day to day AI systems most concern you?
What AI system would we want to change or
democratize?
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🔧 Workshop
Introduction
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Let’s talk:
How might we invert or democratize the example
system from the last slide?
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🚀 Synthesis
Introduction
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Let’s talk:
Leave your takeaways and follow up ideas in the
workflowy. Also, places for further engagement:
● Processing Forums
● Data Visualization Society
● MIT Design Justice Community
● City Data curated from government and privates sources for all cities
in the US
What others can you add?
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[ Appendix ]

📝 License / notice
Creative Commons
These slides are made available under the CC BY-NC-
SA 3.0 license.
Link
Views are our own
The views expressed are those of Sam and Varsha. They do not attempt to reflect
those of any other organization or any work cited.
Open science
All works cited are publicly available. All demos linked are pre-existing open source
contributions. See Works Cited for code and data.

📚 Works Cited
Bell-Mayeda, Melanie. “What Is Systems Design? How to Surface Opportunities for Change.” IDEO U, IDEO, https://www.ideou.com/blogs/inspiration/what-is-systems-design-how-to-surface-
opportunities-for-change.
Burgun, Keith. “Asymmetry in Games.” Game Developer, Informa, 1 Oct. 2015, https://www.gamedeveloper.com/design/asymmetry-in-games.
Crockford, Kade. “How Is Face Recognition Surveillance Technology Racist?: News & Commentary.” American Civil Liberties Union, 16 June 2020, https://www.aclu.org/news/privacy-technology/how-is-
face-recognition-surveillance-technology-racist.
“Data Practices & Transparency.” Google, Google, https://safety.google/privacy/data/.
Gopalakrishnan, Varsha. “Hyperlocal Air Quality Prediction Using Machine Learning.” Medium, Towards Data Science, 8 Feb. 2021, https://towardsdatascience.com/hyperlocal-air-quality-prediction-
using-machine-learning-ed3a661b9a71.
Harwell, Drew, and Nick Miroff. “Ice Just Abandoned Its Dream of 'Extreme Vetting' Software That Could Predict Whether a Foreign Visitor Would Become a Terrorist.” The Washington Post, WP
Company, 5 Dec. 2021, https://www.washingtonpost.com/news/the-switch/wp/2018/05/17/ice-just-abandoned-its-dream-of-extreme-vetting-software-that-could-predict-whether-a-foreign-visitor-would-
become-a-terrorist/.
Hodge, Rae. “Police Will Get AI-Powered License Plate Readers, but Ethical Concerns Remain.” CNET, CNET, 24 Oct. 2019, https://www.cnet.com/home/security/police-will-get-ai-powered-license-
plate-readers-but-ethical-concerns-remain/.
“Home.” TRACER, Colorado Secretary of State, https://tracer.sos.colorado.gov/PublicSite/HomePage.aspx.
Jung, Yoohyun, and Danielle Echeverria. “Where Low Cost Air Quality Sensors Are - and Aren't - in the Bay Area.” The San Francisco Chronicle, The San Francisco Chronicle, 11 Oct. 2021,
https://www.sfchronicle.com/projects/2021/purple-air-monitors-california/.
Kramer, Adam D., et al. “Experimental Evidence of Massive-Scale Emotional Contagion through Social Networks.” Proceedings of the National Academy of Sciences, vol. 111, no. 24, 2 June 2014, pp.
8788–8790., https://doi.org/10.1073/pnas.1320040111.
Pottinger, A S. “FoodSim: San Francisco.” FoodSim, Sam Pottinger, 16 Apr. 2023, https://foodsimsf.com/.
Pottinger, A S. “Startup Options Bot.” Startup Options Bot, Sam Pottinger, 20 Oct. 2022, https://startupoptionsbot.com/.
Pottinger, A S. “TRACER Analysis.” Sam Pottinger, 2013, https://gleap.org/content/tracer_analysis.
Ryan-Mosley, Tate. “A New Map of NYC's Cameras Shows More Surveillance in Black and Brown Neighborhoods.” MIT Technology Review, MIT Technology Review, 14 Feb. 2022,
https://www.technologyreview.com/2022/02/14/1045333/map-nyc-cameras-surveillance-bias-facial-recognition/.
Smith, Stacey Vanek. “The Big Reveal: New Laws Require Companies to Disclose Pay Ranges on Job Postings.” NPR, NPR, 5 Nov. 2022, https://www.npr.org/2022/11/05/1134193927/salary-
transparency-range-new-york-pay-laws.

🌇 Image Credits
Lucas Clara
Unsplash License
Redd F
Unsplash License
John Cameron
Unsplash License
Johnathan Borba
Unsplash License
Pond Juprasong
Unsplash License