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A Samuel Pottinger and
Varsha Gopalakrishnan
Re-Empower the People with
Data Visualization
and Game Design
👋 Hello!
Introduction Challenge Discussion
Worksho
p
Setting the stage
Conversation
Examples Explore
Analysis Represent
Participate Context
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?
Introduction Challenge Discussion
Worksho
p
Setting the stage
Conversation
Examples Explore
*Views our own and not reflective of another organization. See notice.
Analysis Represent
Participate Context
🗺️ Overview
Discussion
Worksho
p
Setting the stage Examples Explore
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.
Analysis Represent
Participate Context Conversation
🏔️ The Challenge: analysis
Introduction Challenge Discussion
Worksho
p
Setting the stage Examples Explore
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.
Analysis Represent
Participate Context Conversation
🏔️ The Challenge: participation
Introduction Challenge Discussion
Worksho
p
Setting the stage Examples Explore
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.
Analysis Represent
Participate Context Conversation
🏔️ The Challenge: context
Introduction Challenge Discussion
Worksho
p
Setting the stage Examples Explore
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.
Analysis Represent
Participate Context Conversation
🏔️ The Challenge: representation
Introduction Challenge Discussion
Worksho
p
Setting the stage Examples Explore
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
Analysis Represent
Participate Context Conversation
Introduction Challenge Discussion
Setting the stage Examples Explore
🗺️ 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.
Analysis Represent
Participate Context
Worksho
p
Conversation
🛝 What’s next
Introduction Discussion
Setting the stage Explore
We have some examples
For you to explore and play with before we have some
group conversation.
Challenge Workshop
Conversation
Analysis Represent
Participate Context
Examples
⭐️ Solution Example: participation
Introduction
Setting the stage Examples Explore
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
Challenge Discussion Analysis Represent
Participate Context Workshop
Conversation
⭐️ Solution Example: analysis
Introduction
Setting the stage Examples Explore
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
Challenge Discussion Analysis Represent
Participate Context Workshop
Conversation
⭐️ Solution Example: representation
Introduction
Setting the stage Examples Explore
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
Challenge Discussion Analysis Represent
Participate Context Workshop
Conversation
⭐️ Solution Example: context
Introduction
Setting the stage Examples Explore
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
Challenge Discussion Analysis Represent
Participate Context Workshop
Conversation
🛝 What’s next
Introduction Discussion
Setting the stage Explore
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?
Challenge Workshop
Conversation
Analysis Represent
Participate Context
Examples
🗣️ Conversation
Introduction
Worksho
p
Setting the stage
Conversation
Explore
Let’s talk:
What day to day AI systems most concern you?
What AI system would we want to change or
democratize?
Challenge Discussion
Examples
Analysis Represent
Participate Context
🔧 Workshop
Introduction
Setting the stage Explore
Let’s talk:
How might we invert or democratize the example
system from the last slide?
Challenge Discussion
Examples
Workshop
Conversation
Analysis Represent
Participate Context
🚀 Synthesis
Introduction
Setting the stage Explore
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?
Challenge Discussion
Examples
Workshop
Conversation
Analysis Represent
Participate Context
[ 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

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Re-Empower the Public with Data Visualization and Game Design

  • 1. A Samuel Pottinger and Varsha Gopalakrishnan Re-Empower the People with Data Visualization and Game Design
  • 2. 👋 Hello! Introduction Challenge Discussion Worksho p Setting the stage Conversation Examples Explore Analysis Represent Participate Context 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
  • 3. 👋 Hello! Sam Pottinger Varsha Gopalakrishnan What makes for meaningful transparency? Introduction Challenge Discussion Worksho p Setting the stage Conversation Examples Explore *Views our own and not reflective of another organization. See notice. Analysis Represent Participate Context
  • 4. 🗺️ Overview Discussion Worksho p Setting the stage Examples Explore 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. Analysis Represent Participate Context Conversation
  • 5. 🏔️ The Challenge: analysis Introduction Challenge Discussion Worksho p Setting the stage Examples Explore 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. Analysis Represent Participate Context Conversation
  • 6. 🏔️ The Challenge: participation Introduction Challenge Discussion Worksho p Setting the stage Examples Explore 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. Analysis Represent Participate Context Conversation
  • 7. 🏔️ The Challenge: context Introduction Challenge Discussion Worksho p Setting the stage Examples Explore 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. Analysis Represent Participate Context Conversation
  • 8. 🏔️ The Challenge: representation Introduction Challenge Discussion Worksho p Setting the stage Examples Explore 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 Analysis Represent Participate Context Conversation
  • 9. Introduction Challenge Discussion Setting the stage Examples Explore 🗺️ 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. Analysis Represent Participate Context Worksho p Conversation
  • 10. 🛝 What’s next Introduction Discussion Setting the stage Explore We have some examples For you to explore and play with before we have some group conversation. Challenge Workshop Conversation Analysis Represent Participate Context Examples
  • 11. ⭐️ Solution Example: participation Introduction Setting the stage Examples Explore 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 Challenge Discussion Analysis Represent Participate Context Workshop Conversation
  • 12. ⭐️ Solution Example: analysis Introduction Setting the stage Examples Explore 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 Challenge Discussion Analysis Represent Participate Context Workshop Conversation
  • 13. ⭐️ Solution Example: representation Introduction Setting the stage Examples Explore 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 Challenge Discussion Analysis Represent Participate Context Workshop Conversation
  • 14. ⭐️ Solution Example: context Introduction Setting the stage Examples Explore 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 Challenge Discussion Analysis Represent Participate Context Workshop Conversation
  • 15. 🛝 What’s next Introduction Discussion Setting the stage Explore 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? Challenge Workshop Conversation Analysis Represent Participate Context Examples
  • 16. 🗣️ Conversation Introduction Worksho p Setting the stage Conversation Explore Let’s talk: What day to day AI systems most concern you? What AI system would we want to change or democratize? Challenge Discussion Examples Analysis Represent Participate Context
  • 17. 🔧 Workshop Introduction Setting the stage Explore Let’s talk: How might we invert or democratize the example system from the last slide? Challenge Discussion Examples Workshop Conversation Analysis Represent Participate Context
  • 18. 🚀 Synthesis Introduction Setting the stage Explore 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? Challenge Discussion Examples Workshop Conversation Analysis Represent Participate Context
  • 20. 📝 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.
  • 21. 📚 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.
  • 22. 🌇 Image Credits Lucas Clara Unsplash License Redd F Unsplash License John Cameron Unsplash License Johnathan Borba Unsplash License Pond Juprasong Unsplash License