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The instructions below explain how to use the card deck to respond to a design prompt. However, I encourage you to experiment to discover how the deck might best help you incorporate and/or reflect upon the use of predictive algorithms in your practice.

Workshop Instructions for ML Cards

  • Each group should have a deck of cards. Separate your cards into four piles (one color in each pile). Set aside the gray cards (Ethics) for now. Focus on the blue, red and green cards (Augment, Anticipate, Personalize) for this first round. 
  • Pull a prompt from the provided options or begin with a prompt of your own. Once the first prompt is selected, draw a card from each of the three piles. Be sure to select whatever card appears on top of the pile. Don’t shift through them to select the best one.
  • Working together as a group respond to the prompt using the strategies on the three selected cards. Focus on one strategy at time initially and then begin to combine strategies. To use a card ask yourself: “How could your design [do whatever’s on the card] to respond to the prompt, i.e. meet a human need?”
  • Move through this exercise several times using new prompts. Then pick several of your strongest ideas.
  • Sketch out your ideas to explore each of the experiences or interfaces that you came up with. 
  • Now return to the pile of gray cards (Ethics). Consider the questions posed on all 9 gray cards in relation to each of your sketches. Iterate/revise as appropriate.
  • Come back together as a larger group to discuss the results.  

This card deck is part of my larger research project: a book entitled Big Data. Big Design. Why Designers Should Care about Machine Learning (Princeton Arch Press, 2021)

Students using machine learning cards to incorporate Ml technology into their current project. In the image students discuss and sketch in reaction to the cards before them.
Machine learning card deck. Cards are the size of standard business cards. Cards are divided into four categories: blue: Augment, red: Anticipate, green: Personalize, and gray: Ethics. Each category includes 9 cards. Each card has a different prompt that urges the user to experience with a specific function of predictive algorithms.

Additional Resources:

GENERAL ML

Machine Learning for Designers by Patrick Hebron (book)

You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place by Janelle Shane (book)

Prediction Machines by Ajay Agrawal, Joshua Gans, Avi Goldfarb (book)

Machine Learning: The New AI by Ethem Alpaydin (book)

A People’s Guide to AI by Mimi Onuoha and Mother Cyborg (Diana Nucera) (zine)

Frontline: In the Age of AI (documentary)

The Great Hack (Netflix documentary)

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ETHICS

Rumman Chowdhury: Building Ethical and Responsible Technology into Government (lecture)

21 Definitions of Fairness and Their Politics (lecture)

Caroline Sinders: AI is More Than Math: Using Art and Design to Interrogate Bias in AI (lecture)

Data Selves by Deborah Lupton (book)

Weapons of Math Destruction by Cathy O’Neil (book)

Invisible Women by Caroline Criado Perez (book)

When Biometrics Fail by Shoshana Amielle Magnet, (book)

The Age of Surveillance Capitalism by Shoshana Zuboff (book)

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CONVERSATIONAL INTERFACE

The Voice in the Machine by Roberto Pieraccini

Wired for Speech by Clifford Nass and Scott Brave

Conversational Design by Erica Hall

Designing Voice User Interfaces by Cathy Pearl

Designing for Conversation: List of articles by Paul Pangero

VoiceFlow (prototyping tool for voice interface)

DialogFlow (Google prototyping tool for text or voice based interface)