Investigation 2 - Creative Exercise

Roleplaying Presences

tl;dr: As part of this exercise, you’ll explore questions of uncertaintly around systems, first-hand, and the value of ‘spookiness’ as a metaphorical approach by adapting/repeating the thought exercise from class to have a conversation with someone else about everyday intelligences. Time Limit: 2 hours

Learning Objectives

As part of this exercise you will be asked to:

Develop your awareness of the challenges surrounding complexity and expalinability in everyday systems and processes;
Explore the kinds of interpretations and beliefs that form around everyday technologies through light-weight user research; and
Examine the affordances of a ‘spooky’ or otherworldly lens on everyday technology.

Brief

Drawing on the examples introduced in class: work with someone from outside this class (a friend, family member etc.) engage them in a conversation (an short interview) where you examine an everyday technology of the smart and connected home. Use the supernatural entity or haunted metaphor to help this exploration.__ (OPTIONAL: Prepare a materialization or diagram their mental models.)__

This work is completed individually. In class groups you choose the entity/metaphor. We’ll use this to compare and contrast the conversations within your groups next week.

Post in #projects with a 100-150 word write up

Note This is a creative exercise and you should spend no more than 2 hours on this exercise.

Precedent Project

In this module, we’ll consider how the complexity of distributed, smart, and connected systems challenges explainability, but also provides a resource for critical design. In this exercise you’ll take cues from the work of Graham Dove (Links to an external site.) & Anne-Laure Fayard (Links to an external site.), and explore the how the supernatural can be useful metaphor to examine how people understand and intrepret everyday systems.

The authors note:

“Research into ML often focuses on explaining algorithmic decision-making or making it more transparent to users. However, transparency and explanations have limitations … Monsters are to be feared, but also are generative spaces, places to question, wrestle with uncertainty, resist easy classifications, name power.”
Graham Dove and Anne-Laure Fayard. 2020. Monsters, Metaphors, and Machine Learning. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ‘20). Association for Computing Machinery, New York, NY, USA, 1–17. DOI:https://doi.org/10.1145/3313831.3376275

In this study, “Monsters, Metaphors, and Machine Learning”, the authors developed a hands-on workshop to materialize questions posed by machine learning. They introduced a series of ‘monster cards’ (see above) to help encourage reflection on designing with machine learning. Each monster is related through a brief description to an aspect of machine learning’s uncertainty and processes. Using this, participants map out their assumptions and concerns about these processes and later materialize them as a monster using everyday materials.

Deliverables