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Let’s play 20 questions!

Last week it was my turn to facilitate a 30-minute activity, and how Edward de Bono would say “Humor and creativity can change that road we always take and do some lateral thinking”, so, by putting myself in a green hat mood I did a small game to get the creativity up and coming. I connected the readings about the digital addiction by Jan Leslie and why do we have metrics? by Joe Edelman.

 

Intro

First of all, I started by setting the stage, in order to do that I wanted all of the members of my team to be in the same channel, so, I wrote down on a big board the goal, focus and take away this activity should provide when completed. The activity started right after setting the stage and then we had a discussion of how they felt in this activity and what questions they had lingering after doing the game.

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The main goal of this exercise would be to understand how the metrics as simple maximizers1 are forming the data that media has defined as “who we are“ according to the reading of Joe Edelman. Also, I wanted to make an emphasis in the reading of Jan Leslie to build empathy with the feeling of an operant conditioning chamber2, so, in less words build empathy with the rat that had been inside that box, my team being the rat in this case. The areas where I wanted to focus were the metrics and the Skinner Box, specifically on rewards and hot triggers.

The take away I wanted my team to leave with after this exercise. Firstly, I wanted them to see the algorithms with a different lens (a green hat lens) of how by describing people with algorithms of behavior (as media does sometimes) they are missing out the values, goals and reasons for them to be who they are. Secondly, to incorporate some hot triggers to have more motivation on the activity, I gave them a Halloween candy for each time they had a right answer as a reward, for a wrong answer there was no reward and with no participation, you had no candy at all. The rewards would hopefully make the team feel good and therefore feel more motivated in participating (as the rat did every time he pressed the lever and a reward came along).

 

Let’s play 20 questions!

The game started, like any game, by explaining the rules of the game. Behind the piece of paper with the exclamation mark there was one person that I choose, no one knew who it was except for me. They, as a team, had to ask me no more than 20 yes/no questions to guess correctly (the questions being the simple maximizers1). However, I did not tell them where would be rewards when having a correct answer, I wanted to leave that as a surprise.

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The team started by asking:

  • Are you a living thing? Yes (reward with candy)
  • Are you a celebrity? Yes (reward with candy)
  • Are you into politics? No (no reward)
  • Are you a singer? Yes (reward with candy)
  • Are you a woman? Yes (reward with candy)
  • Are you an actress? Yes (reward with candy)
  • Are you an African American? (reward with candy)
  • Are you and oldie? No (no reward)
  • Are you a comedian? Yes (reward with candy)
  • And with some help they found the celebrity I had chosen…

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It’s Lizzo, who does not like her, right?

After showing her picture, I wrote down the word “Algorithms” all the things they asked for where similar as how social media thinks of us, by knowing those kinds of things they can know which kinds of ads, friends in common, likes and dislikes we have. But as Joe Edelman said in his writing, they are missing the greatest part of al, the reason why we do those things. For example, Lizzo started singing because she wanted to make his father proud after he passed away, or that she appreciates her body and challenges other women to see their body as what it is and not go with what fashion says it’s correct. So those are the main values and reasons she has behind doing what she does.

So, some questions came up doing this activity, what are they missing? What are her real values? Do algorithms define you? What it means to understand someone as a person? When you describe a friend, what do you think about her/him?, do you describe your friend as that blue robot in the picture above or do we describe them with values and things that are important to you about them.

After doing the game we had some sort of discussion about how they felt about this activity and what main take away they had after the questions. How did the candy reward felt? How did the game felt? Overall they felt the way I intended to and I was happy that the discussion went well and we all had a good talk about the activity.

 

Reflection and self-reflection

  • As a team reflection we had some discussion about how algorithms are good for some people and bad for other, like for example, for me, those alcogithms don’t define me, I don’t like being pushed to buy things that media knows I like, but I obviously can’t afford. Some other teammates had the opposite reaction. At the end ethics is a personal way of thinking and there are no right or wrong answers. The team left a feedback that maybe having more time to debrief after the activity would have been helpful, which I agree.
  • As a reflection with faculty they said that I lacked of a ultimate take away as designers, what can we do as designers? Ending up with a how might we…  And also that the candy reward would have been better as an “aha moment” of surprise at the end of the activity, which I agree.
  • As a self-reflection I would like to say to myself from the future, to do the activity with real people to timebox the actual time that is takes to complete the activity. I had 30-minutes and I thought that the activity would take 50% of the time but it actually lasted for about eight minutes, which thankfully I had a very participatory team and could do great discussion. But maybe for the next facilitation, have another activity prepared just in case I have some spare time.

 

If you have additional thoughts on how I could build or improve on the activities listed above – please reach out to me!

Ana.toca@austincenterfordesign.com

 

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1 Simple maximizers are metrics that work as equations that give each option a number. The metric then evaluates potential future states of the world. And it always picks the option that leads to the world with the highest score.

2 Operant conditioning chambers is a laboratory apparatus used to study animal behavior. The operant conditioning chamber was created by B. F. Skinner while he was a graduate student at Harvard University. It permits experimenters to study behavior conditioning (training) by teaching a subject animal to perform certain actions (like pressing a lever) in response to specific stimuli, such as a light or sound signal. When the subject correctly performs the behavior, the chamber mechanism delivers food or another reward. In some cases, the mechanism delivers a punishment for incorrect or missing responses.