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Introducing #ForYou: A Game About Algorithms
Not many words have had a rise as meteoric as the term “algorithm.” Once only familiar to mathematicians or computer scientists, today algorithms are the subject of warnings from scholars and activists, personified and catered to by would-be YouTube stars, and seen as the almost magical element that is vital to the success of newer platforms such as TikTok.
MediaSmarts’ research, however, shows that while young people are now highly familiar with the idea of algorithms, they have little understanding of how they actually work. When we asked young people to explain what an algorithm was, most shared examples of their interactions with a recommendation algorithm on a platform like Instagram, Netflix, TikTok or YouTube, and expressed a sense of powerlessness and a lack of control when it came to the influence and impact of algorithms in their lives. That’s why MediaSmarts has launched #ForYou: A Game About Algorithms, a tabletop card game designed not just to teach players about recommendation algorithms but to get them to reflect on and ask critical questions about the role that algorithms play in their lives.
#ForYou has three phases, each of which introduces a different way in which recommendation algorithms work:
- The Popularity phase, in which players try to get their video seen by as many people as possible;
- The Advertising phase, in which players try to make sure their ads will be seen by the right audience; and
- The Machine Learning phase, where players learn how proxy data can infer extra information about users.
Each phase has two rounds: in the first round players try to find out as much as possible about the algorithm, and in the second round they use what they’ve learned to try to “game” it.
In the Popularity phase, the player designing the algorithm chooses an Optimization card, which represents the different things a platform might use their algorithm to do – to get them to watch videos for longer, for instance – and shows it to the other players.
They then design an algorithm using three of the six algorithm cards. Each of these stands for something an algorithm might measure to decide how widely to recommend a video: how many “Likes” it has received, for example. The algorithm player then ranks these three, from most to least important, and places them face down in front of them.
Next, the other players – who are each taking the role of an aspiring video-maker – draw five Video cards and play one. The Algorithm player now scores each of these videos according to how well it matches the algorithm cards they played (for instance, this one matches Likes and Subscribers). Videos receive three points if they match the top card, two if they match the second, and one if they match the third, leading to a score between zero and five.
The second round is where players try to “game” the algorithm, guessing based on the scores in the first round which algorithm cards were played and in what order. Based on that guess, they choose two of the Video cards remaining in their hands which they think will score highest.
To help players understand that algorithms can sometimes be manipulated in other ways, the game also features Boost cards. These stand for an “inauthentic” way of making something more popular, such as a Retweet Room (groups of accounts that all share each other’s posts, to make them seem like they’re going viral.)
The second and third phase follow the same basic gameplay, but add new issues and more complexity. In the second phase, the players are advertisers instead of video makers, and use Data cards – which represent personal information about users – to more effectively target their ads. In the third phase players learn about how machine learning can use what is known about a user as a “proxy” for something they don’t know – for instance, using someone’s name to guess their gender, or what websites they’ve visited to guess their sexual orientation – and use that for even more precise targeting.
#ForYou is accompanied by both a lesson plan and discussion guide. Both of these include instructions for not just playing the game but “pre-briefing” before each phase, to help players activate prior knowledge and introduce key information and ideas, and debriefing afterwards to reflect on what they’ve learned through gameplay.
From video sites to job applications, from our credit scores to the prices we’re charged when shopping online, algorithms have become an inescapable but often invisible part of our lives. We hope you’ll try out this card game in your classroom or community group to help young people understand how algorithms shape their lives – and what they can do to take control.
Find out how to order free sets of the card game here.
Matthew Johnson, Director of Education (MediaSmarts, Canada).
Article reposted with permission from Media & Learning Association