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AI Bingo turns a familiar game into a practical way to ask how AI works: What is a technology trying to predict, and what information might it use? Make a five-by-five card of technologies your family recognizes, then take turns explaining the predictions behind them. The aim is thoughtful discussion, not getting every technical detail right.
What kids learn from AI Bingo
AI systems can use a dataset and a learned method to make predictions. That does not mean a device is thinking like a person: it means a system has been built to make a particular kind of estimate or choice from information.
The game also helps children notice that a familiar service can contain different features, and that not every feature should be treated as one single AI system. Ask about the specific task: for example, a video service might recommend what to watch, while a voice assistant might try to recognize spoken words. The data selected and the goal chosen by people can shape how well a system works and how it affects different people.
Set up a family game
The activity is adapted from Blakeley H. Payne’s MIT Media Lab-supported An Ethics of Artificial Intelligence Curriculum for Middle School Students, dated August 2019 and designed for approximately grades 5–8. MIT describes AI Bingo as a 30-minute classroom activity. Its original format has students find a partner who has used a listed system, then discuss the system’s prediction and possible dataset. For a family game, a parent can be a child’s partner, or siblings can pair up; that is a practical adaptation, not a separately tested format.
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- Make a card. Draw a five-by-five grid and write one technology or feature in each square. You can use the examples below, or let children suggest things they encounter. These are prompts, not a claim that every product or feature always uses AI.
- Choose a partner. Players take turns asking whether their partner has used a technology on the card. If yes, discuss what the system might be trying to predict and what data could help it do that.
- Mark a square. Mark it when the partner has used the system and the pair has offered a reasoned prediction-and-data explanation. There may be more than one plausible answer; the point is to explain the guess.
- Play to five. The first player to fill five squares in a horizontal, vertical, or diagonal line wins. For a longer game, play until someone fills two lines.
- Review the card. After play, compare a few filled squares and talk about what was easy or difficult to work out.
Example squares for a homemade card
Use these as a menu rather than a required or official MIT card. Keep the named task specific, because the same product may offer several features.
- Video recommendations
- Music recommendations
- Online shopping recommendations
- Search result ranking
- Email spam filtering
- Phone face recognition
- Photo organization by subject
- Voice-to-text transcription
- Voice assistant speech recognition
- Map route or arrival-time estimates
- Keyboard next-word suggestions
- Autocorrect suggestions
- Game opponents that adapt to play
- Photo filters that identify faces
- Image search
- News or social-feed ranking
- Fraud alerts on a payment
- Video captions or translation
- Smart-home voice controls
- Weather forecasts
- Customer-service chat responses
- Content moderation
- Fitness activity estimates
- Accessibility tools that describe images
- Autofill suggestions
Model one square before playing
Video recommendations
Ask: “What is the system trying to predict?” A reasonable answer is that it is estimating which video a viewer may choose to watch next. Then ask: “What information might help it make that estimate?” Children might suggest videos watched before, searches, likes, or how long a viewer watched. These are possible examples, not a verified list of data used by any particular service. Explain that an actual service’s inputs can differ and may not be visible to players.
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Encourage kids to distinguish the prediction from the data: “It predicts what I might watch” is the prediction; “it may use what I watched before” is a possible data source. If a child gives another plausible answer, ask what makes it plausible instead of treating the game as a test with one exact answer.
Questions to ask after the game
- Which systems were easiest to explain? What made those predictions easier to spot?
- What information might help a system make a prediction? What information might be missing?
- Could the same system make a less accurate prediction for someone with different habits or experiences?
- Who chose what the system should try to predict, and what might happen if that goal is wrong for a user?
- Which answers were guesses rather than facts about how a particular product works?
These questions connect the activity to accuracy and fairness without implying that a child can determine a commercial system’s actual data or design from the outside. The MIT curriculum’s broader learning objectives include considering how training data affects accuracy, how dataset composition can create bias, and how people shape AI goals and experience their effects.
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Age, timing, and what the activity can show
The MIT Media Lab curriculum version targets approximately grades 5–8 and lists AI Bingo as a 30-minute activity. MIT Full STEAM Ahead also lists a bingo-style AI activity among its K–5 activities, suggesting the format can be adapted for younger children. That does not establish that the middle-school worksheet itself has been validated for every age; for younger players, use familiar examples and help them separate the prediction from the possible data.
The curriculum sets out learning objectives and directions, but the consulted sources do not report measured learning gains from this particular bingo game. Treat it as a conversation starter and an introduction to asking useful questions, not proof that a child has mastered AI.
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Where to continue the conversation
Common Sense Education and Day of AI offer a free AI Literacy Toolkit for Families, with short videos, family activity guides, conversation cards, and a glossary. Its topics include what AI is, privacy, fairness, responsibility, and using AI wisely for school success. You can use those materials as a guided follow-up if the game raises questions your family wants to explore further.
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