‘How (not) to get hit by a self-driving car’ is a street-based game that challenges anyone to avoid being detected by an AI-powered camera. In the game, players see themselves augmented on a large screen at the end of a playing field. Marking each player is a percentage signifying the level at which the AI sees them as a pedestrian. If this exceeds a certain limit, the player will lose, and so to win, players must figure out how to cleverly dodge the AI and reach the goal without detection.

Every player’s win generates vital data that exposes the inability of the system to detect pedestrians and highlights the flaws of these algorithms, which could potentially be used to improve self-driving cars in the future. As a result, players are presented with a final dilemma upon victory: either train the AI or not. They can opt-in their anonymised gameplay footage to improve the AI models, or immediately delete the image. This poses the question of whether people are willing to trade their data for a potentially safer system, or if they would rather remain invisible, despite the implied risks of inaccurate systems in the future.

Created by : Tomo Kihara & Dan Coppen (Playfool)

Stuff used :
– camera
– object detection algorithm
– traffic cones
– giant screen

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photography : Luke O’Donovan