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Description
Game concept - Lots of facial recognition technology, particularly in the past, was much more accurate for certain demographics than others largely due to disparity in data (e.g Gender Shades Study (2018) – Joy Buolamwini & Timnit Gebru). We'd like to show why/how this exists through a game.
Essentially, we need to categorize "people" (here, we'll represent with shapes or cartoons or something for obvious reasons) into multiple groups. For instance, we may be classifying shapes into one of 4 categories (let's say no risk, low risk, mid risk, high risk of criminal activity to connect to facial recognition in criminal investigation, I'll sketch out context later dw). We'll already be given some pre-sorted shapes in each category - e.g one category contains a bunch of green triangles, another contains a bunch of blue triangles. But say for squares, only 1 category contains 1 red square, another only contains 1 blue square and 1 red square (point being, much less data for squares so harder to sort).
Then users will be given different shapes and asked to sort them, at the end we'll see the accuracy rate and notice its much higher for shapes where there's more data.
GOAL FOR THIS ISSUE: Get initial structure working.
- Create a new frame / use existing empty frame in the facial recognition case study page, and for now avoid graphics.
- Have an array of integers, pre-set to whatever you want (say of length 10-15). Only one element of array is visible on page at any time.
- There should be a 4 counters with clickable buttons, visible in the frame (location/visuals dont matter, this is just backend logic).
- Get the following functionality to work - I should be able to click a button and have the counter increment by 1. This should also switch to the next element in the array.
The idea is that this will be the backend for choosing which category (counter) to put each integer element (shape) in. The 4 counters should be independent so we can, in the future, track correct/wrong guesses.
Remember for now, visuals don't matter at all.