There are about 200 biases. Even though each and every one is very interesting, one of the first steps we needed to take was selecting the biases we want to work with. In a first step, we clustered familiar biases and, of course, focused on biases that are relatable to learning. In the end, we still had a list of 93 biases. Obviously, a further selection was necessary. Therefore, we choose criteria that would help us with our final objective of this project: relatable to learning, suitable for video, responsive to de-biasing, measurable, frequently observed, scientifically established and, representative. After this hard piece of work, our list of biases was still very long. The final question will always be ‘Is this bias suitable for filming’? If it isn’t so, we can decide to replace it with a bias from the reserve list.