The SODA 2020 conference will include a paper by Vincent Cohen-Addad (LIP6), Frederick Mallmann-Trenn (King's College) and Claire Mathieu (IRIF) about computing with noisy data. The problem: select valuable objects in a setting where each assessment has a probability of error, using redundant assessments.