Description [en] This workshop was conducted at the Design Research Society Festival in Bilbao and is the result of a collaboration between DCODE students and non-academic partners. DCODE is a European network and PhD Program –under the umbrella of the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN- 2020) within the European Horizon 2020 Framework Program. DCODE introduces a post-disciplinary mode of working called ‘prototeams’: teams of PhD students working in real-world contexts to develop and prototype future professional design roles and practices, including the scientific knowledge needed to support them. These ‘prototeams’ are formed by different Early Stage Researchers (ESRs) working on one of the five main areas. Abstract [en] Developing and designing machine learning systems requires multidisciplinary teams working together across the machine learning pipeline. However, information and values of different disciplines can be amplified or diminished depending on their positioning within that pipeline. In our prototeam, we chose to investigate this phenomenon and “plumb” the machine learning pipeline. We developed a workshop where the constraints and contextual conditionings surface during the decision-making process in which AI systems are developed. Through a gamified approach, our participants acted out a fictional machine learning design scenario for an image classification system and reflected on how values are embedded and ‘lost’ in industry practices.