How to build an Ethical Data Science System without losing money?

Inspired by Google DeepMind's team, Shakir Mohamed, William Isaac, and Implikit's founder Marie-Therese Png article, Decolonial AI, my experience with Data Science and readings, I'll try to propose a production strategy that compensates the lack of scalable ethics in Data Science Systems and make it embedded since the beginning of the development, saving the cost of change later. The main problem that I'll approach might be kind of obvious. Data Science does not implement efficient and scalable Ethical guidelines. Data Science is not Customer Centric, yet. The reason, I'll detail along the article is: Implicitly, our work might be motivated by solely on optimizing revenue, costs, human and non-human operational resources under the facade of enriching Customer Experience when we are launching Data-based products. This is as complicated to say as is it to tackle.