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Artificial Intelligence (AI) and its relation with societies is increasinglybecoming an interesting object of study from the perspective of sociology andother disciplines. Theories such as the Economy of Conventions (EC) are usuallyapplied in the context of interpersonal relations but there is still a clearlack of studies around how this and other theories can shed light oninteractions between human an autonomous systems. This work is focused intostudying a preliminary step that is a key enabler for the subsequentinteraction between machines and humans: how the processes of researching,designing and developing AI related systems reflect different moral registers,represented by conventions within the EC. Having a better understanding ofthose conventions guiding the advances in AI is considered as the first andrequired advance to understand the conventions afterwards reflected by thoseautonomous systems in the interactions with societies. For this purpose, wedevelop an iterative tool based on active learning to label a data set from thefield of AI and Machine Learning (ML) research and present preliminary resultsof a supervised classifier trained on these conventions. To further demonstratethe feasibility of the approach, the results are contrasted with a classifiertrained on software conventions.

Conflict and Cooperation: AI Research and Development in terms of the Economy of Conventions