Accurate data annotation is essential to successfully implementing machine learning (ML) for regulatory compliance. Annotations allow organizations to train supervised ML algorithms and to adapt and audit the software they buy. The lack of annotation tools focused on regulatory data is slowing the adoption of established ML methodologies and process models, such as CRISP-DM, in various legal domains, including in regulatory compliance. This article introduces Ant, an open-source annotation software for regulatory compliance. Ant is designed to adapt to complex organizational (...) processes and enable compliance experts to be in control of ML projects. By drawing on Business Process Modeling (BPM), we show that Ant can contribute to lift major technical bottlenecks to effectively implement regulatory compliance through software, such as the access to multiple sources of heterogeneous data and the integration of process complexities in the ML pipeline. We provide empirical data to validate the performance of Ant, illustrate its potential to speed up the adoption of ML in regulatory compliance, and highlight its limitations. (shrink)

In this philosophical paper, I discuss and illustrate the necessary three ingredients that together could allow a collective phenomenon to be labelled as “emergent.” First, the phenomenon, as usual, requires a group of natural objects entering in a non-linear relationship and potentially entailing the existence of various semantic descriptions depending on the human scale of observation. Second, this phenomenon has to be observed by a mechanical observer instead of a human one, which has the natural capacity for temporal or spatial (...) integration, or both. Finally, for this natural observer to detect and select the collective phenomenon, it needs to do so on account of the adaptive advantage this phenomenon is responsible for. The necessity for such a teleological characterization and the presence of natural selection drive us to defend, with many authors, the idea that emergent phenomena should belong only to biology. Following a brief philosophical plea, we present a simple and illustrative computer thought experiment in which a society of agents evolves a stigmergic collective behavior as an outcome of its greater adaptive value. The three ingredients are illustrated and discussed within this experimental context. Such an inclusion of the mechanical observer and the natural selection to which this phenomenon is submitted should underlie the necessary de-subjectivation that strengthens any scientific endeavor. I shall finally show why the short paths taken by ant colonies, the collective flying of birds and the maximum consumption of nutrients by a cellular metabolism are strongly emergent. (shrink)