Modelling and knowledge transfer in complexity science.

I analyse the construction and transfer of models in complexity science. Thereby, I introduce a distinction between (i) vertical model construction, which is based on knowledge about a specific target system, (ii) horizontal model construction, which is based on the alteration of an existing model and therefore does not require any references to a specific target system; and (iii) the transfer of models, which consists of the assignment of an existing model to a new target system. I argue that, in complexity science, all three of those modelling activities take place. Furthermore, I show that these activities can be divided into two general categories: (i) the creation of a repository of models without specific target systems, which have been created by large-scale horizontal construction; and (ii) the transfer of these models to particular target systems in the natural sciences, which can also be followed by an extension of the transferred model through vertical construction of adaptions and additions to its dynamics. I then argue that this interplay of different modelling activities in complexity science provides a mechanism for the transfer of knowledge between different scientific fields. It is also crucial to the interdisciplinary nature of complexity science.

A trust based framework for the envelopment of medical AI.

The importance of a trust-based relationship between patients and medical professionals has been recognized as one of the most important predictors of treatment success and patients' satisfaction. We have developed a novel legal, social and regulatory envelopment of medical AI that is explicitly based on the preservation of trust between patients and medical professionals. We require that the envelopment fosters reliance on the medical AI by both patients and medical professionals. Focusing on this triangle of desirable attitudes allows us to develop eight envelopment components that will support, strengthen and preserve these attitudes. We then demonstrate how each envelopment component can be enacted during different stages of the systems development life cycle and demonstrate that this requires the involvement of medical professionals and patients at the earliest stages of the life cycle. Therefore, this framework requires medical AI start-ups to cooperate with medical professionals and patients throughout.