Csikszentmihalyi (1999: 314) argues that 'creativity is a process that can be observed only at the intersection where individuals, domains, and fields intersect'. This article discusses the relationship between creativity and interdisciplinarity in science. It is specifically concerned with interdisciplinary collaboration, interrogating the processes that contribute to the collaborative creation of original ideas and the practices that enable creative integration of diverse domains. It draws on results from a novel real-world experiment in which small interdisciplinary groups of graduate students were (...) tasked with producing an innovative scientific research problem and an integrative research proposal. Results show that while bisociative thinking assists in the creation of original research problems, both disciplinary skills and an interdisciplinary disposition are core to the integration of creative research proposals. Extrapolating from the results of this experiment, the article discusses the feasibility of preparing students for such work and the implications for universities and other intellectual centers. (shrink)

In this paper we introduce the overlapping design consensus for the construction of models in design and the related value judgments. The overlapping design consensus is inspired by Rawls’ overlapping consensus. The overlapping design consensus is a well-informed, mutual agreement among all stakeholders based on fairness. Fairness is respected if all stakeholders’ interests are given due and equal attention. For reaching such fair agreement, we apply Rawls’ original position and reflective equilibrium to modeling. We argue that by striving for the (...) original position, stakeholders expel invalid arguments, hierarchies, unwarranted beliefs, and bargaining effects from influencing the consensus. The reflective equilibrium requires that stakeholders’ beliefs cohere with the final agreement and its justification. Therefore, the overlapping design consensus is not only an agreement to decisions, as most other stakeholder approaches, it is also an agreement to their justification and that this justification is consistent with each stakeholders’ beliefs. For supporting fairness, we argue that fairness qualifies as a maxim in modeling. We furthermore distinguish values embedded in a model from values that are implied by its context of application. Finally, we conclude that for reaching an overlapping design consensus communication about properties of and values related to a model is required. (shrink)

The development of computer science has raised ethical concerns regarding the potential negative impacts of machine learning tools on people and society. Some examples are pornographic deepfakes used as weapons of war against women; pattern recognition designed to uncover sexual orientation; and misuse of data and deep learning by private companies to influence democratic elections. We contend that these three examples are cases of automated evil. In this article, we defend that the concept of forbidden knowledge can help to inform (...) a coherent ethical framework in the context of machine learning research. We conclude that restricting generalised access to extensive data and limiting access to ready-to-use codes would mitigate potential harms caused by machine learning tools. In addition, the notions of intersectionality and interdisciplinarity should be systematically introduced in data and computer science research. (shrink)