This paper considers the question: In what ways can artificial intelligence assist with interdisciplinary research for addressing complex societal problems and advancing the social good? Problems such as environmental protection, public health, and emerging technology governance do not fit neatly within traditional academic disciplines and therefore require an interdisciplinary approach. However, interdisciplinary research poses large cognitive challenges for human researchers that go beyond the substantial challenges of narrow disciplinary research. The challenges include epistemic divides between disciplines, the massive bodies of (...) relevant literature, the peer review of work that integrates an eclectic mix of topics, and the transfer of interdisciplinary research insights from one problem to another. Artificial interdisciplinarity already helps with these challenges via search engines, recommendation engines, and automated content analysis. Future “strong artificial interdisciplinarity” based on human-level artificial general intelligence could excel at interdisciplinary research, but it may take a long time to develop and could pose major safety and ethical issues. Therefore, there is an important role for intermediate-term artificial interdisciplinarity systems that could make major contributions to addressing societal problems without the concerns associated with artificial general intelligence. (shrink)

In science policy, it is generally acknowledged that science-based problem-solving requires interdisciplinary research. For example, policy makers invest in funding programs such as Horizon 2020 that aim to stimulate interdisciplinary research. Yet the epistemological processes that lead to effective interdisciplinary research are poorly understood. This article aims at an epistemology for interdisciplinary research, in particular, IDR for solving ‘real-world’ problems. Focus is on the question why researchers experience cognitive and epistemic difficulties in conducting IDR. Based on a study of educational (...) literature it is concluded that higher-education is missing clear ideas on the epistemology of IDR, and as a consequence, on how to teach it. It is conjectured that the lack of philosophical interest in the epistemology of IDR is due to a philosophical paradigm of science, which prevents recognizing severe epistemological challenges of IDR, both in the philosophy of science as well as in science education and research. The proposed alternative philosophical paradigm entails alternative philosophical presuppositions regarding aspects such as the aim of science, the character of knowledge, the epistemic and pragmatic criteria for accepting knowledge, and the role of technological instruments. This alternative philosophical paradigm assume the production of knowledge for epistemic functions as the aim of science, and interprets ‘knowledge’ as epistemic tools that must allow for conducting epistemic tasks by epistemic agents, rather than interpreting knowledge as representations that objectively represent aspects of the world independent of the way in which it was constructed. The engineering paradigm of science involves that knowledge is indelibly shaped by how it is constructed. Additionally, the way in which scientific disciplines construct knowledge is guided by the specificities of the discipline, which can be analyzed in terms of disciplinary perspectives. This implies that knowledge and the epistemic uses of knowledge cannot be understood without at least some understanding of how the knowledge is constructed. Accordingly, scientific researchers need so-called metacognitive scaffolds to assist in analyzing and reconstructing how ‘knowledge’ is constructed and how different disciplines do this differently. In an engineering paradigm of science, these metacognitive scaffolds can also be interpreted as epistemic tools, but in this case as tools that guide, enable and constrain analyzing and articulating how knowledge is produced. In interdisciplinary research, metacognitive scaffolds assist interdisciplinary communication aiming to analyze and articulate how the discipline constructs knowledge. (shrink)

When introduced around 1925, interdisciplinarity, grounded in the notion of the unity of knowledge, was meant to reconnect the fragmented and specialized disciplines of academia. However, interdisciplinary research became more and more challenging as the plurality and heterogeneity of disciplinary perspectives and insights increased. Insisting on this divergence and diversity, Julie Thompson Klein has nonetheless contributed in important ways to convergence in interdisciplinarity with her work on the process of integration as interdisciplinarity's defining feature. Of course, she is aware that (...) the increasing inclusion of extra-academic stakeholders in transdisciplinary research constitutes a fundamental challenge to integrative interdisciplinarity. This challenge implies that next to academic contributions, experiential knowledge, interests, and norms must be recognized as valuable to the process, and stakeholder expectations of applicable results must be met. Exploring the future by extending this crucial development further, this article focuses on the actionability of knowledge as an additional criterion for effective interdisciplinarity and transdisciplinarity, as it is in Action Research. With action options for stakeholders being an important goal for such research, it is argued that joint deliberation about these options must be part of the process, aiming for reflective equilibrium. At the same time, an important role for imagination is defended, enabling adequate consideration of action options with their ramifications and implications. The future of interdisciplinarity, it is concluded, will entail an important role for the actionability criterion and for the related role of imagination of potential outcomes, much greater roles than these now have. (shrink)

Introduction: Interdisciplinary, transdisciplinary and action research of a city in lockdown. As we write this chapter, most cities across the world are subject to a similar set of measures due to the spread of COVID-19 coronavirus, which is now a global pandemic. Independent of city size, location, or history, an observer would note that almost all cities have now ground to a halt, with their citizens being confined to their private dwellings, social and public gatherings being almost entirely forbidden, and (...) commercial areas being nearly devoid of visitors. Striking as these apparent similarities are, closer scrutiny would reveal important differences between cities and within cities – differences that can be highly relevant to consider when scholars are assessing the responses of cities to this pandemic or trying to predict the consequences of those responses. For example, the public health systems in some cities are better prepared than in others for coping with the increasing number of patients in life threatening conditions. Multigenerational households, which are associated with a greater risk for elderly members, are not equally common in all cities. Tourist destinations have taken a more severe economic hit from the lockdown than those cities which are economically less dependent upon this particular source of income. Communal celebrations in one city will result in a higher number of contagions and perhaps even deaths in this situation, whereas that same social fabric generally does contribute to a population’s health. The pandemic has also had unprecedented effects on differences and inequalities within cities. In cities in the United States, neighborhoods primarily inhabited by African Americans have been disproportionately affected by COVID-19 due to living and health conditions, yet also due to the fact they disproportionately perform vital jobs. Parks and green spaces are crowded, while city centers like Amsterdam’s Red Light District have suddenly lost the bustle of tourism, providing opportunities for citizens to reoccupy scarce public spaces and reclaim ownership. Clearly, such differences between cities are in many cases only discernible to the eye of an expert, possessing the necessary background knowledge to interpret the perceptible local changes caused by the global pandemic. Typically, drawing upon his or her disciplinary training, the expert also knows how to further probe the impact of the pandemic in an appropriate way. However, compared to the usual application of expertise, this crisis situation might, in an unusual way, test even experts. For the pandemic has created a unique situation, imposing unfamiliar constraints on the health, economic, social, and other conditions of cities, constraints that interact in sometimes unexpected ways with each other. Such interactions in turn force experts to collaborate across the boundaries commonly associated with disciplines, their concepts, theories, methods, and assumptions (Klein, 1996). These brief observations of how a virus pandemic can have differential impacts upon various cities, and what this exceptional situation might mean for the application of city methods, allow us to draw a few consequences for the current context of this chapter on interdisciplinary and transdisciplinary research. First, whenever we are investigating a complex and dynamic phenomenon it is by no means easy to determine which disciplinary perspectives are required to do justice to it. Indeed, the choice of useful disciplines can only be made after an initial overview of the situation and a preliminary selection of what appear to be the most important features of the situation. Relevance is key in guiding this selection process and scholars must remain open to the possibility that they may need to revise their earlier assessments of what is relevant and what is not. Second, if scholars from different disciplines were to study different features of a city in isolation, their ‘multidisciplinary’ account would miss important dynamic and complex interactions, such as those between a city’s demographics and geographical situation, its governance and economy. In other words, it is the integration of the perspectives of different disciplines that is crucial, as only then are such interactions taken into account. Indeed, this integration between disciplinary perspectives is what distinguishes an interdisciplinary from a multidisciplinary account. Thirdly, in addition to checking the relevance of disciplines and aiming for their integration, the outcome of interdisciplinary and transdisciplinary research has typically limited generalizability. Since a city is sensitive to a multitude of internal and external dynamical factors, in ways that partly rest upon its socio-cultural history, its investigation will often have the nature of a case study rather than be capable of leading to law-like insights (Krohn, 2010; Menken & Keestra, 2016). As can be seen from these three characteristics of ascertaining the relevance of different disciplinary contributions, the challenge of their integration, and the limited generalizability of their results owing to the specificity of interdisciplinary (ID) and transdisciplinary (TD) research, such research into ‘real world problems’ is clearly distinct from most monodisciplinary research. A consequence of this distinction is the absence of a general ID/TD methodology that can guide specific case studies. By contrast, the collaboration implied in such research requires researchers – and stakeholders, if they are involved – to reflect upon their potential contribution and the implicit assumptions associated with that. We will elaborate on this in the next section. Next, we offer several typologies of integration that urban scholars could employ for their research projects, after which we will offer a few brief analyses of initial collaborations of urban research. Finally, we discuss in more detail the process of the interdisciplinary research project. This will include a brief reflection upon the decision-making process that is implied in such projects. In sum, we aim to provide some guidance in conducting an ID/TD project, albeit not in the form of a definite methodology. (shrink)

Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition of a set (...) of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article. (shrink)