Openness and collaboration in scientific research are attracting increasing attention from scholars and practitioners alike. However, a common understanding of these phenomena is hindered by disciplinary boundaries and disconnected research streams. We link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. This framework captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. Moreover, it elucidates individual-, team-, organisation-, field-, and society-level factors shaping OIS practices. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners.

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Video games are played by over 2 billion people spread across the world population, with both children and adults participating. Games have gained popularity as an avenue for studying cognition. We believe that studying cognition using games can generate progress in psychology and in neuroscience similar to the one that has occurred in artificial intelligence research over the past decades. Using games to understand the mind enables researchers to scale up theories of cognition to more complex settings, reverse-engineer human inductive biases, create experiments that participants want to take part in, and study learning over long time horizons. We describe both the advantages and drawbacks of using games relative to standard lab-based experiments, and lay out a set of recommendations on how to gain the most from using games to study cognition. We hope that this article will lead to a wider use of games as experimental paradigms, elevating the complexity, robustness, and external validity of research on the mind.

Artificial Intelligence (AI) can augment and sometimes even replace human cognition. Inspired by efforts to value human agency alongside productivity, we discuss and categorize the potential of solving Citizen Science (CS) tasks with Hybrid Intelligence (HI), a synergetic mixture of human and artificial intelligence. Due to the unique participant-centered set of values and the abundance of tasks drawing upon both human common sense and complex 21st century skills, we believe that the field of CS offers an invaluable testbed for the development of human-centered AI including HI, while also benefiting CS. In order to investigate this potential, we first relate CS to adjacent computational disciplines. Then, we demonstrate that CS projects can be grouped according to their potential for HI-enhancement by examining two key dimensions: the level of digitization and the amount of knowledge or experience required for participation. Finally, we propose a framework for types of human-AI interaction in CS based on established criteria of HI. This “HI lens” provides the CS community with an overview of ways to utilize the combination of AI and human intelligence in their projects. For AI researchers, this work highlights the opportunity CS presents to engage with real-world data sets and explore new AI methods and applications.

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