The “Creativity, Innovation and Artificial Intelligence” topic, “Creativity” in short, is the newest research line of CSL Paris. It started its activities at the end of 2017 and it focuses on the investigation of the processes underlying innovation and human creativity and their interplay with the most recent advances in Artificial Intelligence, Machine Learning and Inference methods. The research, by blending in a unitary interdisciplinary effort three main activities – theoretical modelling, data-science and machine learning, gaming and participation – aims at developing a science of the “new”, focusing on how the “new” emerges in social and technological systems and how humans and machines explore the space of possibilities and find new solutions.
The main Topic includes several specific research lines that can be summarized as follows:
(i) The mathematics of the new: One of the key problems when studying innovation processes is represented by a lack of a suitable mathematical framework to describe the occurrence of events whose existence one did not even previously suspect; this is the so-called problem of ‘unanticipated knowledge’. In this framework, a beautiful notion is that of the “adjacent possible”. Originally introduced in the framework of biology, the adjacent possible metaphor already expanded its scope to include all those things (ideas, linguistic structures, concepts, molecules, genomes, technological artifacts, etc.) that are one step away from what actually exists, and hence can arise from incremental modifications and recombination of existing material. Mathematically, the notion of Adjacent Possible has been formulated by some of the core members of the Creativity topic (see tria_2014). Based on this general formulation extremely challenging problems can be faced, to investigate the topology of the space of possibilities and its dynamical evolution at the individual and collective level. The final goal is that of defining a coherent and self-consistent mathematical formulation that, beyond explaining stylized facts (statistical laws, correlation and triggering effects, etc.), is able to cast concrete predictions to be grounded on actual data.
(ii) Unfolding creativity processes: This research line is focusing on unveiling the strategies of exploration of the adjacent possible in many different systems (social, biological, technological). The goal is pursued through a data-science and machine-learning approach to datasets mirroring the emergence of novelties in very different kind of systems. This approach is paralleled by the realization of actual experiments involving people, both through online gaming and open events (see for instance: www.kreyon.net/kreyonDays) to engage people in activities that challenge them to explore their adjacent possible and come up with new ideas, recombining existing ideas, effectively triggering some evolutionary dynamics of novelties (videos of several activities are available here: https://goo.gl/Ejdy14). A special attention is devoted to the way in which machines and artificial agents are able to explore their adjacent possible and overcome the problem of the unanticipated knowledge.
(iii) Platforms for a sustainable world: The intrinsic complexity of the emerging challenges human beings collectively face requires a deep comprehension of the underlying phenomena in order to plan effective strategies and sustainable solutions: from the planning of urban infrastructures to containment strategies for pandemics, from the impact of political campaigns to measures against information pollution and misinformation. In all these cases, decision-making processes have to be supported with meaningful representations of the present situations along with accurate simulation engines to generate and evaluate future scenarios. Instrumental to all this is the possibility to gather and analyze huge amounts of relevant data and visualize them in a meaningful way also for an audience without technical or scientific expertise. Understanding the present through data is often not enough and the impact of specific decisions and solutions can be correctly assessed only when projected into the future. Hence the need of tools allowing for a realistic forecast of how a change in the current conditions will affect and modify the future scenario. In short scenario simulators and decision support tools. In this framework CSL Paris is launching a new research direction aimed at developing effective infrastructures merging the science of data with the development of highly predictive models, to come up with engaging and meaningful visualizations and friendly scenario simulation engines.
Interactions with other Topics
Creativity-Language: The topic of Creativity is strongly intertwined with the topic of Language. Language is in fact one of the most natural playground to investigate creativity and innovation processes for several reasons and CSL Paris has a strong interest in Language studies and its Language team is widely known for its seminal contributions to the developments of Construction Grammars. In addition, Language features a vast ecosystem of innovation phenomena and creative exploits. Not to mention the huge amount of language-related data already available, that are a strategic starting point for any scientific investigation, and the vast corpus of both theoretical and computer science tools for natural language processing.
Joint projects: Anticipation processes.
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