What This proposal aims to create an extensive, interdisciplinary effort combining natural, social, cognitive, and computer science to address three fundamental modern challenges: Increasing the understanding of human behavior. Developing tools for systematic mapping of cognitive and psychological demographics and individualized profiling as a step towards population-scale benchmarking and individualized mental health diagnostics. These will allow us to lay the foundations for future algorithms using machine learning to build upon uniquely human search characteristics. Why The impressive advances within artificial intelligence (AI) and machine learning (ML) are largely due to two distinct novelties: increasing computational power and the increasing availability of massive labeled datasets. Despite their success in specialized applications, they also clearly demonstrate that future AI systems will continue to rely on human insight and intuition, or even interoperate with human intelligence. Humans sometimes exhibit the ability to solve high dimensional, complex problems relying on the ability to extrapolate from sparse data, by applying domain-specific heuristics in the form of ‘intuition’. Recognizing this, we explore the potential of citizen science to better understand human cognitive processes and design human-AI systems to tackle complex challenges. How Our unique approach is to exploit three novel uses of the citizen science: ● We will setup a novel infrastructure allowing for simple and flexible initialization of online, large-scale social science experiments (social science supercollider).● We will create a suite of simple online games, which can be used as an orthogonal basis from which individual player cognitive characteristics can be extracted.● We will utilize the massive amounts of human player data generated in natural science research games to train machine learning algorithms to tackle various problems such as search and optimization. SSR One of the grand challenges of the 21st century is the growing divide between the general population and the knowledge generating institutions which facilitated by the social media companies has led to the existing societal polarization and “fake news” crisis. One acknowledged way to foster critical thinking is through citizen science involving the general public directly in the knowledge generation process. By reaching out to tens of thousands of participants, this project aims to achieve exactly that. At the same time, the project aims to generate general insights about human nature that will help shape a hybrid intelligence future in which the main emphasis is on technology augmenting the intrinisic skills of humans.