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Mapping Digital Infrastructure and AI (MADI)

Helping the Convergent Aeronautics Solutions project leverage cloud automation and AI to better identify transformational solutions to wicked problems facing humanity.

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About NASA

The National Aeronautics and Space Administration (NASA) is an independent agency responsible for the civil space program, aeronautics research, and space research. The Convergent Aeronautics Solutions (CAS) project investigates and invests in "wicked problems" and potential solutions that might have transformational impacts on humanity and the environment through the lens of aviation and aerospace research.

The challenge

How might CAS and NASA use modern NLP and cloud automation to ingest large volumes of unstructure data and understand connections between emerging trends, needs, and technical capabilities across the world?

NASA’s brand is exploration. The goal of the Convergent Aeronautics Solutions (CAS) Project is to foster a culture of innovation within the Aerospace Research Mission Directorate by advancing disruptive system-level concepts and early-stage technologies that have potential for transformational impact.

The entry point of CAS’s investigatory function (known as Mapping) is the survey of emerging trends, capabilities, and human needs. This input data is gathered from a variety of sources including data analytics tools, interviews, news articles, published research, workshops, and lectures. The Mapping team uses collaborative ideation methods to synthesize this input data into future scenarios and to find problem areas, such as healthcare or education, where aviation or the aviation industry may have a broad and highly beneficial impact on society. The Mapping Team facilitates a series of workshops and investigatory processes that engage the broader NASA community, focus on a long-term horizon, and leverage the collective participant wisdom in evaluating threats and opportunities of potential futures. The MADI project aims to use AI and cloud tooling to supplement the human-driven process of mapping and synthesizing the high volume of inputs that CAS collects.