NSF Convergence Accelerator

I’m delighted to announce that I am part of an interdisciplinary team that has received an NSF award as part of the Convergence Accelerator program.

Here’s the project abstract:

High volume, rapidly changing, diverse information, which often includes misinformation, can easily overwhelm decision makers during a crisis. Decisions made both during and long after a crisis, affect the trust between responsible decision makers and citizens (many from vulnerable populations), who are impacted by those decisions. This project seeks to help decision makers manage information, promoting reliance on authentic knowledge production processes while also reducing the impact of intentional disinformation and unintended misinformation. The project team will develop a suite of prototype tools that bring timely, high-quality integrated content to bear on decision making and governance, as a routine part of operations, and especially during a crisis. Integrated and authenticated content comprising scientific facts and technical information coupled with citizen and stakeholder viewpoints assure the accuracy of safety decisions and the appropriate prioritization of relief efforts. The project team will synthesize convergent expertise across multiple disciplines; engage and build stakeholder communities through partnerships with government and industry to guide tool development; build a prototype tool for authenticating data and managing misinformation; and validate the tool using real world crisis scenarios.

The project team will create use-inspired personalized AI-driven sensemaking prototype tools for decision-makers to comprehend and authenticate dynamic, uncertain, and often contradictory information to facilitate effective decisions during crises. The tools will focus on curation while accounting for source and explainable content credibility. Guidance from community stakeholders obtained using ethnographic methods will ensure that the resulting tools are practical, timely, and relevant for informed decision making. These tools will capitalize on features of the information environment, human cognitive abilities and limitations, and algorithmic approaches to managing information. In particular, content and network analyses can reveal constellations of sources with a higher probability of producing credible information, while knowledge graphs can help surface and organize important materials being shared while facilitating explainability. The project team will also design and develop a microworld environment to examine and improve tool robustness while simultaneously helping to train decision makers in real-world settings such as school districts and public health settings. This project represents a convergence of disciplines spanning expertise in computer science, social sciences, linguistics, network science, public health, cognitive science, operations, and communication that are necessary to achieve its goals. Partnerships between communities, government industry, and academia will ensure the deliverables are responsive to stakeholder needs.

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