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itle: Assessing Human Need at Scale


  • We tend to measure human progress with financial numbers that are decoupled from the actual well-being of our population. Optimizing measures like GDP has led to over-consumption and production without regard for need satisfaction. A variety of new measures (such as gross national happiness) have been developed in order to address this, but they are inherently composed of arbitrary trade-offs and lack a participatory nature that most theories of well-being show to be necessary. To this end, I propose using intra-individual networks of needs and satisfiers (rather than single numbers) to represent the needs of an individual, and, when aggregated, an entire population. In the proposed community informatics platform, individuals construct their own need network through reflection, experience sampling, and/or by labeling existing data (such as financial statements and calendar entries). Once constructed, these networks can be aggregated at arbitrary scales to construct multi-layer networks representing entire populations, without losing details of specific unmet needs. Leaders can then use these network representations to better assess and solve challenging social problems, while individuals can further develop need-literacy to improve well-being.
  • ICS program: Dual PhD
  • Advisor: Stephen Voida
  • Home degree department: Computer Science
  • Name of research lab: Too Much Information Lab