What is it about?

In the United States, progress towards ending homelessness is assessed by collecting data in information systems. This study brought together individuals involved in homelessness work and those who have experienced homelessness for workshops to discuss the goals and specific approaches for collecting data. Current approaches prioritize data needs to justify the need for continued funding of homelessness services. However, if impact on ending homelessness is to be more fully understood and the needs of individuals actually experiencing homelessness are to be prioritized, information systems must evolve to support more diverse types of data while also protecting individual privacy.

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Why is it important?

While being data-driven is often seen as a positive for society, the reality is that it could be damaging if the data does not accurately represent the problem we think we're examining. While national, state, and municipal-level decisions are based on this homelessness data, the current data stored in databases lack the capacity to show the complete picture of the state of homelessness in the United States. If the goal truly is to end homelessness by collecting data about it, then information systems must be adapted to embrace data that shows more of the context of people experiencing homelessness - while also respecting individual's privacy.

Perspectives

It was extremely important for me to involve the perspectives of people who were currently or had formerly experienced homelessness in this study - especially by engaging them in a conversation with the people who work in, and fund homelessness services. I was honestly surprised that they advocated for additional data collection, but it is important to acknowledge that they only wanted it if it meant being better understood by society more broadly.

Dr. Chris Bopp
Saint Bonaventure University

Read the Original

This page is a summary of: "Showing the Context": A Need for Oligopticonic Information Systems in Homelessness Measurement, Proceedings of the ACM on Human-Computer Interaction, April 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3579622.
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