In July, we held a session discussing data visualization design principles centered around equity and accessibility. We explored how our design decisions for data visualizations could potentially exclude parts of our audiences, shaping who can gain insights from the data and who isn't. We also examined what accessibility means, best practices for inclusive design, and heard from several CTData staff members who have made adjustments to their own work.
Read MoreOur June Community of Practice session was centered around the AISP Toolkit for Centering Racial Equity Throughout Data Integration. We explored how decisions throughout data work, from project design to credit attribution, can either advance equity or reinforce harm.
Read MoreOur May Community of Practice session focused on evaluating generative AI tools with a risk-aware lens, highlighting key considerations like data handling, model transparency, and ethical safeguards. We also took a look at some practical checklists and evaluation rubrics to help guide responsible AI use in the workplace.
Read MoreWhen designing surveys that include LGBTQ+ demographic questions, how do we balance the need for data with respect for privacy and identity? Our March Equity in Data Community of Practice session tackled this challenge by examining real-world examples and developing inclusive, transparent, and trustworthy data collection guidelines.
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