Data Skills Survey

The scale and impact of data-driven practices using automation technologies have caused a surge of high-demand, high-salary data roles needing specific data skills in every sector. Yet, the access to developing these skills in our society remains elusive to many communities, especially Black women. Working with data is fast becoming an essential skill. In our efforts to close the gap for Black women in this industry, DataedX Group designed this survey to capture data-related experiences in the workplace. The goal however is to empower job seekers, career changers, along with new and seasoned data workers alike with information about the most sought after skills and tools in the increasingly lucrative job market. We shed light related to WHO is doing WHAT with DATA in the workplace by identity background, education and opportunity and job titles and responsibilities. Download our survey report and check out the findings. 

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Trustworthy AI in Law and Society

The Institute for Trustworthy AI in Law & Society (TRAILS) is the first organization to integrate artificial intelligence participation, technology and governance during the design, development, deployment and oversight of AI systems. We investigate what trust in AI looks like, how to create technical AI solutions that build trust, and which policy models are effective in sustaining trust. In addition to UMD, GW and Morgan State, other participation in TRAILS comes from Cornell University, and private sector organizations like the DataedX Group, Planet Word, Arthur AI, Checkstep, FinRegLab and Techstars.

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Atlanta Interdisciplinary AI (AIAI) Network

The AIAI Network believes that an equitable, ethical, and justice-oriented approach to AI is possible when humanistic ways of thinking come together with technical knowledge and community expertise. It's a collaboration initiative with founding member organizations Emory University, Clark Atlanta University, Georgia Institute of Technology, and DataedX Group. We aim to bring the city of Atlanta, with its historical place in the civil rights movement, to current conversations about the biases embedded in our AI systems.

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