DEI Conference
De-siloing Your Data Strategy For Equity
Session Description:
Humanizing our data operations is possible when the community is collectively pushing for data transparency, making data/AI systems and knowledge workers accountable while exercising our data citizenship and agency.
In this session, participants are set up to clarify the ethical gaps in their data pipelines so that they can develop practical interventions and action step to making data/AI projects more equitable without disrupting your existing data operations and processes.
We’ll unpack how to separate data policies, practices and products within a single department in order to allow for a holistic approach across multiple departments for sustainable equitable data practices.
Then, we’ll specify common criteria that helps and inhibits equity in their data pipelines.
Last, we’ll identify inclusivity-based recommendations to address limitations within existing data operations.
It’s important to hone in on the areas most palpable for impactful change and developing concrete roadmaps to making data operations less harm-inducing. There will be small group activities to help participants build these roadmaps.
Objectives and Key Takeaways:
When a participant leaves this session, they’ll be able to:
- catalog your team’s existing data operations
- identify key markers for ethically weak data operations and standard practices.
- describe strategic analog and algorithmic interventions to mitigate ethically weak data efforts
Audience:
Audience Knowledge and Experience:
Additional Materials
Guest Speakers
Brandeis Marshall
Founder and CEO of DataedX Group, LLC
Founder and CEO of DataedX Group, LLC, providing learning and development training to help educators, scholars and practitioners humanize their data practices. She is the author of Data Conscience: Algorithmic Siege on our Humanity (Wiley, 2022). Marshall speaks, writes and consults on how to move slower and build better human-centered tech by highlighting the impact of data practices on technology and society. She has been a Stanford PACS Practitioner Fellow and Partner Research Fellow at Siegel Family Endowment. Marshall has served as a tenure-track faculty member at Purdue University and then Spelman College. Her research work in data education and data science has been supported by the National Science Foundation and philanthropy organizations. She holds a Ph.D. and Master of Science in Computer Science from Rensselaer Polytechnic Institute and a Bachelor of Science in Computer Science from the University of Rochester.
