Eliminating AI Bias Through Inclusive Data Annotation with Andrea Brown

Open||Source||Data

Learn how Andrea Brown, CEO of Reliabl, is revolutionizing AI by ensuring diverse communities are represented in data annotation. Discover how this approach not only reduces bias but also improves algorithmic performance. Andrea shares insights from her journey as an entrepreneur and AI researcher.

Episode timestamps

(02:22) Andrea's Career Journey and Experience with Open Source (Adobe, Macromedia, and Alteryx)

(11:59) Origins of Alteryx's AI and ML Capabilities / Challenges of Data Annotation and Bias in AI

(19:00) Data Transparency & Agency

(26:05) Ethical Data Practices

(31:00) Open Source Inclusion Algorithms

(38:20) Translating AI Governance Policies into Technical Controls

(39:00) Future Outlook for AI and ML

(42:34) Impact of Diversity Data and Inclusion in Open Source

Quotes

Andrea Brown

"If we get more of this with data transparency, if we're able to include more inputs from marginalized communities into open source data sets, into open source algorithms, then these smaller platforms that maybe can't pay for a custom algorithm can use an algorithm without having to sacrifice inclusion."

Charna Parkey

“I think if we lift every single platform up, then we'll advance all of the state of the art and I'm excited for that to happen."

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