Equitable Algorithms: Designing AI for Positive Impact
As artificial intelligence (AI) takes over more and more aspects of our work and personal lives, how does it impact the way we and others–especially those from marginalized backgrounds–are treated?
With the rise of large language models (LLMs) trained on highly biased datasets and those writing algorithms lacking the lived experience and formal education to understand how and to what extent their creations are introducing, perpetuating, and exacerbating social and institutional biases, we are at a crossroads.
Join The Mathpath, Aubrey Blanche-Sarellano, for a deep dive into what the potential future of a machine-enabled world can look like, and walk away with practical ideas about how we can ensure that leaning into technology can create a fairer, more equitable future.
Aubrey Blanche-Sarellano is a math nerd and empath who helps organizations build equitable processes, products, experiences, and operations. Her work combines an empathic and intersectional approach with social scientific methods to create meaningful, sustainable change with a focus on environmental, social, and governance and people operations. From fair talent processes and bias-resistant product design to equitable algorithmic design and communications strategy, she helps organizations think holistically about evolving to meet the needs of a rapidly-diversifying and globalizing world.