Building Unbiased Machine Learning Systems with Elixir and Erlang

Rashmi Nagpal’s presentation discusses the role of Elixir and Erlang in creating fair machine learning systems amidst the challenges of algorithmic bias. The talk emphasizes the necessity of fairness in AI, citing Martin Luther King Jr.'s philosophy on doing what is right. It covers the dangers of bias in AI and machine learning, with examples highlighting how biased training data can lead to unfair outcomes. The speaker also shares strategies for mitigating bias, including the importance of diverse datasets and the application of fairness techniques in model development. Throughout the talk, Nagpal engages the audience with interactive elements and offers insights into the technical aspects of machine learning deployment and testing, urging for responsible practices that involve all stakeholders in the journey toward ethical AI.