Mo McElaney
- talk
Digital Discrimination: Cognitive Bias in Machine Learning (and LLMs!)
Learn from Mo"We have entered the age of automation, overconfident yet underprepared. If we fail to make ethical and inclusive artificial intelligence, we risk losing gains in civil rights and gender equity under the guise of machine neutrality"
On a global scale we are growing numb to stories in the news about machine learning algorithms causing real-world harm. People's lives and livelihood are affected by the decisions made by machines. Learn about how bias can take root in machine learning algorithms, how the rise of foundation models and Large Language Models (LLMs) have impacted this phenomenon, and ways to overcome it. From the power of open source, to tools built to detect and remove bias in machine learning models, there is a vibrant ecosystem of contributors who are working to build a digital future that is inclusive and fair. Now you can become part of the solution.
Track Sponsors
Originally presented in the Responsible AI: Safety, Security, Guardrails and Governance track
About Mo McElaney
Mo McElaney (pronouns they/them) is Lead of AI Open Source Developer Programs at IBM. They are on the Tutorial selection committee for PyCon US and a contributor to the Hippocratic License through Ethical Source. From 2012-2018 they ran a non-profit teaching people to code using collaborative curriculum open sourced on GitHub. Mo is also on the board of the Vermont Technology Alliance and lives in frosty Vermont with their family, cats, and many plants.