09-15, 09:00–09:50 (Europe/Amsterdam), Foo (main)
Many of us have heard terms like Data for Good, Ethical Machine Learning, Human-Centric Product Design, but those words also bring forward questions -- if we need "Ethical ML" what is the rest of machine learning? The current conversation around AI Doom paints a picture where AI goes hand-in-hand with dystopian outcomes. In this keynote, we'll explore what AI could look like if at the core, it was led by these ideals. What if distributed, communal machine learning were a central focus? What if privacy and user choice were a part of our everyday machine learning frameworks? What if aid organizations, governments, coalitions helped shape the problems for AI research? Let's ponder these questions and their outcomes together, imagining AI without the potential for dystopia.
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No previous knowledge expected
Katharine Jarmul is a privacy activist and data scientist whose work and research focuses on privacy and security in data science workflows. She recently authored Practical Data Privacy for O'Reilly and works as a Principal Data Scientist at Thoughtworks. Katharine has held numerous leadership and independent contributor roles at large companies and startups in the US and Germany -- implementing data processing and machine learning systems with privacy and security built in and developing forward-looking, privacy-first data strategy.