Explainability and transparency are often presented as goals like “Don’t be evil.” But really, who wants to be confusing and obfuscating? The challenge is that these goals are often harder to define and deliver when dealing with technology that has black-box tendencies like AI or with data so big our brains can’t see the traps hidden inside.
Jana Eggers explores explainability and transparency as both required and unachievable goals for AI. This talk is designed to give you and your teams the tools to approach the question of transparency and explainability with your use case, data, and algorithm in mind, so you can feel confident that you will build trust with your users and satisfy regulatory concerns.
Jana Eggers is CEO of Nara Logics, a neuroscience-inspired artificial intelligence company providing a platform for recommendations and decision support. A math and computer nerd who took the business path, Jana has had a career that’s taken her from a three-person business to fifty-thousand-plus-person enterprises. She opened the European logistics software offices as part of American Airlines, dove into the internet in ’96 at Lycos, founded Intuit’s corporate Innovation Lab, helped define mass customization at Spreadshirt, and researched conducting polymers at Los Alamos National Laboratory. Her passions are working with teams to define and deliver products customers love, algorithms and their intelligence, and inspiring teams to do more than they thought possible.
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