AI Bias, Data Quality, and the Road to Ethical AI: A conversation with Matt Maccaux, Head of Customer Engineering at Google

In this episode of AI Realized, Christina Ellwood interviews Matt Maccaux, the head of customer engineering at Google Cloud, to discuss the challenges and practical advice for AI adoption in enterprises and digital native companies. The conversation covers the ethical use of data, focusing on reducing bias and using synthetic data. Maccaux emphasizes the importance of understanding and improving existing data sets and discusses the conditions under which synthetic data is useful. He highlights barriers to AI deployment, such as lack of executive sign-off and budget constraints, and offers advice for enterprises to start with productivity use cases to build a business case. For digital natives, he notes their faster pace due to less technical debt but acknowledges budget constraints. Finally, Maccaux advises executives to engage with peers across different industries and to learn from both traditional enterprises and digital natives to balance innovation with practical challenges.00:00 Introduction to AI Realized Podcast01:19 Ethical Use of Data in AI03:46 Synthetic Data and Bias in AI06:43 Challenges in AI Deployment15:15 Guidance for Enterprise Executives16:49 Learning and Networking Resources18:19 Final Thoughts and Takeaways

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