The Mind the Data Gap podcast focuses on modern data practices and their impact on software dev and testing and applications in data science. Together with our guests, some of the greatest minds in the world of data, we deep dive into the most important data trends and topics. Your host is Nicolai Baldin, CEO and Founder of Synthesized. Mind the Data Gap is is the official podcast of Synthesized.io, a development framework that enables any company to optimal datasets for their testing and data science needs.

Mitigating AI Bias and Business Risks: From Theory to Practical Steps

February 09, 2022 00:32:00 61.48 MB Downloads: 0

Ansgar Koene, global AI and ethics regulatory leader at Ernst & Young, joins us on the latest edition of the "Mind the Data Gap" podcast to discuss AI and business risks, and how to define, measure and mitigate such AI related risks. He shared his view on how data plays into this risk and what organizations do to manage this risk. Koene believes we should rethink legislation relating to data collection on gender, for instance, in order to avoid unintentional data bias.

A former research scientist, Mr Koene works with policymakers, regulators and industry leaders among others, to support the trustworthy use of AI for the benefit of people, society and organizations.

Speakers:

Nicolai Baldin, CEO and Founder of Synthesized

Nicolai leads Synthesized’s rapid growth, as a leading provider of DataOps tools for software testing and data science applications, across the UK, Europe and North America. Nicolai is responsible for the direction and product strategy of Synthesized. For over 8 years, Nicolai has designed and delivered complex ML solutions used by top financial and healthcare institutions. He holds a PhD in Machine Learning and Statistics from the University of Cambridge.

Ansgar Koene, Global AI Ethics and Regulatory Leader, Ernst & Young

His current work focuses on the development of design and regulatory tools to maximize the beneficial use of information technologies and minimize negative consequences on people and society.

He has a multi-disciplinary research background, having worked and published on topics ranging from Policy and Governance of Algorithmic Systems (AI), data-privacy, AI Ethics, AI Standards, bio-inspired Robotics, AI and Computational Neuroscience to experimental Human Behavior/Perception studies. He holds an MSc in Electrical Engineering and a PhD in Computational Neuroscience.

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