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Explaining and preventing algorithmic bias with a panel of experts

Algorithmic bias can affect us everywhere, from minor trivia such as our social media feeds to critical decisions where bias can wreak havoc with a person's life dream or a company's survival. Sources of algorithmic bias are manifold – some, such as biased data and overfitting, sit squarely in the domain of data scientists themselves, while others only can be tackled by the business users and government agencies who use algorithms, be it through carefully crafted experiments that generate truly unbiased data or through deliberate tweaks of the decision-making process.

In this practical and interactive talk, data scientist and psychologist Tobias Baer (also author of 'Algorithmic Bias') put algorithmic bias in the bigger context of human decision biases and engaged the audience (through quizzes and Q&A) in a discussion about both psychological and statistical sources of bias and what business users and data scientists can do respectively to manage and prevent algorithmic bias.

The evening concluded with a panel discussion about how regulators should think about algorithmic bias. The panel consisted of Tobias Baer, Maria Axente (Responsible AI and AI for Good Lead at PwC), Orlando Machado (Chief Data Scientist at Aviva), Clemi Collett (Cambridge based researcher), and will be moderated by Simone Schnall, Director of the Cambridge Body, Mind and Behaviour Laboratory and a Fellow of Jesus College. 

After the event, Clemi Collett said: 'Tobias' new book is a timely, thorough and necessary overview of algorithmic bias which everyone needs to read! This was made even more clear by his brilliant and engaging talk. Thank you to the brilliant audience and the wonderful fellow panellists/hosts for making the discussion so vibrant. It was a joy to be a part of such a successful evening'.

Tobias said: "The discussion was a unique experience because both the panellists and the audience brought to bear such a broad range of perspectives - questions touched upon everything from philosophy and ethics to the most cutting edge statistical techniques and practical business issues."

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Tobias Baer

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