Explainable AI: How to Navigate the New World of Data Regulation.
Exploring the regulatory risks, ethical conundrums and business opportunities in the increasingly important world of Explainable AI.
With France, Austria, South Africa and more than 50 other countries accelerating efforts to control the digital information produced by their citizens, government agencies and corporations, many are now wondering how this push toward data sovereignty will affect their businesses.
The push is already in full swing, with the number of laws, regulations and government policies requiring digital information to be stored in a specific country more than doubling to 144 from 2017 to 2021. This new environment will require new strategies and approaches in order to not fall foul of the authorities. Fortunately, much of what regulation asks of businesses can be solved by adopting explainability/interpretability within their AI systems.
More broadly known as Explainable Artificial Intelligence (XAI), Explainable AI is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms.
In this conversation, we will explore not only the regulatory risks posed by not adopting Explainable AI but also explore the business opportunities granted when enterprises understand the AI systems they rely upon.
Takeaways you can expect from ‘Explainable AI: How to Navigate the New World of Data Regulation’.
- What is Explainable AI?
- Why should businesses care about whether or not their systems have the ‘black box’ issue.
- How enterprises can enact change and understanding around their AI models.
- The tools that are available in reaching Explainable AI within your organization.
- How this fits into the wider trend of data sovereignty seen over the past few years.
Speaker
Mr Eugenio Zuccarelli
Data Science Leader for Fortune 100 | Forbes 30 Under 30 | Fulbright Scholar | TEDx Speaker | MIT, Harvard, Imperial College
CVS
Eugenio is a Business-Focused Data Science Leader, driving the innovation efforts for several Fortune 500 companies across multiple industries, including Healthcare (CVS Health), Automotive (BMW) and Finance (Morningstar). He is a Forbes 30 Under 30, a Fulbright Scholarship recipient and studied across MIT, Harvard and Imperial College. Currently, he leads the innovation efforts for complex chronic care at CVS Health, the #1 Healthcare company in the world and a Fortune 5 firm.
In addition, he has been working in the Task Force using analytics to fight COVID-19 and develop policy recommendations for The White House and overall finding solutions to fight the COVID-19 pandemic. You can find Eugenio's work across Forbes, The Washington Post, Bloomberg and Financial Times as well as multiple journals and in the App Store. Previously, Eugenio worked as Data Scientist at Dr Foster - Telstra Health, a leading Fortune 500 healthcare analytics firm based in London working closely to the NHS, after having worked as Data Analyst for a fintech startup, Arkera. He obtained a Master of Business Analytics from MIT, a Master of Science in Biomedical Engineering with Neurotechnology from Imperial College London.
While at MIT, he worked as a Researcher at the MIT Operations Research Center and at the MIT Media Lab, while at Imperial College he worked at the Brain & Behaviour Lab under the supervision of Prof. Aldo Faisal, developing state-of-the-art prosthetic technologies as a member of Team Imperial to participate in the first Bionics Olympics, Cybathlon. Previously, he received a Bachelor of Science in Electronic and Information Technology Engineering from the University of Genoa in Italy.
