Clara is a director at IEEE, the world's largest technical organization  founded by Tesla and Edison more than 100 years ago. Today, she is working on developing an ethically aligned design framework to help companies develop safe and effective AI systems. Listen to the 20th episode of the Data Democratization Podcast to find out what the difference is between standards and certifications, what the role of values is in ethically aligned design and what synthetic data and fresh Alpine spring water have in common! 

In this episode, Alexandra Ebert, MOSTLY AI's chief trust officer will be talking to one of the founders and the chief data scientist of MOSTLY AI. If you are looking to get a behind-the-scenes view of how data privacy is implemented in practice, you are in the right place! You won't need a math Ph.D. to finally understand how privacy is measured and what is takes to protect personal data. Klaudius is also a huge fan of the concept of open data and talks about how synthetic data is the way forward for realizing the potential of open data sharing for research and innovation. 

Lisa Palmer is the chief technical advisor of Splunk, the popular data platform designed to remove barriers between data and action. Besides working for Splunk, she is a university professor, a podcast host, and an author. She spent years at Microsoft, Gartner, and Teradata, building up her unique perspective on data and technology-related business opportunities. In this episode, Lisa shares her most exciting insights and data stories around tackling real-life problems with data, including wildfires and F1 racing, how privacy-enhancing technologies like homomorphic encryption and synthetic data can be used for social good, why we need truly complete datasets to address biases, the role synthetic data plays in ethical AI and bias mitigation, how to increase diversity, especially in tech and how to think about data opportunities in times of disruption and opportunity. Check out the transcript for this episode and all previous episodes of the Data Democratization Podcast at our website! 

In the latest episode of the Data Democratization Podcast, Jim Hu, MOSTLY AI's Data Engineer, talks about the most exciting synthetic data engineering he has been busy doing. Synthetic data is quickly becoming a must-have engineering tool across industries, with new use cases emerging every day. If you want to learn how to leverage synthetic data in insurance and banking, listen to the episode! Learn to maximize synthetic data's business impact:how to increase profit margins in insurance using synthetic datahow to maximize the lifetime revenue of a loanhow to detect suspicious transactions and prevent fraudhow to estimate credit risk using machine learninghow to unlock transaction data for AI trainingwhy synthetic data is superior to legacy data anonymization techniquesoptimize software testing processescreate personalized banking experiences

Claudette McGowan is an award-winning technology leader with a real passion for cybersecurity. In this episode of the Data Democratization Podcast, she shares her personal journey to the cybersecurity field as well as her perspective on the current state of cybersecurity. Listen to the episode to learn more about how the pandemic changed the threat landscape, how companies should prepare for cyberattacks, how data should be managed for maximum security, what is a zero-trust approach, the importance of privacy-safe data sharing, why data literacy is important, why cybersecurity is an amazing career option and where you can learn about cybersecurity. Also, don't forget to check out Claudette's podcast, the Cyber Suite, to elevate your everyday cyber literacy!  

Scott, the Data Whisperer, knows a thing or two about proper data management. If you are in the business of making large scale data projects happen, make sure you listen to this episode and learn about creating visibility and getting executive buy-in for your data projects. Find out how to set your data projects up for success from the beginning through master data, metadata, data governance and data stewardship and get great tips on how to tell great data stories. 

Amir Tabakovic has lots of experience in developing banking products, and as a chairman of the AI and Data Privacy Experts Group at Mobey Forum, he has a very good overview of privacy best practices and the most common mistakes in the banking industry. Listen to this episode to learn about how to develop customer-centric banking products and take them to market? How can traditional banks compete with neobanks?  What is privacy-enhancing technology? How should banks leverage privacy tech for success? Which privacy technology to choose when? How to make privacy-by-design happen from an organizational point of view? What is the difference between pseudonymization and anonymization? What's the problem with legacy anonymization technologies? Amir and his team at Mobey Forum recently published a report entitled The Digital Banking Blindspot: Emerging Privacy Enhancing Technologies. Download the report if you would like to get a detailed overview of how privacy tech is changing the banking industry!To learn more about synthetic data, visit MOSTLY AI's Synthetic Data Blog! 

Behrang Raji is a data privacy officer for the Hamburg Commissioner for Data Protection and Freedom of Information. He is right where legislation happens, knows what drives regulators and has a pretty good understanding of trends and the larger regulatory landscape. Listen to this episode if you are curious about the upcoming European AI regulations, fairness in law and how synthetic data helps fix biases and test AI systems, the most common data anonymization mistakes, data anonymization standards and compliance strategies that really work. 

NVIDIA is famous for its graphics cards, but NVIDIA's story is so much bigger than this. Their graphics cards have been used to accelerate AI and data science, and now they offer a whole ecosystem of services and tools for companies ready to make AI happen. Listen to the episode to learn about the top AI use cases in finance and insurance and how to make those happen. Questions you will get answers for in this episode: How to implement AI successfully? How does NVIDIA help democratize AI? How to automate explainability? How is synthetic data used for evaluating and supervising AI models? What does the future of AI hold for financial institutions? 

Nancy Nemes is an AI expert with 20 years of hand-on experience in implementing frameworks as a leader at Microsoft and Google. She is the founder of HumanAIze, an organization that aims to make AI more inclusive. If you are looking for some practical advice on how to implement responsible AI at the moment, then look no more – In this episode you will learn about all the necessary steps to perform ethical AI. What are the most important ethical AI best practices? What does the regulation aspect mean for the financial sector? What kind of skills are necessary to adapt to this AI-driven environment? How to identify the right metrics for understanding privacy and fairness when developing AI systems? Which kind of privacy enhancing technologies should you implement? Who are the experts that you should gather? Learn the answers to these by following the best, expert, practices!