Welcome back to season 5 of the Data Democratization Podcast - and our first-ever live studio recording.

In this episode, Alexandra Ebert sits down with Faris Haddad, AWS' Global AI Technical Strategy Lead. Together, they delve into the transformative role of synthetic data in modern enterprises.  

Faris shares his journey into the world of synthetic data, highlighting its evolution from a niche solution to a cornerstone of enterprise data strategy. He discusses the challenges organizations face with data silos, legacy systems, and privacy concerns, and how synthetic data offers a pathway to overcome these hurdles.  

Whether you're grappling with data accessibility issues or exploring innovative ways to leverage your organization's data assets, this episode offers valuable perspectives on integrating synthetic data into your enterprise data strategy. 

AI democratization sounds great in theory, but why do so many enterprises struggle to make it work? In this episode, Ari Kaplan, Head of Tech Evangelism at Databricks, breaks down the biggest roadblocks to scaling AI—and what’s needed to overcome them. From data intelligence and synthetic data to why leading enterprises rely on unified data and analytics Platforms to cut costs, reduce governance complexity, and streamline AI adoption—we explore how organizations can move beyond AI pilot purgatory and use AI to drive tangible impact at scale.

Ari dives into the hard truths about AI implementation, including why companies still face governance hurdles, siloed data, and inefficient infrastructure. Ari and I discuss how organizations can get more value from their data, deploy AI responsibly, and use synthetic data to scale securely.

Plus, Ari shares his personal approach to balancing a global career, thought leadership, and content creation—including how he manages to make time for writing books while advising enterprises worldwide. We also discuss his take on social media strategy, the skills he’s encouraging his kids to develop for an AI-driven world, and the future of work in an era of intelligent automation.

If you care about AI democratization, enterprise AI strategy, and staying ahead of the curve, this is an episode you won’t want to miss!

In this episode, we are joined by our esteemed guest, Dr. Meshari Alwashmi, a prominent Digital Health Scientist whose expertise spans not only extensive research but also a successful track record as a serial entrepreneur and trusted advisor to digital health initiatives.

Prepare to be enlightened as we uncover the latest trends and advancements propelling the digital health industry forward. Discover the remarkable potential for progress and the direction in which this dynamic industry is heading. Moreover, we will delve into the invaluable contributions that synthetic data in healthcare can make to this ongoing revolution.

This episode offers much more than just a glimpse into the future of digital health. Tune in for actionable advice that will guide your organization toward embracing innovation and achieving success in the realm of digital health.

In this episode of the Data Democratization Podcast, host Alexandra Ebert interviews Daniela Pak-Graf, the managing director of Merkur Innovation Lab — the innovation arm of Merkur Insurance. Daniela shares her tips and best practices for innovating with data in one of the most conservative and sensitive industries, health insurance. Tune in to find out how to accelerate innovation through effective data management, forward thinking organizational decisions and enabling technologies, like AI-powered synthetic data generation.

The 40th episode is a special one. We invited MOSTLY AI's Chief Product Officer, Mario Scriminaci, to quiz him about synthetic data technology and how the filed is progressing beyond the data privacy use case. Mario will share how MOSTLY AI is developing its synthetic data platform to provide users with easy and fast data augmentation tools. The frontiers of generative synthetic data is exciting - tune in to learn what's already a reality and what the future holds.

In episode 39 of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at MOSTLY AI, is joined by Rania Wasir, co-founder and CTO of leiwand.ai, to discuss AI transparency, the misconceptions surrounding AI transparency and fairness, and why having a standard for transparency is important. The episode also explores the concepts of fairness and explainability in AI, and how they differ from transparency. The challenges of detecting biases in large language models such as ChatGPT are also explored.

Karin Schöfegger is a seasoned ML product manager who knows how to create successful AI/ML products and mitigate the risks involved. In this episode, she shares her insights about challenges in building AI products. Tune in to learn about:

• How to align the business side and the data science side of product development
• What's the difference between traditional software development and machine learning development
• How to bring customer understanding into data science and engineering
• What are the most common traps in data science
• Why it's essential to work with realistic data instead of picture-perfect datasets
• How to get buy-in from stakeholders for ethical AI

Kicking off season three of the Data Democratization podcast, our host, Alexandra Ebert, MOSTLY AI's Chief Trust Officer, talks to Ryan Carrier, Founder and Executive Director of the NGO For Humanity. Ryan's mission at For Humanity is to translate emerging AI regulation into auditable criteria, helping to build an AI ecosystem that people can trust.

If you want to learn more about For Humanity's work, join their Slack community or take one of their classes online.

Noelle knows her stuff when it comes to implementing and scaling AI while, at the same time, keeping everyone content and on board. With experience leading teams at Microsoft, NPR and Amazon, she is well-versed in the day-to-day challenges of building an AI-ready culture and knows how to overcome them. She specializes in conversational AI, voice technology, intelligent apps, and responsible AI, working on creating innovative tech education programs. Tune in to learn her tips and tricks for building AI teams and AI models with success! 

Pedro Pavón is the Global Policy Director responsible for monetization, privacy, and fairness at Meta. Pedro is a professor of law and a certified privacy professional who talked to us about the state of privacy and fairness. Meta has been the focus of attention for its role in society and the public discourse. Pedro sheds light on some of the challenges and solutions social media companies need to tackle to preserve privacy, facilitate research and mitigate impacts on democracy.

Author of a best-seller book for AI ethics, Ethical machines, Reid's mission is to educate business leaders about the practical reality of AI ethics. Business leaders need to understand ethics if they care about their brands. As Reid says, you can't math your way out of AI bias. Issues of ethics need to be addressed head-on, and those at the top must understand the nuances of operationalizing AI ethics and running AI systems to do so. Tune in to this episode of the Data Democratization Podcast to learn:

• why ethics is not a fuzzy topic and how to properly operationalize it,
• why businesses should hire AI ethicists and why lawyers can't do the job of an ethicist,
• how to think about AI ethics,
• how to build an AI risk mitigation program,
• what are the pitfalls and best practices for implementing AI ethics,
• how to buy AI solutions and prepare procurement for the challenges of purchasing responsible AI products,
• the difference between responsible AI, ethical AI, and trustworthy AI,
• how to write an AI ethics statement that actually does its job,
• what's the difference between global explainable AI (XAI) and local XAI

Reid is a regularly published author at Harvard Business Review. If you would like to learn more about his work, read his article entitled Everyone in Your Organization Needs to Understand AI Ethics.

The Data Democratization Podcast is back with an intriguing episode giving us a glimpse into the future of healthcare. Just like with any industry, AI is set to revolutionize how health insurers and healthcare service providers work. Improving patient outcomes is a great way to maximize the positive impact. However, the risks, as well as the opportunities are even greater when it comes to the health of millions of humans. Laura and Brent, two AI Ethics experts working at Humana, a large US health insurance company, are pioneers of their fields. For them, ethical AI, fairness and explainability are not just far-away buzz words, but everyday todo items with hands-on solutions. If you would like to learn more about how ethical AI gets done, listen to this episode and find out:

• How will AI revolutionize healthcare?
• How to build AI ethics programs?
• What is fairness in AI and what does synthetic data have to do with it?
• How is fair synthetic data used to promote AI fairness?

Meet Laura Mariano, Lead Ethical AI Data Scientist and Brent Sundheimer, Principal AI Architect from Humana and your host, Alexandra Ebert, Chief Trust Officer at MOSTLY AI, the world’s leading synthetic data company! 

For the 50th episode of the Data Democratization Podcast, I sat down with Anna Lishchenko, Data & Analytics for Business Platform Lead at Erste Group. As a true champion of data democratization, Anna shares invaluable insights into how to make data widely accessible, actionable, and impactful across a large, decentralized organization.

💡 What you'll learn:

• The essential elements of building a data-driven culture, including data literacy, governance, and community building.
• Laying the foundation for success: How to align data and AI initiatives with business goals and secure buy-in from key stakeholders.
• Breaking barriers to experimentation: Using synthetic data to democratize access and accelerate innovation.
• Bridging silos: Connecting business and technical teams to drive collaboration and create real impact.
• Scaling AI and data initiatives: Turning one-off projects into sustainable enterprise-wide strategies.

Whether you're just starting on your AI journey or scaling data initiatives, this episode is packed with actionable insights and practical advice. Don’t miss this engaging conversation about the status-quo and the future of data democratization!

Omer Tene is a well-known data privacy expert, who led the International Association of Privacy Professionals for years. He has a deep and global understanding of data privacy legilsations as they stand in 2022 and has a pretty good grasp on the trends and about the way things are likely to evolve globally. Tune in to learn about the latest news on data privacy legislations and the hot topics of the day, including crypto, NFTs and the metaverse. 

Ville Sointu is leading the Emerging Technologies team at one of Europe's biggest banks, Nordea. In this episode, he shares his advice and insights about adopting new technologies in famously conservative financial environments. Ville is also a host of the podcast entitled Fintech Daydreaming where he covers fintech topics with his guests from the financial sector. 

In this episode we talked to a prominent scientist from the data privacy field, Yves-Alexandre de Montjoye. He is an assistant professor at the Imperial College London, leading the Computational Privacy Group. A lot of fascinating privacy questions came up about behavioral data, k-anonymity, differential privacy and meaningless privacy guarantees that mask true risks. We talked about the way forward and how true data privacy can be created in practical terms. Tune in for an enlightening conversation that puts a lot of greys into the seemingly black and white world of data privacy!   

The recently announced Transatlantic Data Privacy Framework will foster data flows between the US and the EU, addressing the concerns raised by the Schrems II. decision. The US-made an unprecedented commitment to strengthen the privacy protection applicable to US signals intelligence activities within the new framework. New safeguards will be implemented to protect citizens' rights while advancing cross-border data flows. The next step is to translate this framework agreement into legal documents that will be put into practice on both sides of the Atlantic. But what does this mean for data privacy in practice? What are the major challenges, and what can we expect in the long run? We spoke to J. Scott Marcus, Senior Fellow at the EU's economic think tank, Bruegel, about the history and future of transatlantic data flows.
Read on to learn how synthetic data can solve cross-border data sharing!

We talked to an amazingly experienced and visionary test engineer to find out all about her challenges and inspirations. Alexandra and Maaret covered a lot of ground in the testing landscape, from everyday testing challenges to best practices and to visions of the future. According to Maaret, testing is about breaking illusions and we couldn't agree with her more. Testing is also like singing. Why? Tune in to find out! 

What does it take to create effective digital policies? Why does the AI Act only go half-way - and what else needs to happen to ensure meaningful regulation of AI? How could the EU and the US overcome the challenges of negotiating transatlantic dataflows? And why should the EU might consider to stop relying on the Brussels Effect and instead get down on the negotiation table? Tune in to this conversation with Andrea Renda, a Senior Research Fellow at the Center for European Policy Studies (CEPS) and Advisor to the European Parliament, to learn more about the geopolitical battle on data, AI and digital policies.

What's synthetic data's future, and what's behind the synthetic data hype? This episode is all about synthetic data. We spoke to Tobi Hann, CEO of MOSTLY AI, the world's leading synthetic data company about the opportunities and challenges surrounding this important data tool. MOSTLY AI's recent Series B funding round is the biggest investment for synthetic data in Europe to date. What is synthetic data? It's an emerging privacy enhancing technology that enables privacy-preserving data usage, improves machine learning models and allows realistic testing. In short: a data democratization tool. Listen in to find out all about why the future is synthetic. 

To celebrate Data Privacy Day 2022, we talked to the godfather of GDPR, Paul Nemitz, about how bigtech threatens democracy, the role law can play in protecting people and societies from adverse effects of technology and why it's time to regulate AI. Tune in to learn more about the upcoming European AI act and find out what role synthetic data is likely to play in this regulated future! 

Axel Voss is  leading the Special Committee on Artificial Intelligence in the European Parliament. He's been working on a report outlining important policy recommendations for the upcoming European AI regulations. Among other things, Axel talked to us about:

• why the GDPR is due for an update
• what the future of data protection holds
• how the EU should compete globally in AI and digital innovation
• why access to high-quality data is so important 
• how synthetic data can help bridge the gap between data protection and data-driven innovations
• what the upcoming European AI-regulation will look like

If you would like to learn more about the legislative privacy landscape around GDPR and the upcoming AI regulations, listen to one of our previous conversations with Axel von dem Bussche, GDPR, the new European AI regulation, and the privacy landscape. 

Denis Rothman has been an AI practitioner since the dawn of this technology. Denis shares his ideas on the origins of explainable AI, its necessity, the way forward for model agnostic explainable AI and the challenges of natural language processing. 

In episode 2 of the new season, Alexandra Ebert chats with Daragh Morrissey, Microsoft’s Director of AI for Worldwide Financial Services, recorded live at Money2020 US. Daragh offers a global perspective on AI adoption in financial services, highlighting unique strategies and challenges faced by institutions worldwide. He explains why Canada and Australia stand out in AI progress and why succeeding with Gen AI requires financial institutions to shift from over-strategizing to focusing on tangible outcomes.

Daragh also shares insights on impactful AI applications in financial services, from automating contact centers to upselling, enhancing customer relationships, and modernizing legacy code. Lastly, Alexandra and Daragh take a look at the future of work and the role autonomous agents might play. They also debate whether AI will free up advisors time and whether, as a result, banks will have many more human advisors, or if the future of personalized banking will be more automated, yet transformative in enhancing individual financial health and fostering greater inclusivity.

Daragh’s compelling anecdotes and strategic insights make this episode a must-listen for anyone interested in AI’s future in financial services.


Table of Contents:

• 0:00 - 2:39 Introduction to the Episode and Guest
• 2:39 - 4:42 Daragh's Role and Microsoft's AI Approach in Financial Services
• 4:42 - 6:37 Patterns in Successful AI Adoption Globally
• 6:37 - 8:20 Gen AI Adoption: Early Success Stories and Lessons Learned
• 8:20 - 10:59 Overcoming Challenges: Moving Beyond Perfectionism in AI Projects
• 10:59 - 12:14 The Shift in Financial Services AI Use Cases
• 12:14 - 14:36 Regional Differences in AI Approaches in Financial Services
• 14:36 - 17:55 AI Use Cases in Financial Services: From Advisors to Autonomous Agents
• 17:55 - 20:00 Ethical Challenges and Responsible AI in Financial Services
• 20:00 - 23:25 The Future of Financial Services AI: Customer Relationship Innovations
• 23:25 - 27:32 Expanding Financial Inclusion with AI and Responsible AI Practices
• 27:32 - 29:41 Closing Thoughts on AI’s Impact on Financial Services

What does the future hold for the insurance industry? In the latest episode of the Data Democratization Podcast, our host, Alexandra Ebert talked to David Marock, a seasoned insurtech, fintech and proptech expert from London. David shared his insights on the state of AI in the insurance industry and what are the current trends developing in the insurtech space. In this episode you will hear about AI opportunities in insurance, why traditional insurance companies are tech hesitant, how to overcome the tech inertia in insurance organizations, how regulatory pressure is changing minds about digital transformation, why fairness is critical for insurance companies, how synthetic data solves data access and privacy issues, what to do about less tech-savvy business leaders and why the future of insurance will be driven by new technologies. 

Take an organizational deep-dive into the topic of responsible AI with Maria Axente, PwC's Responsible AI lead! You'll hear lots of hands-on advice for decision makers looking to make their company's AI adoption a success from hiring decisions, organizational structures and the new AI mindset of pause and reflect. 

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 data
• how to maximize the lifetime revenue of a loan
• how to detect suspicious transactions and prevent fraud
• how to estimate credit risk using machine learning
• how to unlock transaction data for AI training
• why synthetic data is superior to legacy data anonymization techniques
• optimize software testing processes
• create 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. 

Welcome back to Season 4 of the Data Democratization Podcast! In the 1st episode of the new season, Alexandra Ebert sat down with Malcolm DeMayo, NVIDIA's VP of Global Financial Services, live at Money2020 US to dive into what it takes for financial services organizations to succeed with data and AI at scale. 

Malcolm shares insights on using data as a true differentiator, why Responsible AI practices are more important than ever, and how modern privacy-enhancing technologies - like federated learning and synthetic data - help tackle common data challenges. He also sheds light on how Gen AI is impacting talent and the surprising ways AI assistants might help organizations counteract the negative effects of employee churn. And, of course, Alexandra asks Malcolm for his vision for the future of AI in financial services. 

Check out other episodes of the Data Democratization Podcast for more stories about data, privacy, responsible AI and how to do data democratization well.

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!

Nicolas Passadelis is a lawyer and privacy expert who has been leading the Data Governance team at Swisscom for over four years. In this episode of the Data Democratization Podcast, Nicolas shares his best practices of data governance and provides real-life examples of how Swisscom's data ethics board works. The episode contains an amazing collection of actionable takeaways and great answers to the big questions of data governance. For example, how to implement data governance in an enterprise setting successfully? How to automate and scale compliance? How to self-assess your data protection practices? What is data ethics? How to create a data ethics framework? How to create a data ethics board? What are the six ethics principles for assessment at Swisscom? Listen to the episode and reach out to us with your own solutions to these questions by sending a voice recording to podcast@mostly.ai!
Read the transcript! 

Paul Tiwald has been part of the MOSTLY AI team since the beginning. He is the mastermind behind the team's research into fairness and the idea of fair synthetic data. 

In this episode, you will hear about: 

• what it's like to work in the field of artificial intelligence (spoiler: it's really fun!)
• how the idea of fair synthetic data came up
• how to create machine learning models that are private and fair by design
• why is it so challenging to remove bias from an algorithm
• what are proxy variables, and why are they dangerous
• what is the definition of fairness, and why do we need one in the first place
• how should companies start implementing fairness and ethical approaches into their AI development
• why it's impossible to fix bias without fair synthetic data and algorithmic fairness

We talked to one of Europe's most renowned GDPR and data experts, who shared his insights about the regulatory landscape in Europe and elsewhere and gave excellent advice for lawmakers and companies. 

In this episode, you will hear more about:

• recent regulatory developments, including Schrems II, GDPR, and the new AI-regulation proposal from the European Court of Justice
• why regulation is necessary and timely for AI
• what companies should do in light of these recent developments
• how, according to Axel's prediction, we'll end up with 20 GDPR-like laws
• how to make regulation less complex and easier to comply with
• how to develop a successful data strategy and to turn data privacy into a competitive edge through know-how, proactivity, and risk assessments 
• why 95% of data transfers became illegal after Schrems II and that companies need to map all of their cross-border data transfers to comply with regulations
• how synthetic data can help, since it's exempt from GDPR and Schrems II

In this action-packed episode, John Frushour, Deputy Chief Information Security Officer at New York-Presbyterian Hospital, shares his best frontline data stories. And data stories don't get any more frontline than his. From fighting the opioid crisis to the COVID-19 emergency in New York, John and his team accomplished superhuman achievements with data. 

In this episode, you will hear more about:

• the most useful leadership, data, and technical skills for CISOs
• how DevOps teams operate and how they mature with data science and automation
• balancing data protection with data access in a healthcare setting
• advanced analytics use cases: tracking opioids and sensor data in the ICU
• the COVID-19 challenge in New York 2020 from a CISOs perspective
• using synthetic data for AI/ML
• AI and data regulations from a CISO's perspective in 2021
• how to increase diversity in cybersecurity teams
• tips for keeping your data safe and secure and for finding the best tequila in town

Ryan is a Senior Data Scientist at Spotify with extensive experience in developing great
customer-centric products with the power of data. He is a data consultant and university
lecturer, passionate about data science and understanding the business side of things.
In this episode you will hear about:

• How to start building data infrastructure in your organization, no matter the size.
• How to embed data best practices in your team and how to get the most value out of data science.
• Actionable advice on how to scale machine learning in your organization through making data accessible and automating data access processes.
• Data protection is a true differentiator in today’s market. You don’t need to use
  personal data for data science and fake users are better than real ones for testing your
  ideas.

Punit Bhatia was the Privacy and Protection Officer at ING and has tons of experience in managing privacy and data protection in large international environments. In this episode, Punit shares his best strategic advice for those looking to strategize privacy in their organization. 

You will hear about:

• the three biggest privacy challenges for enterprises and their solutions
• whose responsibility should privacy be in an organization for best results
•  why synthetic data is the way forward in data-sharing
• how to approach AI from a privacy and data protection standpoint
• what should companies expect in the privacy space in 2021 and beyond

In the fourth episode of the Data Democratization pod, we are talking to Sang Shin, serial entrepreneur, investment expert about his adventures in data monetization and he'll share his vision for the future of the data and privacy space. 
Topics discussed in the episode:

• How Been Choice, a privacy protection and data monetization app was banned by Apple
• What is the data privacy landscape like in Southeast Asia in 2021
• What are some notable privacy tech innovations
• How synthetic data made a datathon possible with data from both the private and public sector
• What the future holds for tech innovations and why the open data movement is gaining momentum

In this episode, we will be exploring best practices around digital transformations in banking. Rebecca has decades of experience in leading financial institutions and led major transformations during her career. She has a unique, executive-level perspective to share with us about processes, data management, and how AI can be used for fairness. You can find Rebecca through her website.

In the 47th episode of the Data Democratization Podcast, host Alexandra Ebert talks to Maritza Curry, Head of Data at RCS South Africa, to explore practical insights into developing effective data strategies. The discussion delves into the importance of solid data management and data governance. It also covers the topic of whether an AI strategy is necessary and the critical need for integrating business literacy into AI and data initiatives. Maritza offers valuable tips from her extensive experience, emphasizing the importance of good communication. She highlights the necessity of talking not only to executives but also to those on the frontlines in order to develop effective data strategies and tailor them to best fit your organizational culture.

Check out the other episodes of the Data Democratization Podcast for more stories about data, privacy, responsible AI and how to do data democratization well. 

Our second guest on the show is Nada Bseikri, a privacy pro from Apple Bank, New York. Nada has a unique perspective: she has both a legal and a software engineering background. Thanks to this double role, she can share unique insights into the field of data privacy. Nada shares her best tips for making privacy go beyond compliance, and we'll find out why privacy carrots are important. 

What better way to celebrate Data Privacy Day than to have an awesome chat with a seasoned privacy professional who has been in the frontlines of privacy since the dawn of days? Shampa Chatterjee shares her great adventures around the world and in the service of others, as well as her best advice to those looking to create success stories in the field of data privacy. We discussed customer-centricity, privacy tech, automation, synthetic data, and more. 

In the 46th episode of the Data Democratization Podcast, host Alexandra Ebert is talking to Wolfgang Weidinger, AI, Data Science, and Analytics Coordinator at Generali Insurance, Austria, and Chairman Of The Board at the Vienna Data Science Group.
Wolfgang is a seasoned data scientist with tons of experience managing AI, data science, and analytics projects. 

The episode covers a wide range of topics, offering actionable tips for those looking to deploy AI models in large organizations:

• selecting the right tools for AI projects,
• the adoption of AI in various industries,
• the significance of soft skills, collaboration, and domain knowledge,
• the organizational role of the data scientist,
• how to bridge the gap between business and technology.

If you would like to learn more about data science and AI in practice, we recommend The Handbook of Data Science and AI - Generate Value from Data with Machine Learning and Data Analytics, co-authored by Wolfgang. If you are in Vienna, Austria, follow the Vienna Data Science Group for great meetups and opportunities to connect with the local data science community!

In this episode of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at MOSTLY AI, sits down with Caroline Louveaux, Chief Privacy & Data Responsibility Officer at Mastercard, to explore the evolving landscape of data privacy and AI governance. Caroline shares her insights on topics ranging from privacy-enhancing technologies (PETs) to data for social impact. Here is what you'll learn:

• How to be successful in today's data and AI ecosystem,
• What is the role of the Chief Data Responsibility Officer,
• How to set up your organization for compliance with the 'alphabet soup of EU regulations',
• How to make compliance loveable,
• What's needed on the regulatory side,
• How to enable AI innovation,
• What is an AI governance framework, and how to make it work?
• How can privacy pros prepare for AI?
• How can privacy-enhancing technologies facilitate AI innovation?
• Why is automation so important?
• Can data and AI positively impact society?

Dive into this conversation to better understand the importance of data governance and responsible data usage in the digital age.