In the podcast episode Jodi Daniels, Founder & CEO of Red Clover Advisors, and Justin Daniels, Legal and Corporate Counsel at Baker Donelson, share valuable insights on privacy and security considerations in product development. They discuss the common mistakes made and the crucial questions to ask when designing new products, emphasizing the need for proactive data protection.

Jodi and Justin delve into core principles and best practices for integrating privacy-by-design, highlight the risks of neglecting privacy and security during product development, and explore ways to balance innovation and functionality with privacy and data protection requirements. They also address the importance of ingraining privacy and security throughout the product life cycle and provide guidance on evaluating the privacy and security implications of emerging technologies like AI.

Topics:

From your point of view, what do you think is the biggest mistake or oversight people make when building new products when it comes to privacy and security?
What kind of questions should I be asking myself when designing a new product when it comes to data protection?
What are the core principles and best practices for operationalizing privacy-by-design when developing new products?
What are the potential risks and challenges associated with neglecting privacy and security considerations during the product development phase?
How can organizations effectively balance the need for innovation and functionality with the requirements of privacy and data protection?
What steps can companies take to ensure that privacy and security are ingrained throughout the product life cycle, from design to deployment?
Are there any specific regulations or standards that companies should be aware of when it comes to privacy and security in new product development?
What are some of the privacy and security challenges facing companies interested in generative AI?
When it comes to any kind of new technology, like AI, how can individuals and businesses evaluate the privacy and security implications before integrating them into their operations?
What are some common misconceptions or myths surrounding privacy and security in AI, and how can they be addressed?

Resources:

Data Reimagined: Building Trust One Byte at a Time

Saving When Self Employed

DIY Money | Personal Finance, Budgeting, Debt, Savings, Investing

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