From the course: Privacy and Compliance in the Age of GenAI: Data Governance, Classification, and Inventory

The state of privacy regulation

From the course: Privacy and Compliance in the Age of GenAI: Data Governance, Classification, and Inventory

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The state of privacy regulation

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- [Instructor] Consumers want privacy laws that protect their data from harm or incorrect usage. Governments want laws that protect consumers, hold companies accountable, do not stifle innovation and align with the more global baseline. As a tech executive whose employers depend on consumer data for growth, I am even more invested in strong and solid privacy laws. That might sound surprising to folks who think that companies don't care about privacy. So let me explain. For any business to succeed, they need to grow their customer base and create customer engagement. This requires building trust with consumers, partners, and other stakeholders. Privacy laws that are confusing and are theoretical and complicated are often very hard to implement. It could even be more harmful when these laws contradict each other. Such laws slow down engineering innovation and fail to make a difference in privacy protections for the consumers, which is a lose-lose situation for everyone. For example, there is no universal approach to sensitive data in the US or in the jurisdictions overseas that have adopted comprehensive privacy regulation. One federal agency defines it as information that can be used to distinguish or trace an individual's identity. This definition requires a case-by-case assessment of the specific risk that an individual could be identified. This is the very definition of a lose-lose situation at scale. It makes the privacy teams look like blockers and creates the perception that engineers don't care about privacy, and this is why data classification is so critical. Data classification leads to privacy risk definitions that are actionable for your business rather than abstract and theoretical. Second, the ability to customize those definitions to account for different laws and changing business needs. Third, a relationship where privacy experts and others can collaborate continuously to classify data and tailor privacy protections meaningfully and continuously as well. This approach has two important benefits. First, it'll help shape a privacy governance process that'll give your company a sense of stability and continuity. Second, much like tax preparation software helps you file your taxes without getting lost in the complexity of tax law, the classification process will help your engineers operate efficiently and smartly. Your engineers will now need to think about the details of privacy laws and be able to focus on building amazing products and avoid mistakes and surprises. That way you can drive innovation without being buried by regulation, creating a win-win situation for you, the business and your customers at the same time.

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