Benefits of Transparency in Data Practices

Data privacy and ethics must be a part of data strategies to set up for AI. Alignment and transparency are the most effective solutions. Both must be part of product design from day 1. Myths: Customers won’t share data if we’re transparent about how we gather it, and aligning with customer intent means less revenue. Instacart customers search for milk and see an ad for milk. Ads are more effective when they are closer to a customer’s intent to buy. Instacart charges more, so the app isn’t flooded with ads. SAP added a data gathering opt-in clause to its contracts. Over 25,000 customers opted in. The anonymized data trained models that improved the platform’s features. Customers benefit, and SAP attracts new customers with AI-supported features. I’ve seen the benefits first-hand working on data and AI products. I use a recruiting app project as an example in my courses. We gathered data about the resumes recruiters selected for phone interviews and those they rejected. Rerunning the matching after 5 select/reject examples made immediate improvements to the candidate ranking results. They asked for more transparency into the terms used for matching, and we showed them everything. We introduced the ability to reject terms or add their own. The 2nd pass matches improved dramatically. We got training data to make the models better out of the box, and they were able to find high-quality candidates faster. Alignment and transparency are core tenets of data strategy and are the foundations of an ethical AI strategy. #DataStrategy #AIStrategy #DataScience #Ethics #DataEngineering

5 of 8 Privacy Design Strategies: 𝗜𝗻𝗳𝗼𝗿𝗺 To inform is to be transparent about your data practices. Transparency is key to privacy protection. Informing data subjects about the processing of their personal data in a timely and adequate manner allows users to make informed decisions. Do this: ✅Inform users clearly and promptly. ✅Explain what, how, and why data is processed. ✅Notify them in real-time. This builds trust and shows your commitment to privacy. It empowers users and ensure responsible data handling.

Building Trust with Transparent Data Privacy Practices Data privacy is more than just compliance—it’s a way to build customer trust. With privacy concerns rising, here are some practical tips on how to communicate your privacy practices clearly and effectively: 1. Simplify the Language: Legal jargon can create confusion. Instead, use straightforward language that customers can easily understand. It builds confidence that you prioritize transparency. 2. Highlight Key Practices: Let customers know exactly how their data is collected, stored, and shared. Clearly delineated sections in your privacy policy or terms can go a long way toward reassuring users. 3. Address AI-Specific Privacy Questions: With AI, it’s especially helpful to explain any data used for training or algorithms. When customers know their data isn’t being used in unexpected ways, they feel safer using your platform. 4. Offer Easy Access: Make sure your privacy policy and terms are easy to find and view on your site or app. This simple step shows customers that privacy is a priority, not an afterthought. Privacy is a continuous effort—how do you show your commitment to transparency? Videos and content are for educational purposes only, not to provide specific legal advice. Contact: msalehpour@salehpourlaw.com #Tech #AI #dataprivacy