How to Protect Consumer Privacy Rights

How To Handle Sensitive Information in your next AI Project It's crucial to handle sensitive user information with care. Whether it's personal data, financial details, or health information, understanding how to protect and manage it is essential to maintain trust and comply with privacy regulations. Here are 5 best practices to follow: 1. Identify and Classify Sensitive Data Start by identifying the types of sensitive data your application handles, such as personally identifiable information (PII), sensitive personal information (SPI), and confidential data. Understand the specific legal requirements and privacy regulations that apply, such as GDPR or the California Consumer Privacy Act. 2. Minimize Data Exposure Only share the necessary information with AI endpoints. For PII, such as names, addresses, or social security numbers, consider redacting this information before making API calls, especially if the data could be linked to sensitive applications, like healthcare or financial services. 3. Avoid Sharing Highly Sensitive Information Never pass sensitive personal information, such as credit card numbers, passwords, or bank account details, through AI endpoints. Instead, use secure, dedicated channels for handling and processing such data to avoid unintended exposure or misuse. 4. Implement Data Anonymization When dealing with confidential information, like health conditions or legal matters, ensure that the data cannot be traced back to an individual. Anonymize the data before using it with AI services to maintain user privacy and comply with legal standards. 5. Regularly Review and Update Privacy Practices Data privacy is a dynamic field with evolving laws and best practices. To ensure continued compliance and protection of user data, regularly review your data handling processes, stay updated on relevant regulations, and adjust your practices as needed. Remember, safeguarding sensitive information is not just about compliance — it's about earning and keeping the trust of your users.

California's recent "do not sell" and "do not share" privacy enforcement sweep targeted streaming services, but it has relevant reminders and lessons for all companies.    1️⃣ "Selling" isn't just trading personal data for money--it can also be sharing data with vendors to make products work or for advertising. "Sharing" encompasses many data exchanges for #DigitalAdvertising.   2️⃣ "Selling" and "sharing" requires specific disclosures before the data is collected, including that the data will be sold or shared and opt-out process details.      3️⃣ Opt-out processes need to be available in the context that consumers interact with the company. Different processes may be required in-app, with connected services or devices, on websites, and in physical locations.   4️⃣ Opt-out processes need to be frictionless, with minimal steps to take.   5️⃣ Opt-out processes need stop the "sales" and "sharing" on a go forward basis across all methods by which the specific customer's #PersonalData is "sold" or "shared".    6️⃣ Starting late next month, detailed regulations regarding technical and operational processed to respond to, honor, and persist preferences (including for known customers) from opt-out signals like the #GlobalPrivacyControl become enforceable. To date, these regulations have been delayed by court order.   If your company has not looked at these issues recently, this quarter is a good time for a tune-up, especially with the California and Connecticut AG record of enforcement in this area, and the forthcoming Washington My Health My Data and #litigation risks that involves.   Here's a tune-up action plan:   ☑️Validate you understand all methods used to transmit data to third parties. Consider offline sharing, server-to-server integrations, SDKs in your apps, and #pixel/tracker/cookie based sharing. ☑️Confirm your process for identifying the third parties that data is disclosed to is current and working. ☑️Check in that protocols for disclosing data to third parties are defined and working, including with your opt-out processes. ☑️For necessary data disclosures that cannot be opted out of, test that #contracting processes are getting the necessary contract terms for sharing with those vendors and partners not to be a "sale" or "sharing" under the law. ☑️Confirm your data practices align with your commitments to customers (including in privacy policies, #cookiebanners, etc.). ☑️Probe that the methods in which customers provide data to your company that may be "sold" or "shared" are also contexts where they can opt-out. ☑️Explore the opt-out processes offered to determine that there isn't unnecessary friction. ☑️Test that your opt-out processes are working, including within the specified timelines.  ☑️Validate opt-out processes respond to the Global Privacy Control, adjusting as needed under privacy regulations such as to associate signals with known customer records. #MHMDA #privacy #privacyoperations #CCPA #donotsell

Your brand is likely misusing first-party data and violating customer trust. It's not your intention, but it's probably happening. Here are some common issues I've seen: 1.) Scattering customer data in too many locations - email vendors/CRMs - data warehouses - spreadsheets (eek) 2.) Ignoring permission ...or defaulting to "allow everything" 3.) Not rolling off/expiring data no longer necessary - long-gone churned customers - legacy systems - inactive contact lists 4.) Lack of transparency in how the customer data will be used ...vague or complex privacy/consent policies 5.) Giving too many employees access to sensitive/data ...not everyone needs access to PII/PHI info 6.) Low-security storage - employees accessing cust data on personal devices - lack of roles/permissions - lack of logging 7.) Sharing passwords - bypassing MFA/2FA w/ shared logins - passwords in shared Google Docs - sent via email (ugh) Get caught, and you could face: - significant fines (we're talking millions) - a damaged reputation - loss of customer trust But you can fix this. Here's what to do: - Ask customers what data they're okay sharing - Keep customer data in one secure place (CDP/warehouse) - Only collect what you need (data minimization) - Set clear rules for handling data (who/what) - Offer something in return for data (value trade) - Only let employees access what they need for their job - Use strong protection for all sensitive info - Give each person their own login Your customers will trust you more. Your legal team will be happy. ...and bonus, your marketing will work better. What other data mistakes have you seen? Drop a comment. #dataprivacy #security #consent #dataminimization

You’re the new Privacy Analyst at a U.S. retail company. Your manager just asked you to ensure the company is compliant with the California Consumer Privacy Act (CCPA), but you quickly realize there’s no data inventory or record of what personal data is being collected, where it’s stored, or who it’s shared with. How would you even begin? First, you’d start by building a data inventory — that means identifying what personal data the company collects (names, emails, browsing history, etc.), how it’s collected (forms, cookies, third-party platforms), and where it lives (CRM, marketing tools, cloud storage, etc.). You’d likely send out a questionnaire or meet with key teams (marketing, IT, sales) to gather this info. Then, you’d map the data flows — what systems touch this data, who has access, and whether it gets sent to vendors or service providers. This is essential for understanding risk and creating compliant privacy notices. Finally, you’d document it all and check it against the CCPA requirements — can users request access to their data? Can they delete it? Is there a way to opt out of data selling? This is GRC work in action.. breaking down compliance into trackable steps and helping the business stay accountable.

Yesterday, the FTC added to the ever-expanding jurisprudence of sensitive data.  By Final Order in X-Mode/Outlogic, the FTC has given a template for what the implementation of reasonable and appropriate safeguards might look like to avoid putting consumers’ sensitive personal information unlawfully at risk. Beyond not selling, sharing or transferring sensitive location data, X-Mode is required to: 1 - create a program to develop and maintain a comprehensive list of sensitive locations; 2 - delete or destroy all location data previously collected without consent (or deidentify/render non-sensitive); 3 – develop a supplier assessment program to assure lawful collection of data 4 – develop procedures to ensure data recipients lawfully use data sold or shared; 5 – implement a comprehensive privacy program, and 6 – create a data retention schedule. Without question, the FTC will expect businesses that collect, have, sell, share, transfer or otherwise obtain sensitive data and/or location data to follow most if not all of these or similar practices. https://lnkd.in/ecZ5aspU #safeguardprivacy #privacy #legaltech #compliance #adexchanger #iapp #dataprotection #onlineadvertising #ftc #tech #data #legal #advertising #law #compliance #ccpa #dataprotection #privacylaw #mobileadvertising #dataprivacy #advertisingandmarketing #technology #business #privacy #dataprotection #datatransfers Richy Glassberg, Katy Keohane, CIPP-US, Michael Simon, CIPP-US/E, CIPM,

It wouldn't be a holiday without news from CPPA and it comes with 🎆🎆 The latest is California's largest CCPA penalty yet: $1.55M against Healthline Media. ALL companies can learn from this latest enforcement. Here are the basics: Health data under scrutiny: First CCPA action targeting health-related information, reflecting nationwide trend of increased oversight on sensitive data tracking. Your opt-out tools are probably broken: Healthline had proper privacy disclosures but their opt-out mechanisms didn't always work. Consumers used webforms, cookie managers, AND Global Privacy Control signals often not working with 118+ cookies and pixels firing data to third parties. Deceptive cookie controls: Healthline's banner promised consumers could disable advertising cookies but it didn't function properly. Opt-outs weren't being honored. False privacy promises now trigger deceptive practice violations.  Purpose limitation now being enforced: First case applying CCPA's "reasonable consumer expectation" standard. Sharing health article data for advertising violated this principle even with disclosures—some data uses may require opt-in or be prohibited entirely. Contract language matters: Vague terms like "for purposes contemplated" don't cut it. CCPA requires specific statutory language in all vendor agreements. What should companies do now? Implement ongoing opt-out testing: Schedule monthly technical validation that mechanisms actually stop data flows, not just update settings. Establish cookie governance program: Create a program that manages the complete lifecycle of all pixels/cookies, their vendors, and contractual compliance status. Audit vendor contracts for CCPA-specific language: Review all contracts for required language and align to the privacy notice disclosures too. We love helping companies build and manage cookie governance programs and auditing your cookie consent software. Ready to get started? Drop us a note and grab our free cookie governance guides + checklists on our website!

🌟 Breaking Down The Data Protection Impact Assessment (DPIA) Methodology 🚀 🔍 Understanding DPIA: A Data Protection Impact Assessment (DPIA), also known as data protection impact assessment or privacy impact assessment, is a vital assessment for mitigating risks to data processing inputs and outputs and for following privacy liability laws like GDPR and DPDP. It enables organizations to take proactive steps to mitigate privacy risks, and serves as evidence of accountability in the handling of personal data. 💡 Detect integrated with DPIA: A breakdown of the DPIA methodology. 1️⃣ GET READY TO COLLECT & MEASURE YOUR DATA: Step 1: Identify All Data Processing Activities. If your goal is to build a loyalty program based on customer data, for instance, you will need to document the varieties of data you are acquiring and from where it is obtained. 2️⃣ Identify risks & benefits of data processing: Assess the potential risk to privacy (e.g. information breaches) and balance them against the business-related advantages, such as better insights about your customers. 3️⃣ Must assess necessity, proportionality and legality of data processing: Ensure the service processes data in accordance with the law and only for the purpose indicated. Do not request unnecessary information such as marital status for a delivery service. 4️⃣ Assess technical & organizational security arrangements: Use the right protections, such as encryption, access controls and employees training to secure sensitive data such as health records or financial information. 5️⃣ Conduct the DPIA: Descriptive configuration and mitigation for data flow and risk analysis. This step ensures compliance with data subject rights and privacy for the processing activity. 6️⃣ Document your DPIA findings: Reflex all observations, risk identified, and practice mitigation. This record demonstrates your organization’s commitment to privacy compliance. 7️⃣ Enforce data protection: Establish the recommended privacy and security controls in the operations. For example, use two-factor authentication for systems that store sensitive data. 📚 Example in Action: --Think about a healthcare provider rolling out a telemedicine platform. --In preparation, they map the data from patients to physicians. --Identify risks, such as unauthorized access to medical records. --Make sure you grant permission to use your data. --Protect patient data in transit and at rest through encryption. As part of DPO Role, DPIA needs to be done, documented in the product and necessary controls are deployed so that product is compliant. #privacy #impact #assessment #DPIA #governance #PII #data #information

Data privacy might seem like a box to tick, but it’s much more than that. It’s the backbone of trust between you and your users. Here are a few ways to stay on top of it: + Encrypt sensitive data from day one to prevent unauthorized access. + Regular audits of your data storage and access systems are crucial to catch vulnerabilities before they become issues. + Be transparent about how you collect, store, and use data. Clear privacy policies go a long way in building user confidence. + Stay compliant with regulations like GDPR and CCPA. It’s not optional - it’s mandatory. + Train your team on the importance of data security, ensuring everyone from developers to support staff understands their role in safeguarding information. It’s easy to overlook these tasks when you're focused on growth. But staying proactive with data privacy isn’t just about following laws - it’s about protecting your reputation and building long-term relationships with your users. Don’t let what seems monotonous now turn into a crisis later. Stay ahead. #DataPrivacy #AppSecurity #GDPR #Trust #DataProtection #StartupTips #TechLeaders #CyberSecurity #UserTrust #AppDevelopment

Trap & Trace: the latest trend of privacy lawsuits (A short guide for Chief Privacy Officers) What is Trap and Trace? Trap and trace devices or processes, originally used by law enforcement, capture information about incoming signals to devices like phones or computers. In the digital context, this term now often refers to tracking technologies such as cookies or web beacons that record user activities like IP addresses, browsing behavior, or interaction with content on websites. Under laws like California's Invasion of Privacy Act (CIPA), unauthorized use of these technologies can lead to significant legal repercussions. What Chief Privacy Officers Need to Know: Statutory Penalties: In California, violations can lead to penalties of $5,000 per violation or treble damages, highlighting the financial risk of non-compliance. Broader Implications: With over 400 lawsuits filed, there's a trend towards interpreting privacy laws more broadly, which could affect businesses across the U.S. What to Look for on Your Website: Tracking Technologies: Identify all cookies, pixels, scripts, or beacons that might be capturing user data. This includes analytics tools and advertising tech. User Consent: Ensure there's explicit consent for data collection. This might involve updating privacy policies or adding clear opt-in notices. Data Sharing: Review how collected data is shared with third parties to ensure it's done with user consent and within legal boundaries. How to Mitigate Risks: Compliance Audit: Regularly audit your website's data practices to ensure they adhere to privacy laws. This might involve third-party audits or consulting with legal experts. Privacy by Design: Implement data protection from the ground up in your website design, ensuring minimal data collection and transparent practices. User Education: Clearly communicate to users what data is collected, how it's used, and how they can control it, enhancing trust and compliance. Stay Informed: Keep abreast of legal changes and court rulings. Laws like CIPA evolve, and staying ahead can prevent legal issues. Privacy Policy: Ensure your privacy policy is comprehensive, clear, and easily accessible, reflecting your actual data practices. Legal Preparedness: Have a response strategy for potential legal actions, including how to handle data breaches or user complaints. By focusing on these areas, CPOs can significantly reduce the risk of privacy violations through trap and trace mechanisms and ensure their organization's practices are legally sound and respectful of user privacy. Need experts to conduct a cookie audit? Reach out! * This post written with the assistance of Grok AI.

Last week, the California Privacy Protection Agency fined a retailer $345,000 for failing to effectively effectuate consumers’ opt-out preference signals to prevent the sharing of their personal information (see decision below). The remedies outlined in the settlement are a clarion call for #privacypros. In short, the CPPA says privacy tech alone is not enough, just as Teresa (T) Troester-Falk wrote in an op-ed published by the IAPP today https://lnkd.in/eNqYpD4x. The CPPA alleges that the retailer relied on third-party privacy management tools without assessing their limitations, validating their operations or monitoring their functioning. They also allege the retailer required consumers to provide too much personal information (including sensitive information) to process their opt-out requests. Privacy tech is often critical today – there are far too many consumer requests, data sources, third-party partners, and assessments to manage manually – but it is equally vital to have a knowledgeable #privacypro building and overseeing the privacy program around it. This will only get more important as AI achieves its potential and scales across society. So what does the CPPA settlement require specifically? Beyond correcting the alleged deficiencies, the CPPA specifically requires the retailer to: -       “develop, implement, and maintain procedures” to identify disclosures and ensure it processes opt out requests appropriately -         “establish and implement, and thereafter maintain policies, procedures, and technical measures designed to monitor the effectiveness and functionality” of its methods for complying with opt-out requests -         “develop, implement, and maintain procedures to ensure that all personnel handling Personal Information are informed of the Business’ requirements under the CCPA and its implementing regulations relevant to their job functions” – i.e. conduct #privacy training -         “maintain a contract management and tracking process to ensure that contractual terms required by the CCPA are in place with all external recipients of Personal Information” Lots for privacy pros to focus on as they gain efficiencies and scale with privacy and #AI governance tech.