AI and Privacy: The Good and the Bad

AI and Privacy: The Good and the Bad

The Good

• Privacy-preserving: AI is all about teaching machines to learn from data without peeking at your personal details. Think of it like a classroom where students share what they’ve learned, but not their personal notes. Technologies like federated learning, differential privacy, and zero-knowledge proofs help make this possible. With federated learning, models learn from devices directly like your phone without sending raw data to a central server. Differential privacy adds a layer of randomness to data, so patterns can be studied without revealing who they belong to. And zero-knowledge proofs let one party prove something is true without revealing the actual information. Together, these tools help AI get smarter while keeping your privacy safe and respected.


• Enhanced security: AI can detect various types of fraud, including payment fraud, identity theft, account takeover, chargeback fraud, fake account creation, and credit card fraud. AI is also effective in identifying synthetic identity fraud in loan applications, insider threats, insurance fraud, healthcare fraud, and protect against cyberattacks in real-time. AI systems analyze patterns and anomalies in data to flag suspicious activities, such as unusual transaction locations, sudden transaction spikes, or atypical login behavior. Additionally, AI can detect fraudulent activities through behavioral analysis, including changes in user behavior, device type, and location. AI-powered solutions can also identify deepfakes, social engineering, and voice cloning techniques used in fraud.


• Local processing: Many AI assistants now process your data right in your browser locally, on your device. This means your information stays private and doesn’t get sent to remote servers, reducing the risk of data leaks or unauthorized access. Think of it like having a smart assistant that works just for you, without ever needing to share your thoughts or queries with the outside world. It’s a smarter, safer way to get help while keeping your privacy in your hands.


• Transparent auditing: More and more, people are asking for transparency when it comes to AI because we want to trust the tools we use. That’s why there’s a growing push for third-party audits of AI models, kind of like a safety check for digital assistants. Independent experts review how these systems behave, looking for harmful, biased, or unfair outputs before they ever reach real users. It’s like having a trusted inspector make sure the AI is playing by the rules before it goes live. This kind of auditing helps build confidence that AI works fairly and responsibly, and it’s a big step toward making AI safer and more trustworthy for everyone.

The Bad

• Massive data breaches: AI companies have suffered significant security incidents OpenAI's data was breached through a supply chain attack compromising user information  2, and LastPass was fined £1.2 million after a breach exposed 1.6 million users  6


• Training data exposure: Ever wonder what happens after you chat with an AI assistant? While the conversation might feel private, the truth is that your inputs along with many others can be used to help train future versions of AI. That means your words, questions, and even your tone might end up shaping how the AI responds to millions of people. While this helps make AI smarter and more helpful, it also means there’s a small chance your personal details could show up in the AI’s answers especially if the data isn’t handled carefully. That’s why it’s important to stay aware of how your data is used, and why many are calling for clearer controls and stronger privacy safeguards. Think of it like sharing a story in a crowded room sometimes, even private moments can become part of the bigger conversation.


• Lack of transparency: Only 20% of surveyed countries have guidelines for patient data use in AI, and many companies don't clearly disclose how they handle your information  12


• Psychological harm: State attorneys general have warned major AI companies about "sycophantic and delusional outputs" that have been linked to serious mental health incidents, including suicides  1  8


• Supply chain vulnerabilities: Even when AI companies have good security, their third party vendors can be compromised as happened with OpenAI's Mixpanel breach  2


• Cybersecurity risks: Even the most advanced AI models aren’t immune to cybersecurity risks and it’s something we should all be aware of. In fact, OpenAI has acknowledged that their newer models could potentially pose high cybersecurity risks. This means they might be used to craft convincing phishing messages, exploit software vulnerabilities, or help hackers bypass security systems. While the goal of AI is to make things smarter and easier, it also means bad actors could use these tools to find new ways to target people and systems. That’s why companies and researchers are working hard to understand and manage these risks like building stronger defenses before the tools can be misused. It’s a reminder that with great power comes great responsibility and staying informed is the first step toward staying safe.

Data You Should NEVER Share with AI

1. Authentication Credentials
• Passwords, PINs, security codes, API keys
• Why: Data breaches are common  2  6, and credentials can be retained in logs or exposed through supply chain attacks
2. Financial Information
• Credit card numbers, bank account details, SSN/tax IDs
• Why: Direct path to identity theft and financial fraud, especially given recent major breaches in the AI industry
3. Medical Records
• Diagnoses, prescriptions, health conditions, mental health information
• Why: Protected by law (HIPAA/GDPR), could affect insurance/employment, and AI healthcare systems have documented privacy vulnerabilities  12
4. Personal Identifiers
• Full legal name + address + DOB combination
• Government ID numbers, biometric data
• Why: Enables identity theft, doxxing, and unauthorized surveillance especially concerning with AI smart glasses raising facial recognition privacy alarms  7
5. Intimate or Sensitive Content
• Explicit photos, private relationship details, mental health struggles
• Why: Could be leaked, used for manipulation, or contribute to harmful AI outputs that have been linked to psychological harm  1  8
6. Proprietary Business Information
• Trade secrets, confidential business data, unreleased products, source code
• Why: Could be leaked to competitors, exposed in model outputs, or used in training data accessible to other users  3
7. Children's Information
• Any personal data about minors
• Why: Special legal protections apply, and state AGs have specifically raised concerns about AI's impact on non-adults  8

Critical Reality Check

The AI industry is currently facing serious scrutiny from regulators who warn that companies are operating with insufficient safeguards  1  8. Recent breaches have shown that even major players like OpenAI can't guarantee your data's security  2. State attorneys general are demanding that AI companies implement incident reporting similar to cybersecurity breaches—but those systems aren't in place yet  1.

General Rule: If you wouldn't want it exposed in a data breach, leaked to competitors, or used to train a model that millions access, don't share it with AI. The "move fast and break things" mentality is being challenged when it comes to mental health and privacy  8, but protections are still catching up to risks.


Sources:
1 - techcrunch.com | 2 - www.zdnet.com | 3 - www.blackfog.com | 4 - www.fastcompany.com | 5 - computerweekly.com | 6 - www.itpro.com | 7 - glassalmanac.com | 8 - forbes.com | 9 - www.ft.com | 10 - www.fastcompany.com | 11 - techradar.com | 12 - coingeek.com


@genartmind