Introduction
The growing integration of artificial intelligence (AI) into our genealogical lives brings remarkable capabilities but also significant privacy risks through systematic data collection, indefinite storage, and potential third-party sharing. Users must adopt proactive measures to safeguard personal and sensitive information while leveraging AI tools effectively.
Objective
This post empowers users to mitigate risks of unauthorized access or data misuse, strengthen control over how platforms use personal information, and minimize exposure of sensitive data to AI systems.
Preparation
Review the privacy policies at each AI platform intended for use to understand data retention rules, third-party sharing disclosures, and training data opt-out options and engage platforms with clear data protection certifications, such as GDPR compliance.
Implementation
First, use strong, unique passwords and enable two-factor authentication (2FA) on all AI accounts.
Second, activate the privacy controls on the AI platform. For example, enable “Temporary Chat” mode with ChatGPT or toggle off “Improve AI” in account settings at Perplexity. It’s also beneficial to establish the habit of deleting unnecessary chat histories and stored interactions.
Third, audit third-party access and revoke permissions for unused integrations, such as with Google Drive.
Finally, avoid using personal identifiers, like the names, dates, locations, or relationships of living people—including DNA match lists—without consent. Instead anonymize this information through data masking, generalization, or the use of pseudonyms to achieve the desired analysis.
Review and Verify
Before pressing ‘Return,’ carefully review each query to confirm that all sensitive information, including personal identifiers, has been anonymized—unless, when dealing with living individuals, explicit consent has been obtained.
Establish a habit of checking privacy settings on a monthly basis or after any platform updates.
Ethical Considerations
Consent Awareness: as mentioned above, avoid sharing others’ personal data without explicit permission.
Transparency Advocacy: support AI platforms that disclose data usage clearly and limit third-party sharing.
Benefits and Limitations
Following these guidelines protects personal information while demonstrating respect for privacy. This approach reduces the risk of identity theft and phishing attempts, ensures compliance with regulations such as GDPR and CCPA, and helps prevent contamination of AI training data.
However, these precautions can also limit AI’s ability to generate powerful outputs and may restrict features that enhance personalization. A common assumption is that sensitive information remains secure simply because it is accessed from a personal computer, but this is not always the case.
Whether working independently or within the genealogical community, the risks posed by bad actors may not always be fully recognized. Unknown threats persist—seemingly harmless information can be exploited in unexpected ways. Cybercriminals continuously develop new techniques to manipulate, misuse, or aggregate data, transforming innocuous details into tools for fraud, impersonation, or even blackmail.
Takeaway Tips
- Review AI Platform Policies – Understand the privacy policies and data handling practices of each AI platform before using it.
- Strengthen Security Measures – Use strong, unique passwords, enable two-factor authentication (2FA), and consider a password manager like 1Password. Regularly update your passwords.
- Maximize Privacy Settings – Activate all available privacy controls within your account to limit data exposure.
- Monitor Third-Party Access – Check and manage permissions granted to third-party applications or services connected to the platform.
- Anonymize Sensitive Information – Remove or obscure personal identifiers before sharing data with AI tools.
- Ensure Proper Consent – If using AI for genealogical research involving others, obtain appropriate consent before sharing personal details.
- Use Offline Alternatives When Needed – For highly sensitive research, consider offline tools or locally hosted AI models that don’t transmit data to external servers.