Safeguarding Confidentiality in the Age of AI

Safeguarding Confidentiality in the Age of AI

As part of LMICK’s continued AI series, this month LMICK wants to discuss the issue of safeguarding client confidentiality when using AI technology. In prior LMICK Minute Issues, LMICK has discussed ethical considerations lawyers face when using AI in their legal practice, particularly around the protection of confidential and secure information. These concerns include:

1. Data Privacy and Confidentiality

  • Risk of Data Exposure: AI systems often require access to large datasets for training and operation. If sensitive client information is included, there’s a risk of unauthorized access or exposure.
  • Cloud-Based Solutions: Many AI tools are cloud-based, raising questions about where data is stored, who has access, and whether the data is encrypted during storage and transit.
  • Breach of Attorney-Client Privilege: Sharing confidential information with third-party AI providers might inadvertently waive attorney-client privilege.

2. Cybersecurity Threats

  • Vulnerabilities in AI Systems: AI tools may have exploitable vulnerabilities that hackers can target, such as through adversarial attacks or exploiting poorly secured APIs.
  • Phishing and Social Engineering: Cybercriminals may exploit AI-generated content to craft more convincing phishing schemes targeting law firms.
  • Ransomware Attacks: If an AI system is compromised, sensitive legal data could be encrypted and held hostage.

3. Regulatory Compliance

  • Data Protection Laws: Compliance with laws like GDPR, CCPA, or HIPAA (in healthcare-related legal matters) is critical when using AI. Lawyers must ensure that AI providers meet these requirements.
  • Jurisdictional Issues: Different jurisdictions may have varying standards for data protection and AI usage, which complicates compliance for firms operating across borders.

4. Vendor Reliability and Security

  • Third-Party Risks: Relying on external vendors for AI solutions introduces risks if the vendor has inadequate cybersecurity measures.
  • Insider Threats: AI providers might not adequately vet their employees or contractors, increasing the risk of insider data breaches.

Strategies to Mitigate These Risks

To address these concerns, lawyers can adopt the following measures:

  • Due Diligence on Vendors: Assess AI vendors for compliance with legal and cybersecurity standards. Ensure vendor agreements include robust confidentiality clauses, data handling practices, and compliance with any applicable laws. Verify how the AI vendor uses the data (e.g., for model training) and whether client data will remain confidential.
  • Data Encryption: Ensure all data shared with AI systems is encrypted both in transit and at rest. Avoid sharing unnecessary client-specific information.
  • Limited Data Sharing: Avoid providing unnecessary confidential information to AI systems.
  • Regular Audits: Conduct cybersecurity audits of AI tools and processes. Regularly review AI usage logs and data flows to ensure compliance with policies and security measures. Periodically check that third-party AI tools remain compliant with privacy and confidentiality standards.
  • Training and Awareness: Educate legal teams on recognizing and mitigating AI-related cybersecurity risks. Establish policies for AI usage within the firm, including acceptable tools and prohibited practices. Train employees on how to use AI responsibly, highlighting potential risks and the importance of data confidentiality.
  • Compliance with Ethical Obligations: Ensure AI use complies with rules of professional conduct and confidentiality obligations specific to the jurisdiction. If AI tools require sharing client data externally, obtain informed client consent before proceeding.
  • Custom AI Solutions: When feasible, use custom AI tools developed specifically for the firm, hosted on private servers to ensure maximum control over data. Opt for local processing when using AI tools to prevent data from being uploaded to external servers.
  • Incident Response Planning: Develop a clear response plan for potential data breaches, including notification procedures for clients and regulators. Have specialists on hand to handle AI-related risks and incidents.

In addition, the American Bar Association’s online article titled, “Ethical Obligations to Protect Client Data when Building Artificial Intelligence Tools: Wigmore Meets AI”, provides additional information on the ethical obligations attorneys face when using AI, as well as additional risk mitigation measures.

By balancing the innovative potential of AI with robust cybersecurity and ethical practices, lawyers can better protect sensitive information while reaping the benefits of these technologies.

Questions? Contact Jared Burke (burke@lmick.com) for more information.