{"id":973,"date":"2025-07-31T21:14:47","date_gmt":"2025-07-31T21:14:47","guid":{"rendered":"https:\/\/bryanlopez.com\/?p=973"},"modified":"2025-07-31T21:14:58","modified_gmt":"2025-07-31T21:14:58","slug":"10-questions-corporate-counsel-must-ask-before-green%e2%80%91lighting-ai-solutions","status":"publish","type":"post","link":"https:\/\/bryanlopez.com\/?p=973","title":{"rendered":"10 Questions Corporate Counsel Must Ask Before Green\u2011lighting AI Solutions"},"content":{"rendered":"\n

1. Does the proposed AI system comply with U.S. federal and state privacy laws, and international frameworks?<\/strong><\/h2>\n\n\n\n

AI systems processing personal data must meet GDPR standards (e.g. data minimization, lawful basis, rights of access\/deletion), and U.S. laws like CCPA, Nevada\u2019s AI data collection bill, and Utah\u2019s AI Policy Act (effective May\u202f1,\u202f2024) (Microsoft Azure<\/a>). Microsoft\u2019s AI platforms offer data residency, Privacy Management in Microsoft 365, and tools like differential privacy and transparency dashboards tailored to these jurisdictions (Microsoft<\/a>, Microsoft<\/a>).<\/p>\n\n\n\n

2. Are you respecting algorithmic discrimination and explainability mandates?<\/strong><\/h3>\n\n\n\n

The EU\u2019s AI Act (effective August\u202f1,\u202f2024) imposes heightened obligations for \u201chigh\u2011risk\u201d AI systems, including fairness testing, human oversight, and transparency (Wikipedia<\/a>). U.S. regulators echo concerns under FTC and EEOC enforcement. Microsoft provides tools such as Fairlearn, Content Safety, and model interpretability features designed to identify and mitigate bias.<\/p>\n\n\n\n

3. Does the AI deployment meet professional legal ethics standards?<\/strong><\/h3>\n\n\n\n

In legal practice, ABA Model Rules (1.1 Competence; 1.6 Confidentiality; 5.1 Supervision) and bar guidance\u2014including the NYC Bar \u201cSeven C\u2019s\u201d\u2014require lawyers to understand AI risks, supervise outputs, ensure confidentiality, and obtain informed consent (Reuters<\/a>). Microsoft Copilot solutions support enterprise-only deployment, do not retain client prompt history by default, and are configurable within compliance controls.<\/p>\n\n\n\n

4. Are cybersecurity safeguards sufficient under federal and industry regulation?<\/strong><\/h3>\n\n\n\n

SECs, NIST (800\u201153), FISMA, and CMMC require robust risk disclosure and cyber resilience. Microsoft\u2019s Azure, Microsoft 365 GCC High, and Defender for Cloud meet FedRAMP High, CMMC levels, and support policy enforcement and real\u2011time monitoring.<\/p>\n\n\n\n

5. Is there clear governance over models, training data, and outputs?<\/strong><\/h3>\n\n\n\n

Governance requires impact assessments, audit trails, and lifecycle controls. Microsoft mandates internal Responsible AI Standard v2 process steps including impact assessments and annual reviews prior to development phases (cdn-dynmedia-1.microsoft.com<\/a>). Azure ML and Purview provide model lineage, approval workflows, and data asset governance tools.<\/p>\n\n\n\n

6. How do you assess IP risk and output liability?<\/strong><\/h3>\n\n\n\n

Generative AI raises questions about copyright ownership. Pamela Samuelson has argued that training and output rights pose evolving legal issues around fair use and authorship (Wikipedia<\/a>). Microsoft publicly commits to content filters, red\u2011teaming to reduce hallucinations (~\u202f10\u202f% error baseline reduced to below\u202f10\u202f% via safety messaging and citation features), and prohibits use of its models for infringing IP (cdn-dynmedia-1.microsoft.com<\/a>, Microsoft<\/a>).<\/p>\n\n\n\n

7. Are there model-level security risks\u2014such as prompt injection or data poisoning?<\/strong><\/h3>\n\n\n\n

Academic and industry research warns of emerging model-exploitation tactics. Microsoft employs robust Red\u2011Teaming, secure model release controls, and is governed by its AETHER ethics board, embedding safety across design and deployment lifecycles (PMC<\/a>).<\/p>\n\n\n\n

8. Have we vetted vendors and external certifications?<\/strong><\/h3>\n\n\n\n

Vendor vetting should extend beyond contracts: reputation, data handling, transparency, ISO 42001, and auditability matter. Bloomberg Law and Reuters reporting stress vetting practice and governance even for well-known providers (Bloomberg Law<\/a>). Microsoft\u2019s voluntary commitments under the U.S. Biden\u2013Harris administration (July\u202f2023) include internal and external security testing, watermarking, public capability disclosures, bias research, and ecosystem collaboration (Wikipedia<\/a>).<\/p>\n\n\n\n

9. Is this aligned with broader AI regulatory and treaty developments?<\/strong><\/h3>\n\n\n\n

AI is governed globally via frameworks like the EU AI Act, Council of Europe AI treaty, and academic proposals for consistent international standards (Wikipedia<\/a>). Microsoft, UNESCO, and Partnership on AI work to advance cross\u2011border norms and ethical AI governance (Microsoft<\/a>).<\/p>\n\n\n\n

10. Does the deployment align with fiduciary duties and ESG responsibility?<\/strong><\/h3>\n\n\n\n

Boards and counsel must oversee AI risk disclosure, bias mitigation, privacy protection, and ethical use. Microsoft’s Responsible AI Transparency Reports (2025 edition) publicly detail its governance, risk\u2011management, and compliance framework evolution (Microsoft<\/a>). These documents support ESG reporting, third\u2011party oversight, and due diligence assessments.<\/p>\n\n\n\n

References<\/h2>\n\n\n\n