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How Legal Can Collaborate with Product and Engineering on AI Initiatives

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As organizations increasingly incorporate generative AI into their workflows and products, the relationship between legal teams and product or engineering teams has become a cornerstone of success. For in-house legal counsel, achieving a balance between fostering innovation and mitigating risks requires proactive collaboration, clear communication, and a deep understanding of technical and legal implications.

Generative AI introduces a unique set of challenges that transcend traditional legal considerations. From potential intellectual property issues to regulatory compliance, in-house counsel must anticipate risks at every stage of the AI lifecycle. To align with product and engineering teams effectively, legal professionals should focus on three primary areas:

  1. AI Development: Ensuring compliance with intellectual property and data protection laws during model training and deployment.

  2. Operational Use: Creating guardrails for internal AI use to prevent misuse or accidental exposure of sensitive information.

  3. Customer-Facing Apps: Mitigating risks in AI-powered features provided to clients or end users, including liability for outputs and compliance with evolving AI regulations.

Establishing Effective Collaboration with Product and Engineering Teams

The dynamic nature of AI requires that legal teams adopt a collaborative approach to bridge the gap between compliance and innovation. Key strategies include:

  1. Embedding Legal Early in the Development Process:

  • Engage with product and engineering teams during ideation to provide guidance on compliance and risk management before AI features are fully developed.

  • Conduct regular check-ins to review development progress, ensuring legal implications are addressed iteratively.

  1. Providing Accessible Legal Guidance:

  • Develop role-specific resources, such as one-page cheat sheets, outlining key dos and don’ts for AI-related tasks.

  • Create detailed yet digestible training sessions that focus on both technical and legal aspects of AI, helping teams understand how risks translate into actionable policies.

  1. Clarifying Accountability and Escalation Paths:

  • Assign ownership of AI-related risks across teams, ensuring clear points of contact for questions or approvals.

  • Develop escalation protocols to address complex or ambiguous scenarios, enabling swift decision-making without stalling innovation.

Managing Intellectual Property and Data Security Risks

AI initiatives often involve unique IP and data considerations. In-house counsel can mitigate risks by addressing the following:

  1. Protecting AI-Generated Outputs:

  • Ensure significant human involvement in AI-generated outputs to establish copyrightability, particularly for content intended for public or client-facing use.

  • Review license agreements for open-source models or datasets, confirming rights to modify, distribute, or commercialize derivative works.

  1. Addressing Data Privacy Concerns:

  • Restrict sensitive data inputs, particularly personal data or trade secrets, unless explicitly authorized and safeguarded.

  • Work with engineering teams to ensure compliance with cross-border data transfer rules, particularly for AI models hosted outside of the organization’s jurisdiction.

  1. Negotiating Vendor Agreements:

  • Negotiate robust contracts with AI vendors that specify data usage rights, ownership of outputs, and indemnities for intellectual property infringement.

  • Conduct thorough due diligence to ensure vendors adhere to industry-standard security and privacy protocols.

Ethical considerations, such as bias and misinformation in AI outputs, are as critical as legal compliance. In-house counsel can help mitigate these risks by partnering with product teams to:

  1. Implement "Human-in-the-Loop" Processes:

  • Require human review of AI-generated content before it is released, particularly for marketing, sales, or client-facing applications.

  • Establish clear standards for validating the accuracy and reliability of AI outputs.

  1. Address Bias and Fairness:

  • Collaborate with engineering teams to audit training data for bias and ensure diverse and representative datasets are used.

  • Develop tools that allow end users to flag problematic outputs for further review and adjustment.

  1. Maintain Transparency with Users:

  • Clearly disclose when AI is involved in generating content or making decisions, including disclaimers or watermarks for AI-generated outputs.

  • Work with product teams to create detailed user-facing documentation that explains the capabilities and limitations of AI features.

Adapting to Evolving Regulations and Market Expectations

The regulatory environment for AI is fluid and complex. Legal teams must help their organizations stay agile by:

  1. Monitoring Legislative Developments:

  • Stay updated on emerging regulations, such as the EU’s Artificial Intelligence Act and state-level AI legislation in the U.S.

  • Provide regular updates to product and engineering teams, translating regulatory changes into actionable requirements.

  1. Preparing for Liability Shifts:

  • Work with product teams to draft user agreements and disclaimers that address liability for AI-related issues, including misuse or reliance on inaccurate outputs.

  • Ensure compliance with data protection laws, particularly regarding automated decision-making and user opt-out rights.

  1. Maintaining Flexibility in Governance:

  • Develop governance policies that can evolve alongside AI technologies and regulations.

  • Include provisions for periodic policy reviews, ensuring alignment with current best practices and legal requirements.

Conclusion

Collaboration between legal, product, and engineering teams is essential to harnessing the potential of generative AI responsibly. By embedding legal guidance early, addressing key risks, and fostering a culture of transparency and accountability, in-house counsel can enable innovation while safeguarding their organizations against legal, ethical, and reputational risks. In an era of rapid technological advancement, this partnership is the foundation for sustainable growth and compliance.