This is the third and final installment to this short series on the issues surrounding the evolution of generative AI. This article will explore how companies can utilize policy to regulate AI at their organizations. You can read Generative AI: The Risks and Can AI Product Be Considered Intellectual Property? by clinking the associated links.
Company Policy and Generative AI Issues
If an organization is not successful at incorporating all desired AI restrictions into their third party contracts, clear and concise policies should fill the risk gap. Instituting a top-down, comprehensive strategy will be vital in contextualizing generative AI issues and use within the business.
When creating policies surrounding AI, an organization should first evaluate whether utilizing generative AI is necessary at all for their business tasks. This is typically accomplished via a standard risk/benefit analysis that will identify approved or forbidden use cases for generative AI. The input for the assessment should be gathered from relevant stakeholders. Internal and external legal consultants will then be required to develop specific policies tailored to the context of each business task. Categories may include:
- Scope and Purpose: The business should clearly outline the purpose and scope of the policy, notating the unique applicability to various departments, roles, and responsibilities within the company.
- AI Ethics: Where AI usage is allowed, a core set of principles should be developed to navigate the ethical use of generative AI within the business. These principles may include transparency, accountability, privacy, fairness, and alignment with corporate mission statements.
- Intellectual Property: Company policy must address the legal risks of using generative AI, especially in light of the uncertainty surrounding intellectual property laws and regulations.
- Management, Privacy and Data Security: Policies should define data handling protocols, including data collection, storage, sharing, and disposal. These policies must consider and be in compliance with data protection laws, privacy and confidentiality policies. Also essential is the protection of sensitive, confidential or personal information, as well as the strategic development of robust security measures to protect against data breaches, unauthorized access, and misuse of AI-generated product.
- Accountability and Responsibility: Stakeholders such as AI developers, users, and decision-makers must understand their specific rules and guard rails, guaranteeing a clear chain of accountability in the generation and usage of AI content.
- Human oversight: Company policy should include a framework for human oversight of AI systems, encouraging a balance between automation and human intervention in order to manage possible risks and unintended consequences. Human intervention and participation also eases concern from current employees about “being replaced.”
- Education, Awareness and Training: Companies will need to implement employee training regarding responsible AI use, making sure that they are aware of organizational policies, ethical aspects, and potential risks.
- Transparency: Regulators are increasingly focused on the transparency in AI development and explainability in AI-generated content and decision-making.
- Compliance Considerations: Policies will ensure compliance with industry regulations, longstanding company policies, and other legal obligations related to AI utilization.
- Third-party Relationships: Policies should create guidelines for managing working relationships with third-party AI partners, including due diligence, risk assessment, and ongoing regulation and monitoring.
- Audit Processes: Organizational policy should work to implement routine audits of AI systems to evaluate their performance and ensure adherence to ethical guidelines and business objectives. The policy should outline a clear chain of responsibility and define the reporting process clearly.
- Incident Response: The business must establish policies and procedures for reacting to AI-related incidents, including reporting, investigation, and remediation protocols to minimize damage and avoid recurrence.
Finally, company policy must provide a framewrok to facilitate continuous improvement by soliciting feedback and learning from each AI deployment. Lessons learned can be utilized to refine and improve relevant policies over time. Policies must remain flexible and adapatable in order to successfully keep pace with AI’s rapid evolution, which is arguably still in its inital stages of develpment.
If you want to learn more, contact the IT experts at Alliance IT. We enable Sarasota area SMBs to grow and thrive in an increasingly competitive marketplace.