I've already talked about the pros and cons of AI in the workplace. One of the most effective tools for quickly and transparently managing AI use in your company is an AI use policy.
At Sommo, we developed ours about a year ago (although we should have done it much earlier 🤦♂️). Since then, it has gone through two more revisions. Below, I’ll briefly share my experience and offer tips for creating and implementing an AI use policy.
1. What is AI usage policy
An AI acceptable use policy is a set of fundamental guidelines that explains to employees how to use AI tools like ChatGPT or Google's Bard in the workplace. These policies are designed to ensure everyone uses AI in an ethical and appropriate way.
Having such a policy protects the company from problems like:
- Leaks of Important/Confidential Information: There are more and more stories on social media about employees getting fired for improperly sharing information with AI, misjudging the risks and benefits.
- Erosion of Responsibility and Competency: AI cannot handle more complex or skilled tasks better than an employee. Any task completed with AI must be reviewed by a person who takes responsibility for the final outcome.
- Ethical Issues: Deloitte’s comprehensive and recent report, "State of Ethics and Trust in Technology," is dedicated to AI ethics and its impacts.
- Lawsuits and Reputational Damage: These are the potential consequences of the above problems. The resources needed to compensate for damages and restore the status quo can be substantial.
I hope I’ve convinced you that developing an AI policy is not just a trend but an effective tool for safeguarding and growing your company. Now, let’s move on to the second question—who should create such a policy?
In practice, this is usually handled by executive leadership. For instance, here is some data regarding developing ethical standards as part of an AI usage policy.
If possible, you can form a special committee—a group of individuals from different parts of your company—to work on the AI usage policy.
It is crucial that everyone involved in developing the policy understands the basics of AI and the challenges it can present. A good idea is to organize short workshops on key topics for the future AI usage policy—such as algorithmic bias, data privacy and protection, accountability, ethics, and social implications.
But most importantly, employees need to be aware of the AI usage policy, and it needs to actually work.
For myself, I've outlined the following rules for an effective AI usage policy:
- Team involvement: Different teams will be involved in developing, implementing, and updating the policy. This ensures you address the real interests and needs of those using the policy and fosters a sense of ownership.
- Keep it simple: The policy should be straightforward, concise, and understandable. Time and cognitive resources are the most limited assets—respect that.
- Principles over rules: Principles are more important than rigid rules. However, before establishing your own principles, I recommend looking at examples from companies like Microsoft or Google.
At Sommo, our AI usage policy is built on five key principles: security, privacy, accountability, transparency, and growth (encouraging exploration of AI’s benefits).
2. How to develop an AI-acceptable use policy
Developing an AI usage policy is still relatively new for most companies (see figure below), and there are no clear algorithms or tools yet. Therefore, when creating such a policy, you have to rely on common sense, experience, and your team.
Here are my personal tips for starting your work on an AI usage policy:
- Study government regulations: Look into relevant regulations, such as Artificial Intelligence And Worker Well-being: Principles And Best Practices For Developers And Employers
- Get familiar with the topic: There are already many courses, training programs, and guidelines for AI regulation. For example, a simple option is the AI Regulations and Frameworks Crash Course - 2024 or Introduction to Responsible AI by Google
- Don't reinvent the wheel: Study existing AI policies from similar companies or industry leaders. Use them as a reference to shape your policy. This will save time and ensure you don't miss key elements that have already been successfully implemented elsewhere.
- Focus on the goal(s): Remember that the goal of an AI policy is to encourage innovation and effective use of AI, not to impose unnecessary restrictions. The policy should promote responsible experimentation with AI while ensuring ethical and legal compliance.
The specific content and focus of an AI usage policy will vary depending on the company's industry, size, and specific use cases for AI. However, regardless of your company's industry or size, I recommend following these key steps to develop an AI usage policy:
- Define objectives: Clearly outline the objectives of using AI in your company. Understand what problems AI aims to solve and how it aligns with your business strategy.
- Define core principles: Based on the company's values, determine the ethical principles that will guide the use of AI. This might include principles like security, privacy, accountability, fairness, transparency, and growth. These principles should align with the ethical considerations discussed in the previous step.
- Identify use cases: Determine which business areas will use AI and for what purposes. Identify specific use cases and ensure they align with the company's goals and ethical standards.
- Address ethical considerations: Establish guidelines to prevent bias, ensure fairness, and protect privacy. Include measures to address ethical challenges such as discrimination, data misuse, and transparency.
- Data management: Define how data will be collected, stored, and used. Ensure compliance with relevant data protection laws and regulations and include policies on data security and privacy.
- Risk management: Identify potential risks associated with AI usage, such as security vulnerabilities, biases, or job displacement, and outline measures to mitigate these risks.
- Accountability and responsibility: Assign responsibilities for monitoring AI systems and ensuring compliance with the AI policy. Define who is accountable for any issues that arise from AI usage.
- Training and awareness: Provide training for employees on how to use AI responsibly. Ensure that staff understand both the benefits and risks of AI and how to follow the policy.
- Continuous evaluation: Establish a process for regularly evaluating the effectiveness and impact of AI systems. Update the AI policy as needed to adapt to new challenges, technologies, or regulations.
- Transparency: Maintain transparency with stakeholders, including employees, customers, and partners, about how AI is used and the decisions it influences.
3. AI usage policy template
Below, I provide an AI usage policy template that can be adapted for your company.
AI Usage Policy
1. Introduction
Purpose of the Policy: The purpose of this policy is to establish guidelines for the ethical, legal, and appropriate use of AI tools within [Organization Name]. It aims to ensure that AI technologies are deployed responsibly, respecting user privacy, and complying with applicable laws and regulations.
Benefits and Risks of AI: AI brings numerous benefits to [Organization Name], including increased efficiency, improved decision-making, and enhanced customer experiences. However, there are also potential risks, such as bias, privacy concerns, job displacement, security vulnerabilities, and misuse.
Importance of Responsible AI Use: This policy plays a crucial role in enabling [Organization Name] to harness the benefits of AI while minimizing the risks. The company is committed to responsible innovation, upholding ethical standards, and ensuring that AI tools are used to support the organization's values and objectives.
2. Scope
Applicability: This policy applies to all employees, contractors, vendors, and any third parties using AI tools within the organizational context.
AI Tools Covered: This policy covers all AI tools used by [Organization Name], including generative AI tools, machine learning algorithms, AI-powered decision-making systems, and other AI technologies.
Definition of Key Terms: To ensure common understanding across the organization, the following key terms are defined:
- Artificial Intelligence (AI): The simulation of human intelligence by machines, particularly computer systems.
- AI Model: A computational model that uses algorithms and data to make decisions or predictions.
- Generative AI: AI that creates content such as text, images, or videos based on input data.
- Machine Learning (ML): A subset of AI focused on algorithms that learn from and make predictions based on data.
- Algorithm: A process or set of rules followed by a computer to solve problems or perform tasks.
3. Policy Statement
Organizational Commitment: [Organization Name] is committed to the responsible development, deployment, and use of AI tools. The organization aims to leverage AI in a manner that benefits employees, customers, and the wider community.
Alignment with Laws and Regulations: This policy aligns with all applicable laws and regulations governing AI, data protection, privacy, and non-discrimination. This includes but is not limited to, compliance with the General Data Protection Regulation (GDPR) and other relevant industry guidelines.
4. Core Principles
Security: AI systems must be developed with safeguards to protect the organization, its employees, customers, and partners from harm or misuse.
Privacy and Confidentiality: All forms of confidential information, including personal data handled by AI tools, must be safeguarded in accordance with privacy laws.
Accountability: Human oversight must be maintained for AI systems. Clear lines of responsibility must be established for the outputs and impacts of AI tools.
Fairness and Inclusivity: AI systems must be designed to treat all individuals fairly, avoid biases, and promote accessibility regardless of background or ability.
Transparency and Explainability: AI systems must be understandable, with clear explanations of how they function, the data they use, and the logic behind their decisions.
Growth and Innovation: The organization encourages the exploration of AI applications that align with company values and contribute to responsible technological advancement.
5. AI Usage Guidelines
AI Tool Evaluation and Selection: AI tools must be evaluated for security, privacy, and compliance before use. The evaluation includes reviewing terms of service, privacy policies, and the reputation of the developer.
Data Handling and Privacy: Confidential information must be protected when using AI. This includes procedures for de-identifying data, obtaining consent, and storing data securely.
Prohibited Use Cases: AI must not be used for unethical purposes, such as employee surveillance, social scoring, or any activities violating human rights.
Use Case Specific Instructions:
- AI in Hiring: Procedures must be implemented to mitigate bias, ensure compliance with anti-discrimination laws, and maintain human oversight in hiring decisions.
- AI in Marketing: Generative AI used for marketing content must avoid plagiarism and copyright infringement.
- AI in Customer Service: AI-powered tools must provide accurate information and escalate issues to human agents when necessary.
6. Accountability and Governance
Roles and Responsibilities:
- Executive Leadership: Ultimately accountable for ensuring ethical AI use across the organization.
- Chief AI Officer (CAIO): Leads AI policy implementation and coordinates AI activities, if applicable.
- AI Governance Board: A cross-functional team overseeing AI initiatives, ethical implications, risks, and policy compliance.
- Department Heads and Managers: Ensure policy adherence within their teams and provide necessary training.
- Individual Employees: Responsible for using AI tools ethically and reporting concerns.
Reporting Mechanisms: Concerns or incidents related to AI use must be reported through established channels, such as an ethics hotline or online reporting system.
Enforcement and Consequences: Violations of this policy may result in disciplinary action, including retraining or termination, depending on the severity of the violation.
7. Monitoring and Review
AI System Monitoring:
- Performance Metrics: Key performance indicators such as accuracy, efficiency, and bias detection must be tracked.
- Audits and Assessments: Regular audits will ensure compliance and assess potential risks.
- Incident Response: A response plan must be developed for AI-related incidents, such as data breaches or biased outputs.
Policy Review and Update Process: This policy will be reviewed annually or when significant changes occur in AI technology, regulations, or industry practices.
8. Acknowledgement and Compliance
Employee Acknowledgement: Employees must acknowledge that they have read and understood this policy. A signed document or online form may be used for this purpose.
Training and Education: Employees will receive training on responsible AI use, covering policy content, examples of responsible and irresponsible AI use, and practical scenarios.
9. Resources and Support
Internal Resources:
- Detailed Guidelines: Specific guidance for using AI tools and handling data.
- FAQs: Common questions about the policy and its application.
- Templates: Checklists for AI tool evaluation and incident reporting.
External Resources:
- Industry Best Practices: Guides and frameworks for responsible AI.
- Research and Publications: Articles on ethical AI and relevant legal developments.
- Training Materials: Online courses and webinars on AI ethics and data privacy.
Contact Information: For support, employees can contact:
- IT Help Desk: For technical assistance with AI tools.
- Legal Department: For guidance on legal matters.
- Ethics Hotline: For reporting concerns anonymously and confidentially.
Developing an AI usage policy is an ongoing process. It is important to stay updated on changes in AI technology, regulations, and best practices. Regularly review and revise the policy to ensure it remains effective and relevant.
Even with a firm policy, it is essential to maintain human involvement in the development, deployment, and monitoring of AI systems to ensure they are used ethically and responsibly.
