As a corporate in-house counsel, you've probably realized that the game has changed. As helpful as AI tools like ChatGPT can be for making your organization more efficient, they can also stir up problems if not handled correctly, impacting your company’s reputation and even getting you into legal hot water.
So, what's the solution? A solid, foolproof generative AI use policy. With the right policy, you can make sure your company is using AI responsibly while dodging any pitfalls.
In this guide, we’re going to walk you through crafting that policy step-by-step. By the end, you’ll have a blueprint for handling AI the right way, so your company isn't just keeping up with the tech curve but doing it in a way that’s ethical and above board.
Why in-house counsel needs to care about generative AI usage
Although AI adoption in organizations has stabilized at around 55%, a significant number of companies are planning to ramp up their AI investments. This growing commitment to AI tech suggests that the applications and challenges of these systems will only become more integral to business operations.
For in-house counsel, this should serve as a wake-up call. As companies further invest, you're likely to see an uptick in the legal complexities surrounding AI use.
But why is it urgent to care now?
Let’s look at a recent incident at Samsung when the company faced a major hiccup after it granted its employees access to OpenAI’s ChatGPT.
Apparently, employees used the tool to solve work-related problems, unwittingly entering sensitive information into the text prompts. This led to three separate instances where confidential data ended up as part of the AI's internal training set.
For example, one employee entered source code to troubleshoot an issue, while another pasted produced code for optimization. In both cases, they risked exposing proprietary information. Samsung had to quickly implement new safeguards and guidelines, revealing just how easily things can go sideways when there's a lack of policy governing AI use.
Impact on legal compliance
If you're the go-to legal expert in your organization, the absence of a clear policy on AI usage places both you and your company in a precarious position.
Compliance isn't just about ticking off boxes; it's about mitigating risks that could have far-reaching implications.
For instance, generative AI can create or manipulate data sets in a way that might contravene existing data protection regulations, such as the GDPR in Europe or the CCPA in California. In the absence of a policy, the odds of running afoul of these and other regulations increase substantially.
And it's not just about avoiding penalties; it's also about maintaining the trust and integrity that stakeholders expect.
Also Read: In-House Legal Guide to Safeguarding Company Data
What are some generative AI uses in the workplace?
Generative AI is already weaving its way into less glamorous but equally important aspects of everyday work life. Here are some of its use cases in a worker’s everyday routine:
- Office automation: To schedule meetings or even drafting basic contracts
- Data analysis: To sift through mounds of data to identify trends, make forecasts, or even flag anomalies
- Documentation: To create reports, memos, and even technical documents
- Internal communication: To create internal memos, emails to staff, or project updates
- External communication: To craft client emails or generate responses for customer inquiries
“With generative AI, you can't really define what the use cases are right now. So, to ensure people aren't coming to legal for every test use case, you can just create a sandbox to let them explore and come to you when they're ready to expose something to the customer or they've got a product behind it. It's going to create a better environment for both your technologists and for you.”
~ Ken Priore, ex-Director of Privacy, Atlassian
Mastering the Intersection of Law, Technology, and Privacy
Also Read: Generative AI for Contract Management: Best Practices
The importance of a generative AI usage policy
“Most organizations are realizing that they should have a policy in place for AI adoption, because, otherwise, there's a risk of customer data or confidential data being put into the public tooling.”
~ Ken Priore, ex-Director of Privacy, Atlassian
Mastering the Intersection of Law, Technology, and Privacy
#1 Setting ethical boundaries
Generative AI brings a number of ethical challenges. It can churn out incredibly realistic content, ranging from marketing materials to internal memos. You, as legal guardians of the organization, have the role of ensuring these capabilities don't veer into creating misleading or fraudulent content. A well-defined policy sets these ethical guardrails in place.
#2 Mitigating legal risks
Without a policy, you're looking at a ticking legal time bomb. Consider intellectual property. The ability of generative AI to whip up text, images, or even code introduces the risk of accidental copyright infringement or trade secret theft. A policy acts as your organization's legal compass, pointing out the acceptable routes when leveraging this technology.
Also Read: Legal Risk Management: From the Playbook of 11 GCs
#3 Standardizing usage across the board
Law isn't just about reacting to wrongs; it's also about creating a conducive environment for fair play. A comprehensive policy offers a one-size-fits-all guideline for AI applications, standardizing its usage across various business units within the organization.
#4 Ensuring compliance
Generative AI can tangle you up in compliance obligations, from data privacy laws to financial regulations. A well-crafted policy can serve as your compliance roadmap.
#5 Addressing bias and fairness
AI's inherent bias isn't just a technological issue; it's a legal headache too. Discriminatory outputs can land you in hot water under various anti-discrimination laws. A well-thought-out policy needs to include steps to identify and correct any bias in AI algorithms, safeguarding against both reputational and legal risks.
#6 Assessing social impact
The societal ramifications of generative AI — think altering public opinion or influencing policy decisions — demand corporate responsibility. Your policy should lay down guidelines on how to evaluate and mitigate the broader impacts of this technology, engaging with both internal and external stakeholders for ethical oversight.
Also Read: Overcoming Roadblocks to the Adoption of Generative AI by In-House Legal Teams
Steps to create a robust generative AI use policy
Step #1: Assess your organization's current AI usage
Start with a comprehensive audit of existing AI applications within your organization. Like a thorough medical check-up, you'll want to identify all the AI tools currently in use, their applications, and potential vulnerabilities.
The audit should cover usage, data sources, security measures, and any previous legal or ethical issues tied to these tools. Get to know the AI applications inside-out, not just as a user but as a legal authority.
Understanding the technology will inform your legal strategies, and may even allow you to identify potential pitfalls before they become actual issues.
Step #2: Get buy-in from key stakeholders
Identify who actually has a stake in AI use within the company. The usual people will be C-level execs like the CEO, COO, and CTO, but don't overlook people like the Head of Data Science, Information Security Officer, and even end-users who will work with the AI tools day-to-day.
Create a value proposition
The pitch needs to resonate with each stakeholder's unique concerns and interests. For tech leaders, it might be about efficiency and innovation, whereas C-suite execs might be more focused on ROI and risk mitigation. So, create tailored value propositions for each group.
Build a persuasive deck or document
Develop a comprehensive presentation or brief that outlines the need for the policy. Make sure to include real-world examples that demonstrate the risks of not having a policy, and use data wherever possible to strengthen your case.
Offer a pilot or trial period
People are more likely to get on board if the stakes seem lower at the outset. So, propose a pilot program to test out the policy on a smaller scale before a company-wide rollout. This gives everyone a chance to see the benefits and address any hiccups without major fallout.
Step #3: Draft the generative AI use policy
Drafting a comprehensive policy for generative AI use is like meticulously constructing a legal argument. Both endeavors require a depth of planning, thoroughness in covering all facets, and a level of foresight that anticipates and addresses issues before they arise.
Create sub-sections for each major policy point:
Data management
Clearly define how data will be collected, stored, and used by the AI systems. List out the types of data that can and cannot be fed into the AI system, along with the permissions required for data access
Ethical considerations
Lay down guidelines for ethical use of AI, especially around issues like bias and discrimination. Be sure to include actionable steps on how these issues can be identified and mitigated
Legal compliance
Discuss the laws and regulations that the AI system must adhere to, especially around data protection and intellectual property. Make sure to include the legal consequences of non-compliance
Governance and oversight
Specify who within the organization is responsible for overseeing AI system deployment, management, and audits
Employee training and awareness
Explain the training programs or awareness campaigns that will be put in place to ensure everyone knows how to interact with the AI systems ethically and responsibly.
Incident response plan
In the event something goes wrong, outline a step-by-step response plan, including the communication chain, corrective actions, and any necessary reporting to regulatory agencies.
While drafting, keep asking, "How will this hold up in a court of law?"
It's the same kind of scrutiny you'd give to a contract or any other legal document. This means citing relevant laws, adding disclaimers where necessary, and ensuring there's no ambiguity that could leave you exposed.
Also Read: What is Contract Compliance? The Ultimate Guide
Step #4: Conduct regular reviews
Don't think of aligning your policy with existing laws and regulations as just ticking a box on your to-do list. Rather, consider it the keystone that keeps your policy from crumbling.
Make sure you consult both federal and state laws where applicable, as well as international regulations if your company operates across borders.
Stay abreast of updates in AI legislation; what's considered legal and acceptable today could be subject to change. To that end, consult regularly with your legal department or designated AI ethics team to ensure ongoing compliance.
Remember, the goal here is to build a robust, defensible policy that not only protects your organization but also stands up in court should the need ever arise.
External review
After you've crafted your policy and believe it's in solid shape, bring in external legal experts who specialize in AI and tech law for a thorough review. They can offer a fresh take and help you refine your policy to make sure it's as airtight as possible. They can also flag any inconsistencies or ambiguities that could be exploited and lead to legal or ethical lapses down the line.
“You should have domain experts review the quality and accuracy of the information before it’s sent to anyone, whether it’s customers, partners or even other employees.”
~ Avivah Litan, Analyst, Gartner
Generative AI at work: 3 steps to crafting an enterprise policy
Step #5: Implement the policy and offer training
You've got your policy ironclad and ready to go. Now, it's time to implement it.
Rolling out the policy
Start by setting up a formal launch date and communicate it well in advance. Give employees a heads-up so they know when to expect the new changes.
It's also good to have an FAQ section readily available to handle any immediate questions.
On D-Day, distribute the policy through multiple channels—email, company intranet, and even print copies for those who prefer a physical read.
Don't just hit 'send' and hope for the best; track who's actually opened and read the policy. Most email software can help you with this.
Employee training
“We know employees often don’t read policies in full, so training can enhance adoption and compliance.”
~ Peter Wakiyama, Partner, Troutman Pepper
Navigating the AI Landscape: Privacy, IP, Policies and More
Training shouldn't be a one-size-fits-all webinar that puts people to sleep. Different departments use AI in varying capacities, so tailor your training accordingly.
Organize department-specific sessions, webinars, and even offer one-on-one consultations for more complex roles. Use real-life scenarios and role-playing exercises to make the training interactive and practical.
Remember, the more engaging and relatable the training, the more likely it will stick.
From here on out, keep the channels of communication wide open. Use regular meetings and internal forums to discuss how the policy is being applied in day-to-day operations. Also, keep an eye on engagement metrics to see if employees are following the policy as intended.
Post-rollout, actively solicit feedback. Create anonymous surveys or suggestion boxes to collect insights on what's working and what isn't. Then, act on that feedback; be prepared to make real-time adjustments to the policy or its implementation strategy.
Step #6: Regular updates and reviews
AI isn't static; it's a fast-moving target. Therefore, treat your policy as a living document that requires regular check-ups.
Frequency of reviews
Decide how often to review and update the policy. A year is a good starting point, but in the world of AI, a lot can happen in a few months. So, in addition to the annual reviews, set up a mechanism for emergency updates.
Maybe it's a legal team Slack channel devoted to flagging up urgent AI developments, or perhaps it's a quarterly mini-review. Either way, be prepared to act quickly if significant legal or ethical issues arise.
Staying updated
Subscribe to AI and law journals to stay in the loop about the latest developments and case studies. Engage with online communities where AI law is discussed; they can be goldmines for tips and best practices.
Attend AI-focused legal seminars and conferences; they're not just for schmoozing and canapes but also great opportunities for hands-on learning and networking.
A good conference to attend would be the SpotDraft Summit: Beyond AI Hype on October 20 at Conrad Downtown, NYC. Join us to dive into the real world of AI, beyond the buzzwords and get to the heart of what AI can really do for your legal team:
- See real-world AI applications
- Meet legal leaders across industries
- Learn to ask the right questions to navigate the AI landscape
- Get expert insights into drafting a foolproof generative AI use policy
Also Read: 7 ChatGPT Prompts for In-House Legal Teams
Generative AI policy template
Crafting a Generative AI policy template can be an invaluable resource for in-house counsel. Here's a simplified Gen AI-use policy template that you can build upon.
Generative AI Usage Policy
Effective Date: [Insert Date]
Last Reviewed: [Insert Date]
Policy Owner: [Legal Department/Other]
Table of Contents
1. Introduction
2. Scope
3. Definitions
4. Ethical Guidelines
5. Data Management
6. Legal Compliance
7. Review and Amendments
8. Training and Awareness
9.Enforcement and Reporting
10. Contacts
1. Introduction
The purpose of this Generative AI Usage Policy is to guide [Company Name]'s responsible and ethical use of Generative AI technologies. It addresses the challenges associated with deploying AI systems that generate content, with a focus on safeguarding the legal and ethical interests of all stakeholders involved.
2. Scope
This policy applies to all employees, contractors, and affiliates of [Company Name] who use, develop, or manage Generative AI technologies within the organization.
3. Definitions
• Generative AI: Any AI system designed to create or modify content.
• Stakeholder: Any individual or entity that can affect or be affected by the actions of [Company Name].
4. Ethical Guidelines
• Do not use Generative AI to create misleading, fraudulent, or harmful content.
• Ensure transparency by marking AI-generated content where applicable.
5. Data Management
• Obtain explicit consent before using personal data for Generative AI tasks.
• Adhere to [Company Name]'s Data Anonymization and Encryption Standards.
6. Legal Compliance
• Perform a thorough legal review to ensure that AI-generated content does not infringe on copyright, privacy, or other intellectual property rights.
• Ensure compliance with relevant laws and regulations concerning data protection and privacy.
7. Review and Amendments
• This policy will be reviewed annually, or as required by legal and technological changes.
8. Training and Awareness
• All relevant staff must complete a Generative AI awareness training annually.
9. Enforcement and Reporting
• Violations of this policy will be subject to disciplinary actions.
• Report any observed or suspected violations to [Contact Information].
10. Contacts
For any questions regarding this policy, please contact:
• [Legal Department Contact]
• [Tech Department Contact]
Feel free to add, modify, or remove sections according to your organization's specific needs. This is just a skeleton to get you started.
Don't just adapt, thrive by attending the SpotDraft Summit
So what's next? Complacency isn't an option, not when the tech landscape is constantly shifting beneath our feet.
This is where SpotDraft comes in. If you're looking to craft that foolproof generative AI usage policy, our template offers a stellar starting point. But it doesn't stop at policy drafting; it brings together the legal and tech worlds in a way that helps you not just adapt, but actually thrive.
Oh, and about that conference—the SpotDraft Summit: Beyond AI Hype—is not just another buzzword bonanza. It's a treasure trove of real-world insights, from AI applications to hands-on legal know-how. If you're serious about staying ahead of the game, this is where you want to be.
