Employees Are Using Chatbots — Make Sure Your AI Use Policy Works

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Artificial intelligence generative software such as ChatGPT, Bard, DALL-E, Stable Diffusion, and Midjourney (AI chatbots) is everywhere these days, and as in-house counsel, you need to start addressing the organizational risks that arise when your staff starts to use these services against the business objectives to stay competitive. 

Risks might include: 

  • Performance risks, e.g., errors and biases;
  • Security risks, e.g., false, deceptive, misleading, “deepfakes” data and information, and the potential of cyber intrusions into your organization’s IT systems and network;
  • Business risks, e.g., reputational and misalignment with your organization’s values; 
  • Control risks: loss of control of valuable data, inability to detect unintended outcomes, loss of privacy; and
  • Intellectual property, such as trade secret and copyright risks.

Below, we outline steps you should consider when you start developing your organization’s policy on generative AI tools, including chatbot usage.

1. You need to get started.          

Chances are your staff is already using AI chatbots, seeking to experiment with this new and exciting technology, but having little or no appreciation for the various risks associated with such use. As in-house counsel, it is imperative to provide your firm with guidance, in order to manage the competing dynamics of risk versus efficiency and productivity. In this instance, addressing the opportunity proactively is more advantageous than inaction. 

Team member guiding team on how to use AI app.
Use proper guidance with your team to safely manage and mitigate any potential risks associated with AI chatbots.
hProStockStudio / Shutterstock.com

As in-house counsel, it is imperative to provide your firm with guidance, in order to manage the competing dynamics of risk versus efficiency and productivity.

2. Educate top management.

At this point, there have been enough articles published in popular media imploring top level management to be aware that AI chatbots are everywhere. The reality that people are probably already using the technology in your organization, or the risks that are particular to your operations, may not be top of mind. You need to educate them on the specific risks your organization faces if guidance is not given. Prepare talking points that address each of the following areas (almost all of which are probably applicable):

  • Privacy
  • Data and trade secrets security
  • Copyright and trademark issues
  • Bias contained in AI (e.g., HR products and activities)
  • Coding risks
  • Breach of contractual obligations regarding data use and protection
  • Violation of regulatory obligations (e.g., HIPAA)
  • Errors/output integrity
  • Cybersecurity enhanced risk

This education process should extend to your board or your board risk management committee to assist in their oversight roles and address changing disclosure regulations over cybersecurity practices.

3. Acknowledge why people want to use AI. Commit to examining risks and rewards.

It is very easy for lawyers to talk about risk without acknowledging that there are some real potential productivity gains. Rather than starting with a position of “no usage ever” (although an immediate pause on usage could be reasonable), commit to examining the use instances and working with internal departments to determine what the proper balance of risks and rewards are for your organization. Try to figure out if there are ways to mitigate risks. A number of AI products are starting to roll out enterprise solutions with greater security features. 

4. Assemble a team to examine the organizational risks and needs.

This is not the time for legal to develop policy in a vacuum, and you will need to work closely with various internal constituencies depending on your company’s profile, including your IT team, developers and product teams, HR, finance, investor relations, business generators, risk management, and others.

You should engage people at all levels (and ages) of the organization to find out what is actually happening (or desired) before you can develop a policy that can be actually implemented. The enterprise-wide effort will be more successful if you seek to engage a broader base of internal stakeholders who may be thinking about how to use this technology to advance their business objectives. 

Team communication and project management concept.
It is in the best interest of in-house counsel to engage with the entire organization to decipher risks and needs before moving forward with developing an AI policy.
GoodStudio / Shutterstock.com

You should engage people at all levels (and ages) of the organization to find out what is actually happening (or desired) before you can develop a policy that can be actually implemented.

5. Review regulatory and contractual obligations particular to your organization.

Although everyone may want access to new technology, there may be regulatory barriers or prohibitions. For instance, you may not be able to use an AI chatbot and be compliant with HIPAA health privacy regulations. You might be subject to employment law violations if you make certain HR decisions based on biased AI technology; e.g., recently enacted regulations in New York City. GDPR might prohibit you from allowing PII (personally identifiable information) to be used for training AI chatbots. Make sure you consider the regulatory frameworks that might impact your company’s usage.

6. Determine who will “own” the policy.

To implement a policy, you will need support from top level leadership of the organization, with an understanding of who will own and be responsible for the policy. Will legal, IT, security, compliance, or some other group created during the policy drafting phase be responsible? Like any new company wide process, consider test driving it across various departments and at various levels in the organization. Seek feedback and embed suggested improvements.

The situation will be dynamic and your AI team should monitor ongoing developments and impact in order to address possible policy changes. For example, if you are allowing usage in certain instances, how do you obtain permission? Who will they contact if they want a use instance not explicitly addressed in the policy?

AI monitoring.
In the event of a possible policy change, an AI team should always be up to speed and aware of any ongoing developments. VectorMine / Shutterstock.com

Like any new company wide process, consider test driving it across various departments and at various levels in the organization. Seek feedback and embed suggested improvements.

           

7. Create a policy for your vendors (new and renewals).

It is not just your staff who can create risk for your organization by using generative AI tools. Your vendors are likely using the technology as well, possibly creating risk for your organization. For example, a number of organizations are updating their terms of service, seeking consent to “train” their technology when you use their products. What does “train” mean? What will the vendor do or use?

You should also consider contractual obligations in vendor contracts to explicitly prohibit use of any company data or information to be used for the vendor’s training or other business objectives. Asking questions about how a vendor will use your company’s data and information should be part of the normal vendor due diligence process, and AI use will be no exception.

8. Acknowledge that your policy is going to be interim.

Once you get your policy in place, do not imagine your work will be done. AI technology is evolving too quickly for anything to be permanent. Resolve to keep learning, evaluating and be ready to change.