Framework of an
Acceptable Use
Policy for External
Generative AI
Illustrative for Adaptation

September 2023

Contents
INTRODUCTION

3DATA PROVIDED TO GENERATIVE AI SYSTEMS

5

CONFIDENTIALITY

5RESPONSIBILITY

7

ACCESS

8

MONITORING

99DATA RECEIVED FROM GENERATIVE AI SYSTEMSACCURACY

9REPRESENTATION AS THE EMPLOYEE OR COMPANY11ATTRIBUTION

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Introduction
Trust underpins the financial services industry. Customers trust financial institutions with theirfinancial data and transactions. Companies trust their employees to make decisions every day
with the company’s data, reputation, and more. Financial firms trust each other to honor commitments in trades, transfers, and other transactions.
To maintain this trust, financial firms design and implement policies and controls that enable
employees to make good decisions and adhere to relevant regulations. One type of policy is
known as Acceptable Use, which outlines good risk management and security practices on
specific systems and technologies.
Generative AI is one such technology that has the potential to revolutionize every industry. It
is a powerful driver of optimization, efficiency, and cost reduction as well as the basis for new
business lines and products. It will be integrated into our companies at all levels. But there aremany risks that come with it, and financial firms must be proactive in managing internal adoption
and use of generative AI.
This framework is a guide for firms to design their own Acceptable Use policy for external generative AI. Given the rapid development and adoption of generative AI, we hope this guide serves
as a helpful tool for firms to upgrade their security and risk management policies to incorporate
safe and responsible AI use into their security programs and beyond.
Some argue that financial institutions (FIs) should take a stringent approach and block external
generative AI systems, as these are still nascent, untested, and unvetted. Others believe that
employees may find workarounds to blocking these systems, and so it would be more productive and indeed, more secure, to educate employees on how to safely use them. This frameworkoffers policy guidance on both permissive and stringent approaches, allowing firms to decide
the right balance for themselves.
What follows is a short explanatory text followed by sample policy text (labeled “Policy
Guidance”) that firms can adapt for their own use as they see fit.

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Policy Guidance
Introduction
This policy defines requirements for the acceptable use of external generative AI services.
This policy describes management’s directive to:> Ensure protection of the company’s intellectual property> Ensure that use of these systems reflects the culture and ethics of the company, as

well as the regulatory, privacy, and legal obligations of the company and its employees> Establish a baseline of proper use of these systems for all employees> Ensure compliance with all applicable laws, rules, and regulations, including privacy

requirements such as General Data Protection Regulation (GDPR)> Ensure compliance with the terms of use of many generative AI systems (especiallyattribution and lack of copyright protection)

The policy assumes as an overarching principle that data loss risks are present in the useof generative AI systems, like any other third-party system.
This document applies in all manners of consumption, such as via API, UI, or any otherinterface, as well as in all manners of access, including both corporate and personal devices.

Policy GuidanceDefining External Generative AI
This policy is for generative AI services running external to the firm (as opposed to services
hosted within a firm), irrespective of whether the firm is using the paid or free versions of
the services. Examples of external generative AI include, but not limited to, all versions of:• Text (and related) generation, such as large language models (LLMs), including:> OpenAI’s ChatGPT> Microsoft’s Bing with GPT integration> Google’s Bard

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> Microsoft O365 integration with OpenAI CoPilot> Microsoft GitHub CoPilot> BloombergGPT• Image generation, such as latent diffusion models (LDMs), including:> Stable Diffusion> Midjourney AI> OpenAI’s DALL-E• Other multimedia creation tools (e.g., “deepfake” tools)

Data Provided to Generative AI Systems
Confidentiality
Currently, most external generative AI systems use queries for future training (although somesystems allow opt-outs). The service may preserve the queries, which hackers could breach andrelease. Queries with sensitive data put companies at significant risk.

Policy Guidance
Permissive

Stringent

Employees must take care to preserve
the confidentiality of the company’s work
products above any uses of generative AI
systems. Employees must adhere to thisand all company policies and standards.

Employees must respect the confidentialityof the company’s work products above any
uses of generative AI systems. Employees
must adhere to this and all company policies and standards.

Employees must consider:

Employees must not share:> The impact, importance, or uniquenessof the company’s intellectual property(IP) before sharing it. Consider genericizing and stripping any company> The company’s internal IP, especiallyproprietary, copyrighted, or related IP> Any data having Personally Identifiable| Framework of an Acceptable Use Policy for External Generative AI

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references, especially if the data isproprietary or copyrighted> Limiting or obfuscating the data if it

Information, Nonpublic Personal Information, or other data under the purview
of regulators or similar entities.1

has Personally Identifiable Information (PII), Nonpublic Personal
Information (NPI), or other data under
the purview of reg-ulators or similar
entities> Any information that if exposed pub-

> Repurposing or reducing extraneous> Any information that someone may

information that if exposed publicly:> Might tarnish the reputation of thecompany> Could open the company to regulatoryor legal action

licly might tarnish the reputation of thecompany, or information that would
open the company to regulatory or
legal action
use to reverse engineer or give accessto IP or systems> Any information that if exposed publicly

could reveal the company’s strategy
and/or would be in violation of safe
harbor statements> May allow reverse engineering> May give access to IP or systems> A reminder to not share (in Generative

AI or any form externally) any information that, if exposed publicly, could
reveal the company’s strategy and/or
would be in violation of safe harborstatements

1. This can be adjusted if, through contractual agreements, the firm has the keys to their data vault andcan protect the data held at the service.

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Responsibility
Although generative AI has the power to increase cyber crime through convincing mimicking
of existing communications, excellent translation capabilities, deep fake images, audio, andvideo, ease of finding code vulnerabilities, and much more, the kinds of threats still are the sameas when using other third-party systems. For instance, phishing emails may become more
personalized with generative AI, but the way these enter the organization still is the same. The
responsibility to safeguard against malicious activity when using generative AI is therefore
same as general internet usage to protect IP and other concerns such as compliance.
Policy Guidance
Permissive
Generative AI systems are no different fromany third-party system. They bring massive
benefits, if used responsibly. They can doharm too, so employees need to take careof the queries and inputs to these systems.
Employees should consider the following
as part of that responsible use:
> That the accuracy of these systems isstill suspect; they have been known to“hallucinate” (see “Accuracy” section
below)> Remove references to IP, NPI, PII> Whether the firm’s name needs men-tioning> If sharing code, genericize any variable

names> Genericize the request, making it harder

to attribute back to the firm

> Not share any of the aspects men-tioned in the confidentiality section

Stringent
Acceptable use of these systems is still
unclear, given the accuracy of the output(see “Accuracy” section below). To usethem responsibly, at a minimum, employees must genericize the queries or inputs
and remove any reference to the company or its IP, akin to asking a question oncommunities such as Stack Overflow or
Discord.2
If allowed to access these systems in alimited way, employees should:> Remove any references to IP, NPI, PII> Remove any reference to the firm
> If sharing code, genericize any variable

names> Genericize the request to be as abstract

as possible> Not share any of the aspects men-tioned in the confidentiality section

2. Other policies may prohibit the use of Stack
Overflow and related systems though, and if so,
those prohibited use cases should also apply togenerative AI systems.

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Access
This section elucidates the range of options forcontrolling access to generative AI systems,
including guidance for which staff and fromwhat devices they can access, as well as
whether to use corporate identities
when using them, given that it ispossible that such queries become
public. Also, firms should publish alist of approved generative AI systems, based on its assessment of
the vendor’s compliance with laws,
rules, and regulations. (FS-ISAC
AI Risk Vendor Risk Subgroup is
working on a questionnaire to
aid this assessment.)

Policy Guidance
Permissive
All employees can access approved external generative AI systems from desktops,
mobile phones, and similar corporate
devices. Firms must limit access to generative AI systems from production servers
when not part of a service or application
workflow.

Stringent
Employees must not access generative
AI services from any corporate device orserver.
Employees must not use their corporate
identity (email or related) as a login tothese systems.

Employees can use their corporate identity (email or related) as a login to thesesystems.

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Monitoring
Monitoring is a common section in Acceptable Use Policies, trusting but verifying compliancewith the policy. Firms need to consider what they intercept, monitor, limit, etc.
Policy Guidance
Permissive
The company has the right to monitor
the use of these systems per applicablelaws and regulations. Management may
occasionally verify that the use of thesesystems adheres to the directives outlinedin this document.
Users should inform their management atonce if the use of these systems may haveinfringed on the standards in this policy for
acceptable use.

Stringent
The company will monitor the use of thesesystems per applicable laws and regulations. Management will ensure that the useof these systems adheres to the directives
outlined in this document.
Users should inform their management atonce if the use of these systems may haveinfringed on the standards in this policy for
acceptable use.

Data Received from Generative AI Systems
Accuracy
Generative AI systems are far from perfect, especially with fact-based output. These systems
may “hallucinate” when their answers appear convincing but are completely wrong. Users should
not rely on their accuracy.
Incorrect answers can cause severe issues for companies. For example, inaccurate instructions
for IT administrators may lead to data loss or other system damage. Distortion of statistics orother facts may lead to employees making public claims or key decisions based on erroneous
information.
Other considerations:> Since generative AI may not be current on legislation, answers on accounting, tax, or otherlegal considerations may be inaccurate> Generative AI cannot know organizational culture or intricacies of industries, leading tosuggestions that may do more harm than good.

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> Depending on how users ask the questions, generative AI may not apply GDPR or otherapplicable laws to the answers given.

> Employees can use these systems for nefarious purposes, such as proxy avoidance,

unapproved network uses, or manipulating financial services transactions for personal gain

Policy Guidance
Permissive
Given that the accuracy of generative AI
is imperfect, the firm strongly encourages
employees to manually verify the output
before use. Employees should ensure theoutput does not lead to:> Fraudulent, destructive, and/or inap-

propriate system usage> Poor, biased, and/or unethical busi-

ness practices or decisions> Reputational and/or financial harmof the company

The firm also recommends employees:> Ensure compliance with applicableregulations, laws, and acceptable fairuse of others’ copyright protections> Avoid circumventing or bypassing

this or other company policies

Akin to any other third-party solution, if thegenerative AI system results seem suspect,
it is best to verify and consider alternative
sources.

Stringent
Employees must assume the output
accuracy of generative AI systems areimperfect, and therefore must manuallycheck the accuracy of the output (especially with regards to fact-based queries).
Employees must check that the output
does not lead to:> Fraudulent, destructive, and/or inap-

propriate system usage> Poor, biased, and/or unethical businesspractices or decisions> Reputational and/or financial harm of

the company

Employees must also:> Ensure compliance with applicable reg-ulations, laws, and acceptable fair useof others’ copyright protections.

> Not circumvent or bypass this or othercompany policies

When there is doubt around the accuracy,completeness, or copyright protections of
the output from a generative AI system,
the employee must not use the output
and, instead, rely on other sources of
information.

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Representation as the Employee or Company
External generative AI systems often require users to give attribution to the system for any output,
for example, in the Open AI’s Terms of Use. Knowing this stipulation, it could:> Invalidate some uses of the output for proprietary or copyrighted work
> Open users to copyright violations> Open users to conflicts with other firms potentially using the same or similar output

As generative AI becomes increasingly powerful, organizations will need to reevaluate what they
consider “acceptable” use of such systems. No policy document, permissive or stringent, cancover all situations. For example, a manager short on time uses a generative AI system to write
an employee appraisal. That employee does not like their appraisal and files a complaint. Since
an actual human did not write the appraisal, there is good reason to believe that the employee's
grievances would be upheld.
The onus is on the user to attribute the output correctly.
Policy Guidance
Permissive
There are considerations for employees
before they use generative AI output as
their own:
> In internal documents on behalfof the employee (emails, HR documents, et cetera.), employees must
remember that the output stands
for them. Employees must take careto remove sensitive, proprietary, or
confidential/secret company information. Employees should also
check whether the output is in thedesired tone and language

Stringent
Employees must not use the output of generative AI systems to stand for activity they
undertook. Employees must specificallynot use the output of generative AI to:> Write any internal documents onbehalf of the employee (emails, HR
documents, et cetera.), especiallythose having sensitive, proprietary,or confidential/secret company information> Write any external communication> Employees must note that there isgreater attribution, legal, ethical, andcopyright concerns in external communications and perform stronger
reviews in those uses

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Attribution
Several commercial generative AI tools require attribution in their Terms of Use. Given that users
often do not attribute output to AI, firms may be liable for violations of these terms. Consumers ofthese systems cannot (typically) treat the output as their proprietary IP, so use of this output can
only advise and guide users.
Specific for programming code uses of generative AI, the input to the base of many of these systems is open-source software (OSS) code found in common repositories. Some firms limit the
open-source licenses used in their products and need to verify that the output comes from an OSS
license they approved.
While there are tools that try to detect if a generative AI system developed a specific output, they arenot (yet) dependable enough to find whether an employee’s work is original or not. This
document assumes you cannot use such tools, but that may change.

Policy Guidance
Permissive
Any output from generative AI systems
must follow the policies of the various
external systems, specifically where theyrequire supplying attribution to thosesystems.
Employees should take care that the useof generative AI systems does not compromise the firm’s external reputation, evenwhen supplying attribution. Additionally,
employees must respect and honor any
applicable open-source licenses.

Stringent
Any output from generative AI systems
must follow the policies of the various
external systems, specifically where theyrequire supplying attribution to those systems. The firm will block or limit the use of
systems that require attribution.
Employees must not engage in any use ofgenerative AI systems that could compromise the firm’s external reputation, evenwhen supplying attribution. Additionally,
employees must strictly follow any applicable open-source licenses.

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