originalMEMOreport
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School
Seneca College *
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Course
594
Subject
Information Systems
Date
Apr 3, 2024
Type
docx
Pages
2
Uploaded by LieutenantBookBaboon41
MEMO
TO:
IT Department
FROM:
Microsoft Copilot
SUBJECT:
GenAI Use and Confidentiality in the Workplace
I. Introduction
The purpose of this report is to provide an overview of Generative AI (GenAI) and its implications on confidentiality within the IT industry. This report will discuss the challenges of protecting organization, customer, and employee confidentiality when GenAI is used, provide an
analysis with examples, and suggest solutions.
II. Background on GenAI and Confidentiality
Generative AI (GenAI) is a subset of AI that can create, imitate, or modify various forms of content. While it opens countless opportunities to create value and leverage automation, it also raises significant concerns about confidentiality. The use of GenAI tools can raise privacy issues,
as they may share user information with third parties, such as vendors or service providers, without prior notice.
III. Discussion
Challenges Protecting Confidentiality
1.
Limited Traceability and Irreproducibility
: There are deep apprehensions about the limited traceability and irreproducibility of GenAI outcomes, raising the possibility of bad or even illegal decision making.
2.
Data Security and Unauthorized Access
: Another critical concern is data security and unauthorized access.
3.
Insecure Code
: Many developers are turning to generative AI to improve their productivity. However, a Stanford study found that software engineers who use code-
generating AI systems are more likely to cause security vulnerabilities in the apps they develop.
Analysis with Examples
1.
ChatGPT
: The most well-known example is ChatGPT, an AI-powered language model developed by OpenAI. It has introduced several privacy concerns when certain prompts respond with information that includes sensitive data as a part of the responses.
2.
Samsung
: An example of a company that faced challenges with GenAI is Samsung. It banned employee use of GenAI when it discovered the risks after confidential data was inadvertently leaked.
IV. Conclusion and Recommendations
While GenAI offers numerous benefits, it’s crucial to address its potential risks to ensure the confidentiality and security of our organization’s data. Here are some actionable steps:
1.
Use GenAI Apps from Reputable Businesses
: It’s important to understand how the maintainer of your GenAI software approaches security.
2.
Keep Sensitive Data Out of Prompts
: Users should not prompt GenAI applications with
sensitive information, unless they know it will travel over a private connection.
3.
Avoid Training Data Problems or Leakages
: If you are building your own GenAI application, securing your training data is paramount.
4.
Implement Robust Data Encryption and Access Controls
: Implementing robust data encryption and access controls would be a way to address these worries.
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