ChatGPT, Large Language Models (LLMs), and Data Privacy: What businesses need to know now!
ChatGPT, a general-purpose (AI) Large Language Model (LLM) created by OpenAI, is capable of performing a wide range of digital tasks and has taken the world by storm. The chatbot allows anyone to ask questions and receive responses using natural language. Since the release of this chatbot to the public in November 2022, ChatGPT now has over 100 million users and has received over 1 billion visits to the site. As AI progresses, businesses are leveraging the power of LLMs such as OpenAI's ChatGPT to automate tasks, create virtual assistants, improve customer service, create documents, and generate content. While LLMs, like ChatGPT, offer significant benefits, they pose unique challenges to Data Privacy. There are three key points businesses must consider ensuring they maintain Data Privacy while utilizing LLMs:
Avoid adding sensitive and confidential information to LLMs
Secure your internet-exposed data to avoid ingestion into LLMs
Be aware of legal obligations that apply to third-party uses of LLMs
Avoid adding sensitive and confidential information to LLMs
LLMs like ChatGPT are trained on vast amounts of publicly available text data, including websites, books, and articles. However, this means that any sensitive information inadvertently exposed to the Internet may be incorporated into the LLM's training data. Consequently, businesses must be diligent in keeping confidential information out of LLMs.
To prevent sensitive data from being absorbed by LLMs, businesses should:
Implement strict data access and sharing policies for employees and partners. Only authorized personnel should be allowed to access sensitive information, which should never be shared publicly or in unsecured channels.
Use data anonymization techniques when sharing data with third parties, such as replacing personally identifiable information (PII) with pseudonyms or aggregation.
Avoid using LLMs to process sensitive data, as the outputs generated by these models may inadvertently reveal confidential information. Instead, consider utilizing specialized privacy-preserving AI solutions designed to handle sensitive data.
Secure your Internet-exposed data to avoid ingestion into LLMs
LLMs may inadvertently ingest sensitive information that businesses unintentionally expose to the Internet based on how LLMs gather data from the Internet.
To mitigate this risk, businesses should take the following steps to secure their Internet-exposed data:
Regularly audit and monitor public-facing websites and applications for vulnerabilities and accidental data exposure. Remediate any discovered issues promptly.
Implement strong authentication and access control measures for all web applications, especially those containing sensitive information. This includes multi-factor authentication, role-based access control, and single sign-on solutions.
Use encryption for data in transit and at rest. This ensures that even if sensitive information is accidentally exposed, it is unlikely to be useful to unauthorized parties or ingested by LLMs.
Monitor third-party services and platforms that host or process your data. Ensure they maintain appropriate security measures and have a track record of protecting sensitive information.
Be aware of legal obligations that apply to third-party uses of LLMs
Businesses must also be aware of the legal implications of using LLMs, as they may be subject to various privacy regulations depending on their location and industry.
Some key legal obligations to consider include the following:
Complying with data protection laws, including but not limited to the General Data Protection Regulation (GDPR) in the European Union, the AI Act in the European Union, and the California Consumer Privacy Act (CCPA) in the United States. These regulations mandate strict data handling practices, including obtaining user consent, providing transparency, and allowing users to access, correct, or delete their data.
Adhering to industry-specific regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) for healthcare or the Payment Card Industry Data Security Standard (PCI DSS) for payment processing. These regulations impose additional requirements on businesses to protect sensitive information and may also limit the use of LLMs in certain contexts.
Ensuring that third-party AI vendors, including LLM providers, comply with applicable privacy regulations. This includes conducting due diligence when selecting vendors, reviewing their privacy policies, terms of service, and data practices, and including data protection clauses in contracts and agreements.
Developing comprehensive Data Privacy Impact Assessments (DPIAs) when implementing LLMs. This assessment should identify and evaluate the potential risks associated with using LLMs and outline the necessary steps to mitigate those risks.
Training employees on Data Privacy best practices and the responsible use of LLMs. Staff members must understand these AI technologies' potential risks and legal obligations.
Maintaining an incident response plan to address potential data breaches or privacy violations. This plan should include clear procedures for reporting and investigating incidents and steps to remediate and notify affected parties, as required by law.
As businesses embark upon new ways of leveraging technologies, businesses must always be vigilant in safeguarding sensitive and confidential information while utilizing the benefits of LLMs like ChatGPT. By implementing robust data access and sharing policies, securing internet-exposed data, and staying informed about legal obligations, organizations can harness the power of LLMs without compromising Data Privacy. By doing so, businesses can enjoy the benefits of leveraging new technologies like LLMs while making Data Privacy a Business Advantage.
