As AI becomes an integral part of modern business, companies need to assess the risks of inadvertent disclosure of sensitive information.
Public AI platforms, such as ChatGPT and Gemini, utilize the confidential data you include with your queries to train their models.
A skilled user of these public AI platforms can write queries that cause confidential information to be released to the public.
Companies that are undisciplined in the way AI is implemented could find themselves in breach of privacy laws like GDPR, CCPA, and HIPAA, and could inadvertently give away sensitive information to competitors.
The Allure of Public AI Services
Public AI platforms offer a tempting proposition – powerful AI capabilities without the need for significant upfront investment in infrastructure or expertise. They provide ready-to-use models that can process natural language, analyze data, and even make predictions, all accessible via the cloud.
But this convenience comes with hidden costs and risks that can have serious implications for your business.
Understanding Data Privacy Regulations
General Data Protection Regulation (GDPR)
The GDPR is a comprehensive data protection law in the European Union that regulates how organizations handle personal data. It mandates stringent consent requirements, data minimization, and grants individuals rights over their personal information.
Implications: Sharing personal data with public AI services without explicit consent can lead to substantial fines—up to €20 million or 4% of annual global turnover, whichever is higher.
California Consumer Privacy Act (CCPA)
The CCPA enhances privacy rights for residents of California, giving them more control over their personal information that businesses collect.
Implications: Non-compliance can result in penalties of up to $7,500 per intentional violation, not to mention damage to reputation and loss of consumer trust.
Health Insurance Portability and Accountability Act (HIPAA)
HIPAA sets the standard for protecting sensitive patient health information in the United States.
Implications: Unauthorized disclosure of protected health information (PHI) can lead to fines ranging from $100 to $50,000 per violation, with a maximum annual penalty of $1.5 million.
The Risks of Sharing Data with Public AI Services
Data Ownership and Control
When you input data into a public AI platform, like ChatGPT and Gemini, you grant the service provider rights to use that data to improve their models.
When you upload documents and data as part of an AI query on a public platform, you’re potentially giving away this information to anyone who uses these services in the future.
Once this information has been incorporated into the LLM, it’s indelibly part of the system. There is no way to erase information from the LLM.
Inadvertent Data Exposure
Public AI services process vast amounts of data from numerous sources. Even with security measures in place, the complexity increases the risk of data breaches.
Public AI platforms often give assurances that they anonymize your data before they incorporate it into their models. But data anonymization is imperfect and cannot guarantee a breach won’t occur.
The risk of exposing confidential business information, trade secrets, or personally identifiable information (PII) is directly proportional to the amount of times you use these public AI platforms.
Competitive Risks
Platform Risk
Public AI platforms can analyze the data and usage patterns of all their users to identify trends and opportunities.
Companies like Open AI and Google claim to be “platform” companies, offering AI infrastructure on which companies can build their applications.
But companies like Open AI and Google are under intense pressure to monetize their services and there is no guarantee that they won’t gain insights from your data and decide to build a competing application.
This is not a hypothetical risk. In fact, applications are already being gobbled up by these platforms. For example, Open AI’s latest GPT models are nearly as good at writing software as the applications that were built on top of Open AI.
Data Leakage to Competitors
In some cases, data processed by public AI services could indirectly benefit your competitors.
As the AI incorporates your information into its general knowledge base, your competitors will gain access to insights derived from your data, even if the data is anonymized.
Loss of Innovation Secrecy
Your innovative applications and strategic initiatives might become exposed through interactions with public AI services.
Early disclosure of new products, services, or strategies, could allow competitors to counteract or replicate your initiatives.
Mitigating the Risks
Adopt Self-Hosted AI Solutions
By deploying AI models on servers you control, you maintain full ownership and control over your data.
You can eliminate platform risk by ensuring your proprietary information isn’t used to train external models.
Ensure Regulatory Compliance
You can implement AI solutions that are designed with compliance in mind, adhering to all relevant data protection laws.
You can reduce the risk of legal penalties and enhance trust with customers and stakeholders, if you implement your AI infrastructure with this risk in mind.
Implement Robust Security Measures
Protect your AI infrastructure with advanced security protocols, including encryption, access controls, and regular audits.
You can minimize the risk of data breaches and unauthorized access to sensitive information.
Data Minimization and Anonymization
Only use the necessary data for AI processing, and anonymize personal information whenever possible.
You can reduce exposure of PII and align with the principles of data protection regulations, if you are proactive.
A Strategic Approach to AI Implementation
- Assessing Risk vs. Reward: Carefully evaluate the trade-offs between the convenience of public AI services and the security of self-hosted solutions.
- Investing in Secure Infrastructure: Allocate resources towards building or acquiring secure AI platforms that align with your organization’s compliance requirements.
- Educating your Team: Ensure that all stakeholders understand the implications of data sharing and the importance of adhering to privacy laws.
Conclusion
The integration of AI into your business operations offers immense opportunities for growth and innovation. However, it’s imperative to be aware of the hidden risks associated with public AI services, particularly concerning data privacy and competitive intelligence.
By taking proactive steps to secure your data and comply with regulations, you not only protect your organization from legal and competitive threats but also build trust with your customers and partners.
About Verlicity AI
At Verlicity we specialize in providing secure, self-hosted AI solutions that empower businesses to harness the power of AI without compromising on data security or compliance. Our platform is designed to keep your proprietary information confidential while delivering real-time insights that drive success.