iThis article is the third article in our three-part series focused on data privacy considerations related to the use of artificial intelligence (AI) and machine learning. Our first article highlighted privacy topics related to collecting personal information via AI applications, transparency, and the challenges associated with regulating AI. The second article focused on considerations for customer-facing AI applications (i.e., external facing) whereas our third article focuses on privacy topics related to employees’ use of AI (i.e., internal facing).
AI in the Workplace
The rise of AI technologies in the workplace has opened up new opportunities for businesses to streamline operations and improve efficiency. However, alongside these advancements come potential privacy concerns, especially when employees interact with AI platforms that process personal data. This article explores practical privacy solutions for employee-facing AI technologies, with a focus on the widely-used ChatGPT platform.
As more organizations adopt AI-powered tools like ChatGPT, it is important to understand the potential privacy risks. According to Hayes Connor Solicitors, employees inputting sensitive data into ChatGPT platforms raises privacy concerns, as these platforms learn from the data they process.[1] To address these concerns, businesses must implement privacy solutions that protect employee and customer data while allowing AI to function effectively.
Generative AI Pilot Program
One approach to mitigating privacy risks is to implement an AI pilot program. According to Debevoise's Data Blog, organizations should consider launching a generative AI pilot program as it allows businesses to assess the risks and benefits associated with AI technologies.[2] During the pilot phase, organizations can analyze potential privacy issues, identify vulnerabilities, and develop a comprehensive strategy to address them. This helps to ensure that any data privacy risks are mitigated before the AI technology is rolled out on a larger scale.
Acceptable Use and Data Handling Policies
Organizations should consider creating clear data handling policies that outline how employee and customer data is managed, processed, and stored. By providing guidelines for employees to follow when interacting with generative AI technologies, businesses can minimize the risk of inadvertently sharing personal data with the platform. These policies should also include guidelines on how to handle data breaches and ensure that employees are aware of the potential risks and consequences of mishandling personal or sensitive information.
Access Controls and Anonymization Techniques
Another practical solution is to limit the access that generative AI technologies have to personal data. By creating access controls and restricting the platform's ability to process specific types of information, businesses can reduce the risk of personal data being exposed or misused. For instance, organizations can implement role-based access controls that limit the data employees can input into the AI platform based on their job function and the platform's intended use.
Employing data anonymization techniques can help protect personal information without compromising the functionality of AI technologies. Techniques like data masking, pseudonymization, and tokenization can be used to transform personal and sensitive data into a format that cannot be linked back to an individual, reducing the risk of privacy breaches.
As generative AI technologies become increasingly integrated into various aspects of our lives, the importance of privacy protocols for individuals interacting with these platforms cannot be overstated. Implementing pilot programs, clear data handling policies, limiting access to personal or sensitive data, and employing data anonymization techniques are crucial steps in addressing privacy concerns while reaping the benefits of AI technologies.
[2] "Does Your Company Need a ChatGPT Pilot Program? Probably", Debevoise Data Blog, 2023
