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July 9, 2024The Hidden Risks of AI Training on Your Data
A recent study by Wing highlights a concerning trend: 70% of the top 10 AI applications may use your data for training their models (The Hacker News). This practice poses significant risks to businesses, including potential exposure of sensitive information and intellectual property (IP). The fine print in Terms & Conditions often hides these data usage clauses, leaving security teams scrambling to maintain control and protect proprietary data.
Key Risks and Real-World Examples
When AI applications use your data, four primary risks emerge. First, the leakage of IP and sensitive data can inadvertently reveal proprietary business strategies and trade secrets. Second, data utilisation may improperly align interests, where data from a CRM application, for example, is used to improve AI features that competitors could also benefit from. Third, sharing data with third-party vendors increases the risk of breaches, especially if these vendors lack robust data protection measures. Finally, compliance concerns arise as varying global regulations impose stringent rules on data usage, leading to potential legal and reputational damage.
Navigating Data Opt-Out Challenges
Understanding which data is used for AI training is crucial for managing risks. However, inconsistent and scattered opt-out mechanisms across SaaS applications make this task difficult. Some platforms bury opt-out options in service terms or privacy policies, while others require direct communication with the company. A centralised SaaS Security Posture Management (SSPM) solution like Wing can streamline this process, providing alerts and guidance on opt-out options, ensuring compliance, and protecting sensitive information from AI training models.
(Visit The Hacker News for the full story)
*An AI tool was used to add an extra layer to the editing process for this story.