How to protect your privacy in the age of AI

Artificial Intelligence (AI) has revolutionised how we interact with technology, providing automation, enhanced decision-making, and personalised experiences. However, as AI systems become more integrated into everyday life, they also present significant cybersecurity risks. Many users unknowingly expose sensitive personal or business data when using AI platforms, leading to potential data breaches, unauthorised AI training, and privacy violations. As AI technology continues to evolve, understanding these risks and taking proactive measures to protect data is essential.

One of the biggest concerns is the unintended collection and retention of user data. Many AI platforms store user input to improve their models, but they often do so without clear transparency. Users who input confidential business strategies, financial details, or personal identifiers into AI systems risk having their data analysed and potentially incorporated into future AI models.

A notable example occurred in 2023 when Samsung employees unintentionally leaked sensitive company information by using ChatGPT for debugging and summarising internal documents. Their data was stored by the AI platform, raising serious concerns about corporate security and data protection.

Another major risk comes from AI models learning from user interactions. Many AI systems are trained on publicly available and user-submitted data, making it possible for confidential information to become part of an AI’s knowledge base. If users unknowingly provide proprietary or sensitive data, others may be able to extract similar details through clever prompts.

OpenAI’s early AI models, for instance, were found to generate excerpts from copyrighted materials and proprietary documents, revealing the dangers of AI training on unverified user inputs. This issue raises ethical and legal concerns, particularly in industries that handle sensitive intellectual property, healthcare records, or financial data.

AI-related cybersecurity faces a significant risk of data breaches due to the vast amount of user-generated data stored by AI companies. Hackers can extract sensitive user queries, private conversations, or confidential business insights. In 2021, a major data breach exposed millions of user conversations, highlighting the need for proper safeguards.

Read also: How to protect yourself against AI data breaches

Ethical concerns about AI transparency and accountability are increasing, with many companies failing to disclose how they use user data for training purposes. This lack of transparency creates uncertainty for users and can lead to biases and inaccuracies in AI-generated content, particularly when handling sensitive topics like legal cases or medical advice.

AI-related privacy violations are a significant concern, as seen in the 2019 Apple scandal where contractors listened to private conversations from Siri recordings, Google’s “Project Nightingale” scandal where they accessed patient records without consent, and a 2023 ChatGPT data leak where users’ conversation histories were exposed, highlighting the dangers of AI-related privacy violations.

To mitigate the risks of data exposure when using AI, individuals and organisations must take proactive steps to protect their information. The first and most crucial measure is to avoid inputting sensitive or confidential data into AI platforms. Users should refrain from sharing passwords, financial details, proprietary business strategies, or personally identifiable information when interacting with AI systems. Instead, AI should be used for general enquiries, brainstorming, or research that does not involve critical data.

Understanding and reviewing AI platform privacy policies is also essential. Before using an AI service, users should verify whether the platform retains user data, uses it for training, or shares it with third parties. Some AI providers allow users to opt out of data retention, an option that should be enabled whenever possible to minimise exposure risks. Additionally, choosing AI tools with strong privacy measures, such as on-premise AI solutions or self-hosted models, can offer greater control over data security.

Implementing AI governance policies is crucial for businesses to protect corporate information. Employees should be educated on data risks and secure AI usage guidelines. Encrypting and anonymising data before AI interaction can enhance security. Privacy-preserving AI techniques like federated learning or differential privacy can improve AI models without exposing raw data.

AI presents immense opportunities, but it also comes with significant cybersecurity challenges. Without proper safeguards, users risk exposing personal, financial, or corporate data to AI platforms that may store, analyse, or inadvertently leak this information.

By understanding these risks and taking proactive measures, such as avoiding sensitive data input, reviewing privacy policies, and implementing strict security protocols, individuals and organisations can protect themselves from AI-related cybersecurity threats.