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Protecting Your Data Privacy — Part 4
- AI, the Internet of Things, and Post-Quantum Encryption are set to have a significant impact on data privacy.
- AI models are only limited by the size of the datasets they’re trained on, meaning companies are scraping all publicly available sources of data to feed their models.
- AI can process vast amounts of data in seconds and identify anomalies that may be too subtle for human attention.
- Smart devices connect to the internet, collect data, and may share it with third parties, so it’s important to review privacy settings and limit data collection.
- Post-quantum cryptography is still under development, as current encryption standards are expected to become vulnerable with the arrival of new quantum computers set to arrive by 2030.
- Harvest now, decrypt later is a strategy that bad actors may use to store encrypted data now and decrypt it in the future with the arrival of new technology.
- Organisations, governments, and businesses already take precautions against Q-Day attacks, but consumers can also stay informed and adopt post-quantum encryption standards for safer products.
- Opting out of having personal data used to train AI is an available option on social media platforms and some dating apps.
- Privacy policies are evolving quickly in response to AI, but currently everything posted publicly can be used to train AI models.
- Limiting post visibility settings to “friends” or “followers” only is a way to protect personal information (for now).
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