Run Big Data Analytics, AI & ML

Key Business Considerations

Big Data, analytics tools, artificial intelligence (AI) and machine learning (ML) enable the discovery of new insights across many different industries. These kinds of tools help to make our lives easier, and help to solve some of the world’s biggest problems by enhancing decision-making processes.

The benefits of AI and Big Data analytics include:

• Better and more accurate decision-making.
• Enhanced productivity.
• Increased revenue
• Reduced costs.
• Improved customer service.
• Fraud detection.
• More personalised products and services.

Key Legal Considerations

Big Data, analytics, AI and ML:

• Require a large amount of data to accurately train algorithms.
• Need to combine data sets, often collected for different purposes.
• Produce inaccurate, biased results without access to large datasets.

Processing a large amount of data, and combining several datasets is necessary for Big Data analytics and AI to function well. However, there are some issues. Combining these datasets results in a higher likelihood of reidentification risk via the Mosaic Effect. This is because combining datasets can lead to individuals being identified by linkage attacks, that otherwise would not occur if datasets were kept separately.

When using Big Data and AI, the resulting benefits and the protection of personal data must be balanced, so that a practical way of ensuring both can be discovered.

It is difficult to rely on the legal ground of consent when processing Big Data and using AI, because consent must be specific and informed. AI and Big Data analytics tools are so complex, it is not possible to reasonably rely on a customer’s consent, as you cannot be specific enough for the consent to be valid.

This means that you need to rely on Legitimate Interests processing. Legitimate Interests processing provides benefits for data controllers wanting to lawfully use data for secondary processing and repurposing.

However, for Legitimate Interests processing to satisfy legal requirements, you must show that you are using “appropriate safeguards” that reduce the risk of data misuse, such as GDPR-compliant Pseudonymisation.

Anonos Decentralised Data Protection Technology

Traditional centralised data protection technologies, including encryption, anonymisation, static tokenisation, and differential privacy:

• Significantly degrade the utility of data, distorting the accuracy and predictability of the insights you need;
• Fail to deliver effective protection against unauthorized re-identification; and
• Limit the further use of valuable data for non-primary purposes.
  Anonos patented technology uniquely solves the biggest challenge to digital transformation: enabling maximum-utility from data analytics, AI and ML, sharing and combining in real-time - lawfully and ethically. In addition, it ensures that data privacy remains fully protected in decentralized processing, including data from IoT and 5G devices.
• Our premise is that organizations need “Speed to Insight, Lawfully and Ethically.” Without this speed to insight, organizations will be left behind in the highly competitive COVID pandemic recovery market place. On the flipside, without gaining this insight lawfully and ethically, they face risks of liability or disruption to operations.
• Only Anonos BigPrivacy software and API-based solutions embed policy, privacy and security controls into data flows to enable lawful, decentralised processing while preserving 100% of source data value.

Click here to learn what other global companies have proven – that it is possible to retain up to 100% of the accuracy of analytical value when processing datasets protected using patented Anonos Variant Twins®.

Anonos state-of-the-art decentralised data protection technology is superior to traditional centralised data protection because Anonos enables lawful repurposing, distributed secondary processing and data sharing and combining while delivering data utility equivalent to processing unprotected cleartext versions of personal data.