5 Key Data Privacy problems related to AI

Posted on: Jan 20, 2023 | 3 mins | Written by: HDFC ERGO Team

5 Key Data Privacy problems related to AI

Data privacy is one of the biggest concerns for anyone at this point. Since most of the data is available online, it makes data privacy is a serious concern. And with artificial intelligence taking centre stage at a rapid rate, it is important to discuss data privacy keeping AI in mind. If you are unsure how both are related, here is all you need to know. Such worries make for a stronger case to buy a cyber insurance policy.

Since data is available almost everywhere and its importance is only growing, there are a few countries that have strong data protection laws in place. These do not explicitly apply to AI but aim at protecting the personal information that is available on the internet. Should any company fail to comply with these laws, they face penalties.

Why is data privacy important from an AI perspective?

There are a number of things that you must consider for data privacy as far as AI is concerned. Here are the top 5 considerations.

1. Adversarial attack

Adversarial attacks on AI systems are designed to confuse the system. A few AI systems, such as image recognition systems, have shown vulnerabilities to adversarial attacks. Since this system relies on learning through thousands of pictures, something as small as a pixel in a picture can alter the course. This can result in the system not working accurately. And if it is designed to identify individuals, it can cause a lot of serious issues.

There is a lot of research that is going on mitigate this risk. As of now, introducing simple attacks on a system can test its resilience and robustness. You must opt for cybersecurity insurance to protect yourself from any such occurrences.

2. Evaluation of systems

One of the biggest concerns individuals and companies have when building AI systems is their evaluation. You must evaluate the system at the end to test for its effectiveness as a system. Usually, accuracy is considered one of the key metrics. However, accuracy might not always be the most efficient way of testing a system.

It is important to look at some of the other factors to test the effectiveness of an AI system. Merely relying on accuracy might not be enough. Companies can focus on other metrics such as Receiver Operating Characteristics, Area under the curve, Recall, Precision, and Specificity.

The presence of cyber insurance can save the day for you in the case of ransomware attacks. Cyber insurance for shoppers can be particularly prudent since such attacks can bring down businesses in a flash.

3. Prediction of black swan events

Black swan events are related to the financial market and negatively impact everyone. And they can be very difficult to predict. Relying only on past data to predict such occurrences can be even more difficult. The stock market is a simple example of it. If you create a model that does not focus on any such market corrections or crashes, the model will find it difficult to predict such events.

Even if you train the model through a market crash period, it is unlikely that the system can predict such an occurrence. Thus, we cannot entirely rely on AI to predict such occurrences. To mitigate such risks, the system should be capable of re-training. If the system does not have any capability of re-training, the system will most likely predict incorrectly.

4. Anonymizing of data

There is a lot of concern related to information that can help to identify an individual. If, in some way, the personal information of an individual can be anonymised. It will resolve the issue. But it can be a bit tricky since the presence of data that can identify an individual is useful for a lot of functions.

Using techniques such as one-way hash can provide relief to some extent as it can anonymise the data used for machine learning. It is a simple technique which converts useful data into a number. And it does so in a manner that the original data cannot be easily read from the number. Though this is one of the most followed techniques, it is not perfect and still leaves a lot of room for improvement.

Another point of consideration is not just the data but also data that can leave individuals identifiable. For AI to work, engineers and scientists need large sets of data. However, it can even contain information about their whereabouts, which can be a bit difficult to handle. All these reasons make data privacy an even more important topic of discussion. Having an adequate cyber insurance policy can protect you from such occurrences.

5. Consistency of system

Another concern with AI is the consistency of the system. Most algorithms have stochastic elements that can change the model's outcome. Different data sets will have different outcomes. The outcome of an algorithm in one’s system can be entirely different from the outcome in the field. This is a concern that a lot of individuals and companies have.

To ensure the consistency of systems, companies and individuals can employ cross-validation techniques. Similarly, if someone is working on a forecasting model, they can use it on past data and see if the system would have predicted the events that have already occurred.

The need for cybersecurity policy

Here are some of the biggest advantages of choosing cybersecurity insurance for yourself.

1. Your data is one of your biggest assets, and they are not usually covered as a part of standard insurance policies. Cyber insurance, on the other hand, protects the integrity of your data and its restoration in the event of a loss.

2. Cyber insurance for shoppers can be more than helpful during any downtimes introduced by the cyberattack.

3. The policy will provide forensic experts who might be needed to recover the compromised data sets.

4. The cost of informing your customers about a breach can also be high. The policy will take care of any such expenses.

5. If any of your systems were damaged or compromised during the cyberattack, the policy could help in repairs or even replacement.

6. The policy will take care of any legal fees arising from such situations, which is quite common.

7. Most importantly, the cost of buying a cyber insurance policy is lower than one might think. They are affordable if you consider the information at risk and the potential downsides of a cyberattack.

Conclusion

Above are some of the key problems that come with implementing AI. If you are concerned with any of these, it is highly recommended that you opt for a cyber insurance policy. The policy will protect you against a lot of potential scenarios. It will also keep you safe from the above AI-related issues if something happens to your data.

Disclaimer: The above information is for illustrative purpose only. For more details, please refer to policy wordings and prospectus before concluding the sales.

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