Several fields use artificial intelligence (AI) to support workflows. Such fields include health, engineering, transport, cybersecurity, etc. AI roles also are seen when companies need to collect user data, process it, use it, and store it.

To achieve these functions, AI uses automation processes. Since AI is used to interact with people's data, artificial intelligence privacy is necessary. This article will discuss AI's problems that make regulation a must. It will also discuss why it must be regulated, focusing on the health sector.

The Problems with AI for Data Privacy

As efficient as AI is, the law must regulate its functionalities. This is because AI-powered machines are not perfect and might not be able to function 100% like humans. Here, we shall briefly discuss the problems related to data collection, storing, and sharing with artificial intelligence.

1. Data Inaccuracies

As great as AI is, it has some issues regarding data identification, profiling, and decision making. For example, AI machines sometimes misclassify data or represent them wrongly. This can lead to data errors. Data errors can be incorrect formatting, transcription errors, inconsistencies, etc.

2. Anonymization

Data anonymization is a key concept when it concerns data sharing. AI-driven machines have access to customers' device types, locations, etc. Companies that collect data must hide the owners of these data from the public view. On the other hand, AI machines can be exploited to reveal the identities of those who own certain data.

3. Data Exploitation

Companies can use AI technologies to track user data, how much they share on their devices & networks, where they visit, etc. However, these activities are conducted unknown to customers. Therefore, AI activities must be regulated.

4. Secret Profiling

Though AI is great, some of its applications might hide from AI system designers, customers, and other stakeholders. This might make it difficult for these people to access processed data, interpret it, and use data insights to make decisions.

Artificial Intelligence and Data Privacy in Healthcare

Just as other sectors are experiencing the benefits of artificial intelligence, the healthcare sector has also recorded many successes. One of the major ways AI is of great help in the health sector is that it aids the free flow of information between health workers and their patients.

AI will experience more regulations even in this sector because there are now AI-based health care products. As a result, sellers of these products must adhere to privacy laws governing the healthcare sector and other relevant laws.

Again, technology has advanced immensely, and cyber issues are increasing daily. Therefore, AI processes must be regulated to avoid misusing or mishandling users' data.

In three major points, we shall discuss areas where healthcare practitioners use AI and how they can comply with privacy laws to regulate AI.

1. De-identification

Healthcare practitioners often conceal the identities of their patients if they need to share their data with outside parties. However, de-identification is relative to several privacy laws.

According to the HIPAA (Health Insurance Portability and Accountability Act), de-identification means removing any evidence that could make an expert recognize a patient through their data. Therefore, health officials should de-identify patients' data before storing them in the AI database to ensure the de-identification process is done accurately.

AI still poses some challenges in de-identification. For example, new data sets are added to the database when an AI product expands. These can alter the prior de-identification process and can lead to privacy issues.

2. Vendor Due Diligence

Before sharing patients' data with third-parties, conduct due diligence. Due diligence is a verification process to ascertain if a third party (vendor) is safe enough to entrust with patients' data. In the due diligence process, ensure that you verify how they prefer to collect customer data and their data storage mode.

Also, examine the vendor's mode of data access management.

It doesn't matter if the third party uses AI to collect or store data; if access to data is not properly managed, it could lead to various cyberattacks.

3. Data Security

Data and security are two concepts that organizations must not separate. If healthcare sectors collect data (whether with AI or not), they must invest in facilities and measures to protect patients' data. Healthcare companies must have enhanced compliance monitoring systems, set up access management, and train their staff periodically to secure data.

Artificial intelligence will continue to be regulated to protect customers' privacy. This will help shed its excesses and keep customers' information safe.

Our systems at Zendata are AI-powered, so we understand what it means to need help with AI privacy. So, reach out to us if you need to automate your privacy or start using AI systems for data processing.