Artificial Intelligence (AI) has taken over complex tasks that are laborious for humans to execute. It is designed to solve queries and respond to them just as the human mind will. Even though many feared that AI would gradually take up human roles, leaving them unemployed, it has not happened.
As companies use AI to receive consumer data in various industries, it is harmful to neglect data privacy. A 2020 survey by the European Consumer Organization showed that about 45 per cent to 60 per cent of Europeans accept that AI will lead to more violation of data privacy.
Therefore, some people don’t even trust companies who use AI for data collection with their data. To eliminate this doubt, this article will educate companies on why they must use artificial intelligence design to prioritize data privacy and how they can.
Artificial intelligence is a branch of computer science that concerns building smart machines that can perform tasks that require human intelligence. In other words, it is the capacity of a computer-controlled robot to perform tasks that need human proficiency, judgment, and intelligence.
The four forms of AI are limited memory, reactive machines, self-awareness, and theory of mind. Some artificial intelligence tools are smart assistants (Alexa, Google Assistant, Siri, etc.). Other AI tools are email spam filters, web recommendations (Twitter's based on your likes, Netflix's recommendations, Facebook's people you may know, etc.), and chat bots.
We cannot overlook the roles of artificial intelligence in every sector, especially in medicine, technology, commerce, and agriculture, to mention a few. One of the functions of AI in these sectors is data collection. Since data collection is involved, data protection should be prioritized.
To begin with, computer-controlled robots are governed by humans who make sure that datasets input in them are accurate. These humans also supply them with commands on how to use, store, or share received data. These commands are algorithms upon which these robots operate.
Hence, companies must supervise the processes of these robots to ensure they operate within the confines of the commands given. Doing this will help companies assure that customer data are not exposed to theft, unauthorized access, or duplicated to cause errors.
Furthermore, customers are suspicious about the interactions of AI-assisted machines with their data. Customers who are well-informed with data privacy and the consequences of data leak, can be skeptical about sharing their data with your company.
As a result, your company need to educate customers about how much you invest in data privacy and protection. Tell them how your organizational goals align with the provisions of the data privacy laws of your business scope. Besides, you need to highlight the technologies you will use to protect their personal information. This will earn you customer trust.
Automatically, AI-powered websites give room for a non-consent tracking of online behavior. At times, websites customers visit and the content they interact with can cause artificial intelligence to develop data about their ages, locations, etc. Tracking online users to show them contents such as ads thereafter is violating.
To correct this privacy violation, your organization must use artificial intelligence to collect and use only the data provided by customers and not cut corners to gain extra data. If you stick to this conduct, people will be willing to visit your website because they know you won’t bug them with advertisements or unneeded content later.
Using AI to maintain data privacy is the same as eliminating AI privacy violations. Both concepts require a proactive approach. That is, it is best to avoid rather than to prevent. Designing a data privacy measure that cannot be violated relies heavily on companies.
Companies must avoid piling up data through AI. Periodically, your team members should create a schedule on how to filter unused and excess data from the company’s database.Likewise, your management team should discuss customers' privacy concerns. Following that, you can now think about ways to attend to those concerns if you have no solutions on ground.
If you need to set up new AI solutions for data privacy, use the Privacy-Preserving machine learning approach as it avoids privacy violation. Other techniques that avoid privacy violation are differential privacy, homomorphic encryption, etc.
In summary, artificial intelligence has helped and will continue to help several organizations in the data collection process. However, as helpful as the AI is, it violates customers' privacy at certain times. To prevent this, companies must first plan how to secure their customers privacy before collecting their data. This means data privacy should not be an afterthought.
With our modern tools, Zendata can assist you with keeping your customers' privacy through AI.