Data management
Data management plays a vital role in forming the ethics for the use of data in any industry or market. Nowadays, Data privacy and its purpose are becoming essential because it is full of individual stories of a person. If it gets into wrong hands, then it can be manipulated and will bring disaster to the economy and environment. Some set of rules should be made and follow so that data can be appropriately managed and which can help the economy and sustainability. It is an administrative process which includes many stages, and it is required to ensure to put some restrictions and permission on the access of data.
It can be classified into five parts:
- If the data is private, then it should remain private
Privacy does not mean security of the data; it means if the data is private and the customer has accessed the data and does not allow to share it when any other. Then Privacy should be maintained, and it should not be sold to other business.
- Confidential use of shared data
More restrictions should be there sharing of data – as third-party companies shared the data to the medical, financial or locational companies more strict rules should be made so it cannot be manipulated and used for unnecessary crime. It should be shared in trusted intermediaries with the limited number of the known partner.
- Data should have a transparent view of the customers
Customers should know how their privacy is being used and shared to further companies or third party for some research or any economic growth of the company. There should be some flow in managing the data which can be presented in a well-mannered form to the customers so that they can believe that their information is not used for any misdeed.
- Help in making predictions
By using different AI techniques, now its possible to make the predictions by using the previous steps which can be processed by AI and convert it into making decisions with a probability of growth. So some it needs to identify which inferences should be allowed and which should not.
- Data should not be institutionalized unfair biases
Data should not be used for racism or sexism by the companies. By applying a different kind of Machine learning algorithm, it can result in unconscious biases in the form of population.