Updated: Feb 26
In this world of big data, it is essential to make sure that our outcomes and the result of data research are free of any bias. The sole responsibility of a data analyst is not only to prevent bias but also to utilize it most effectively. In other words, it was long ago when software mastered the art of solving Rubik’s cube. With the help of this unbiased data collected, robots developed are efficiently programmed to perform several tasks.
You might be thinking, why is it important to ponder on this topic?
If you think that biases always negatively impact the organization, you are wrong. You must know that bias helps an organization to allow down the focus, and they can derive relevant and exact information with its help.
Unbiased data can help your organization to answer some of the questions that you didn’t even ask. For example, you can even know which salesman was the best performer or which day is the best to sell your product.
Well, the data has not been too important in the last few eras. But, Big data is here to stay, and we are already living in an era that is dependent on data analysis and collection. This data further helps the integration of Artificial Intelligence in systems that help to complete tasks efficiently without the interference of a human.
Why should we care about the bias in data?
Predictive models only see the reality of the world through the data they get. They know of no other model other than the data model. It is very important to remove biases, as the biased models can limit and reduce the credibility of the stakeholders. In addition to this, biased models can also lead to discrimination among some groups and classes of people. Due to all these problems and issues, it is very important for the data scientist to pay attention that they don’t get the bias in data.