Nowadays, the trust of the algorithms in decision-making processes, increased the concerns about transparency in hiring and loan applications. Others argue that it increases the efficiency and objectivity, while others see that this will creat social inequality. This essay will discuss both views before i give my personal precpective.
In the recent years, with the rapid development of the informatic systems, the world has become more reliant on the algorithms in the desision-making, where the employments and loan applications are now selected by the computer, some people see that this will make the inequality in the word because the computer migh be not well programmed and this will make the hiring system become more difficult and the loans increased in a catastrophic way. For example, the loan system which banks are working with migh be programmed by less excperienced people and this will lead to bad calculation for the inetrest of this loans which make creditors cannot pay those debts. That is why those people think that reliance on these systems will affect negatively transparency and social inequality.
On the other hand, those who think that these systems are better for avoiding bias and transparency think that these programs are the best solution for avoiding bias , where people cannot have a pull to taking another competent person just because he has wast, for exapmle: a person who does not have any experience in a certain job and apply for a this job, and another one who has more expreciened in this field apply too for this job, if the first person has wasta will take the place of the second one, but if the algorithm is the one charged of this appliance, it will take the right person to this job. That is why those people think that these systems are better for decision-making to raise the transparency and avoid bias.
To sum up, in the amidst the spread of these conflicting opinions. In my opinion i see that reliance on these system is better for us because those who programmed it are well known by thier high level of education and this will make these systems the best to avoide bias.
