The internet has given us a lot more than just the opportunity to use 22Bet Bonus – it has created more employment opportunities than we ever thought possible before. People in developing countries with a high unemployment rate are now able to provide for their families, and the job market keeps growing. Still, does this mean that there are no unfair hurdles on the way to a job? Are some candidates more favored than others? Well, if they are the most qualified, sure, but what about those that are denied the opportunity in the first place?

Screening

Online applications sometimes include fields that seem innocent at first glance. Terms like ‘legal name’, and ‘digital native’, may seem like they are a formality, but they are more than that. For example, these two terms have already ruled out people with ethnic names and the elderly, respectively.

In China, for example, there have been cases of regional discrimination. Now imagine that you are applying for a job that requires information about your hometown (not residence) and then the company doesn’t even consider your qualifications. Unfortunately, we are often not fully aware that we are being discriminated against.

Discriminatory Algorithms

Facebook was under fire for listing targeted ads. While that, in itself, is not a bad thing (after all, that’s how Facebook and others earn money), the ads in question were job listings that showed signs of gender discrimination. For example, ads about the need for mechanics, engineers, and factory workers were displayed only to young males. Now, it is impossible for a machine to discriminate – it simply acts on the input. It is the matter of the person entering the parameters that led to this.

Amazon stopped itself before getting into hot water. Namely, back in 2014, Amazon tried to develop AI that would do the initial stage of the recruitment process. The company fed the machine with data from previous job applicants in order to come up with a pattern that would reflect the perfect candidate. Unfortunately, pretty soon the negative side of machine learning came out – the AI weeded out all female applicants.

Why? Well, the information fed into the machine didn’t have many resumes written by women. Consequently, AI decided that women were not suitable for executive positions, penalizing resumes that, for example, had the word ‘woman’ anywhere in the body of the resume.

Native Teachers

Here is one piece of discrimination that cannot be written off as faulty programming. There is an alarming amount of language schools online that will not give equal opportunity to native speakers and those who aren’t. The justification for this comes in many forms. Sometimes, it is that the students prefer native speakers. Other times, it is the argument that no one understands the language rules and culture like the native speaker does.

While these claims appear sound, they are unsubstantiated. There is more to teaching a language than just being born in a certain area and developing an accent. It is worth noting that native speakers with no teaching experience tend to be paid more than language teachers with master’s degrees.

In Conclusion

Do online companies discriminate? They do, but no more than brick-and-mortar companies. Wherever there are rules, there will be people that can circumvent them. These companies will continue to appear clean, all the while masking the bias against minorities, the elderly, the disabled, and people of a certain gender.