---
# System prepended metadata

title: Untitled

---

## Here’s Why Some People Think Google’s Results Are Racist

I also found that Google Images labeled two dark-skinned people as gorillas, that Twitter's image cropping algorithm "prefers" light-skinned portrait areas, that Amazon's AI recruiting algorithm de-weights female resumes, and blurs The algorithm of the photo directly changed Obama's race. Young people aged 15-35 may still have the ability to consciously avoid the prejudice brought about by these algorithmic loopholes, and those who have gradually become "minorities" due to the technological information gap, such as the elderly, children, disabled groups, etc. Rights will be violated. How to protect the rights and interests of these groups and reduce algorithm bias as much as possible is the problem we must solve now. In fact, algorithms and their decision-making procedures are still shaped and written by developers, which means that the values of developers will reflect on the software. For example, if only the face recognition AI sees photos of white people, it will think that people with other skin colors are "not human". This conclusion cannot be said that AI is stupid, but that the distribution of its training data is biased, and more samples are not provided. So if we want to make the algorithm more accurate, we can only review the data from the algorithm training. It’s just that the distribution of the data itself is biased. For example, the number of men in our country currently exceeds that of women. Similarly, most of the Internet users are young and middle-aged, and there are fewer samples of the elderly. There are also differences in the number of men and women employed in the same job. If the algorithm simply "summarizes" experience through data and draws conclusions, it will obviously make those "minority groups" more prejudiced. Addressing prejudice has always started with paying attention to "neglected samples", and the inclusiveness of the Internet is precisely reflected in the attention to these minority groups. I believe that future algorithms will be more humane and systematic.