AI and Data Sets

The one aspect that Miss Kass’s lecture didn’t acknowledge that I believe uneducated people on the subject of AI, Machine Learning, and Deep Learning, is that companies save all of your data to then be analyzed. Each purchase or click on a website is stored in your specific file, and that is the only way AI is able to function, data is the necessity. After taking Computer Science I did a presentation of Facial Recognition Software and how around the world it impacts everyone. In almost every major city there are facial recognition cameras watching over every street. This means our rights to privacy are stripped from us and where we are is constantly being tracked by governments and anyone who has access to that data. 

The data sets are the biggest issue with the Facial Recognition software, as the data sets do not reflect equality around the world. This is a problem in other fields like psychology and medication. In psychology, the data sets of experiments are largely college students who are studying psychology 101 and are being apart of an experiment conducted by upper-class students or professors. This is dangerous because it is only a broad sample of subjects in comparison to the rest of the world. While medication testing is mostly done on white males, and this is not safe for teenagers, the elderly, and women, for medication effects everyone differently. These are both similar to the field of facial recognition and how important data sets are in order for the information to be an accurate set of data that reflects the rest of the world. 

How google results change is also scary. Having machine learning active takes away an individuals right of choice and decision making, taking away one's rights to free choice. While in life the way to better your understanding of a topic is to see the opposition and through learning and discussion you hear their side to better your own understanding of an issue. Like at Govs we are a diverse community with many different kinds of beef which better our education due to that fact. Yet now through google and other searching sites that experience is blocked.

Another major problem is that women are simply not in the field of computer science. Any field that is dominated by a single gender will not reflect neutral work, as seen with the code for facial recognition, as it fails to recognize race and gender of females and darker skin complexion.