Algorithms

In Monday night’s lecture, I learned about something I had hardly ever given a thought to, algorithms. Algorithms are used in many areas today, from what you see as your recommended videos on Youtube, to even who gets recommended for a bank loan or car insurance. While it feels quite harmless when speaking about it from a Youtube standpoint, the idea of a non-human deciding if you get car insurance, a loan, or a job, can be scary. Particularly since we do not even know exactly how these algorithms are picking certain people or things or off of what information. The problem with this is that algorithms are often created with an incomplete or non representative data set. This leads to the algorithms gravitating towards a certain pattern, which includes types of people. If the data set originally given to the algorithm when it begins learning is not diverse, it will reject or not identify anything that does not fit what it has been taught to learn. Joy Buolamwini gave a ted talk on something she called the, “coded gaze”. She found that facial recognition technology oftentimes did not even recognize or correctly identify people of color. After conducting a study, she found that black women were the group most often unrecognized or labeled incorrectly by these technologies. This is believed to be because the data set given to the algorithm used to identify faces was probably not given enough images of people of color, therefore it has not learned to recognize them. Prior to this talk, I have never thought of the need for diversity in this type of context. As algorithms become more and more advanced and move into even more parts of our lives, it is essential that they are programmed to function properly, meaning without exclusion. While the creators may not have created this technologies to purposely not recognize people of color, that was the outcome due to the incomplete data set. This is an example of latent bias. Overall, being more aware of the significance of what we are creating and why diversity and fairness in the programming of these technologies is so important will rid these helpful tools of latent bias. Minority groups are already fighting for equality and visibility in so many spheres, making modern technology a place where they do not have to is essential the success and productivity of a society becoming more and more technologically advanced by the day.