Synthesis Report

 Algorithms - Many people know what it is, others may not. Most know it from the internet, from the various social medias and online platforms. In this Synthesis report, which encompasses various topics that we had studied in this semester. I will talking about the 3 following topics, that all relate to Algorithms: Algorithmic Bias, Algorithmic Oppression and the concept of having a "neutral" algorithm.

Algorithms: a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. This is how google defines it. We use it in our daily lives even without knowing about it, and are impacted by it on a daily basis. Everything from social medias to even grocery/shopping centers uses algorithms in order to create a "better" outcome for most people. However, most of the time the algorithm is left to their own devices and ends up being "accidently" biased towards certain minorities or groups of people due to various factors that play into it. This is why as much as people try to claim that they have a "neutral" algorithm that doesn't have a preface of certain types of people, it is most likely not the case as even at the very least, each of these big companies have a target audience, and having the algorithm be biased more towards this "target" is almost always in the companies' best interest. And when these problems does get exposed occasionally, companies try to find excuses such as "Oh there was a glitch in the system" or "Oh we haven't patched that yet" and end up not fixing anything at all.

Before we get ahead of ourselves, we must address the main things that are caused by having algorithms like this. Firstly being Algorithmic Bias. This is when the Algorithm is well, biased towards certain groups and tends to favor them over the others. This can be seen as sometimes promoting relevant sources of media to them, or showing context with people of said biased groups more. Often, websites such as YouTube or Google will based this bias towards the user based on the previously searched content and curate it towards them based on what it predicts the user's type to be and reference what other people of the same type look up. However, this can be flawed quite a bit as it can call under trying to stereotype entire races of people wanting to see the same type of content; In even worse cases, the algorithm will be so biased that it promotes a certain type of content to everyone and anyone regardless of the type of content it is just due to bias alone, which can sometimes cause it to overshadow over what people are actually trying to search for. In previously mentioned examples (from my other blogs), when search for phrases such as "Why women are" in google, the algorithm will be biased towards the most popular search results, which ends up stereotyping a lot of people and show sometimes rather offensive results. Bias doesn't just exist towards races, but even genders and age, and it isn't limited to what kind of bias it has, whether it be biased on what kind of content it shows, or biased towards what users it has. This leads into our next point of interest: Algorithmic oppression.

Algorithmic oppression is kind of like the opposite of bias - it's when the algorithm refuses to show certain forms of content because it relates to a certain group of people that whoever made the algorithm deemed "not good" for other people to see. This can also range widely from not giving certain users of this undesired group access to all the content, to not recommending or showing media content relating to said groups. This can result in most people not knowing of significant events that had happens with certain large groups of people just because it was deemed "mathematically wrong to show". And these matters aren't long gone either, they're still happening today almost on a daily basis. And although as someone who's seen and worked on algorithms before has to admit, it is not an easy fix; I'm not even sure if making a truly "neutral" algorithm is even possible, but more often than not companies aren't trying, because to them as long as it rakes in money they don't really care.

To put all and all together, this Synthesis report's overlapping theme is Algorithms. Algorithms can be an important tool for many, however if we don't address the issues of having algorithmic bias and algorithmic oppression in the modern day and age, it will eventually lead to social distress and disasters - As something as important and integral to the internet being able to oppress and give more bias towards certain groups is just wrong. Bias and Oppression on this front go hand it hand, you promote 1 thing and you try to hide the other thing, this is why I believe both of these topics intersect with each other - As long as one exists, the other will to in some way, shape or form. Thus concludes my Synthesis report.