The Problem With Data Manipulation in AI

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Data manipulation is the idea of turning existing data into a format that people understand. However, in the world of AI, is turns into the process of quite literally manipulating data and algorithms to do what the machine thinks is best.

On its own, this might not sound like the end of the world. However, if you spend some time analyzing just how big of an influence Artificial Intelligence is in todays world, you’ll quickly realize how detrimental this is.

AI algorithms and large language models such as ChatGPT have been given free rein to control a vast amount of the internet today. Ads, user experiences, social media, recruitment, and content production are all being run by soulless strings of codes that feed off biased data.

In this article we’ll explain more in-depth just what data manipulation is, and why it’s becoming so damaging to modern society.

Let’s get into it.

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Understanding AI Bias: Foundations and Definitions

In today’s world, Artificial Intelligence influences a worrying amount of our lives, which makes its bias and the various ethical considerations regarding data manipulation all the more worrisome.

When I talk about AI bias, I am referring to the naturally prejudiced outcomes that are produced by AI systems, which always stem from the data it is trained from.

Fortunately, AI has not yet reached a stage where it can generate its own opinions and ideas from nothing. However, this also means that it relies on a foundational dataset to gather all its information.

Stanford study found that because AI learns through word embedding in language, it is virtually impossible to prevent AI from perpetuating stereotypes and biases.

We are currently in a world where race, gender, and sexuality are major topics of conversation on all ends of the sociological political spectrum.

Whether it’s the content that an Artificial Intelligence is writing itself through generative AI such as ChatGPT, or the AI-run algorithms that control your social media feeds, you are continuously being exposed to the biases that a string of code is deciding you should be exposed to.

Artificial Intelligence is just a mirror of humans, and humans are biased.

AI is trained on “white male data“. The truth is that the internet, and history in general, is biased towards white men. Systematic racism and gender inequality have been around for ages, and as much as large language model creators such as OpenAI claim that they train ChatGPT to not have this bias it still does.

This means that by using ChatGPT to aid you in any form of fact-checking, critical thinking, or other more subjective and emotionally charged topics – you are learning from an inherently biased source.

Using applications that rely on Artificial Intelligence algorithms can inadvertently trap you in an echo chamber of your own implicit biases. This means that you are more likely to encounter and engage with thoughts and ideas that provoke strong reactions, but that won’t challenge or broaden your perspectives.

Artificial Intelligence doesn’t know what the emotional and social implications that come from the human experience are like.

It doesn’t know what it’s like to live in poverty.

To be a minority in America.

To be a woman in a state with strict abortion laws.

To be unsure of what gender it is.

It doesn’t contain any of these traits and experiences or the struggles that come with them.

Instead, it reads about it from a dataset and algorithm that is inherently biased against white men. Do you want to hear or read about the black trans-woman experience in America from a white man?

Tldr; AI systems learn from data sets that are skewed or incomplete. The AI’s decisions, recommendations, or decisions will then reflect those biases. Using a facial recognition system? Well, if it was trained predominantly on data from one racial group, it is going to struggle to accurately identify people from other groups.


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Data Manipulation in the Workplace

Perhaps one of the most significant impacts of AI data manipulation is in the workplace.

Now imagine that you’re a hiring manager, and you decide to take the path of least resistance and use AI to help hire for a new position at your company.

This shouldn’t be very hard to imagine, because most major companies are currently using this as their main way of hiring.

If you’re a young adult and have tried to job hunt lately, you might have noticed that your applications are somehow rejected within a few minutes.

This is not enough time for a real human to make a judgment on whether your application is a good fit for the company or not; instead, an AI skimmed your resume and/or cover letter and decided that it didn’t have the right keywords for what the company is currently looking for.

Or, it’s just a biased a-hole.

AI perpetuates stereotypes based on all the preconceived notions and generalizations about certain groups of people that have been built up over millennia. Based on this systematic discrimination, AI is going to assume that women are not as qualified for technical positions as men.

The AI will straight up disqualify female candidates because that is the data it has been fed, and it doesn’t have any emotional intelligence to realize the obvious faults in doing so.

Companies are essentially allowing their AI to disqualify wonderful candidates – simply because the dataset said that historically, women are not qualified for technical jobs.

Artificial Intelligence cannot comprehend the truth, as it solely relies on data. Gender equality holds no moral significance to AI; after all, it is just a machine. In its world, nothing holds significance.

AI doesn’t have any emotional intelligence or empathy. It doesn’t recognize any right from wrong, it just jumps the gun on any decision and ability based on datasets. It doesn’t matter that the datasets are faulty and biased.

AI Bias isn’t limited to just our examples but rather spans a whole array of marginalized groups and conceptions associated with it. Princeton Computer Scientist Olga Russakovsky confirms that not only does AI have a bias when it comes to gender and race, but it goes “way beyond that.”

The bottom line is that we’re allowing a sociopathic string of codes with implicit biases based on white male judgment from the past hundred years to manipulate our current reality.

This is why AI data manipulation isn’t just another “oh well” issue; it is a serious hindrance to people of all marginalized groups, and we are simply letting it happen because it’s saving costs.

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Data manipulation in Artificial Intelligence is an inevitable curse that is impossible to cure. It is precisely because of data manipulation that AI is as dangerous and damaging to our society as it is today, and we must educate ourselves on the technology.

Of course, there is very little we normal people can do to stop the exposure we have to AI. Boycotting the entire online world isn’t a realisitc task, and we all (well, most of us), have to get a job somehow.

There are things we can take control over, however.

Content consumption.

Ensure that you’re consuming human-generated content as much as possible.

Of course, this content will be biased as well, because it will be written by a person whose inherent biases will naturally impact their work. But at least now it’s by a human, and you can make a fair judgment that the reason they feel the way they feel is a result of their own human experience.

This is how the world has functioned for all of history. We use each other as a way to open our minds or a way to shut it down.

Regardless, it is the best way to form any sort of opinion.

If you want to let your audience know that your content is produced by humans only, check out our free NO AI badges that you can place on your content to let both your consumers and Google (for SEO reasons) know that everything you’ve got is legit, and not perpetuated by a sociopathic machine.

Do your part in halting the influence that AI has through data manipulation.

Good luck.

Want to learn more about the consequences of Artificial Intelligence in today’s society? Check out our extensive library of articles right here.

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