COMP 2300 Winter 26 / Cody Kern
As we start to work our way through another revolution, it is natural to feel a bit uneasy. Similar feelings arose in every revolution that we, as a species, have been through up until now.
The biggest need that should be the point of concentration is the need for some sort of regulation.
Why AI Feels Unsettling
It is simply human nature to feel uneasy while watching things become more autonomous. It happened during the industrial revolution as well. One thing I would like to point out is that we have also learned to adapt to these revolutions and learned to live with them.
If we look at the history of our media, it is not hard to see why AI would be something we have learned to fear. Movies like The Matrix and Eagle-Eye show us what happens when Artificial Intelligence gets way too out of hand.
Something that should be kept in mind is the difference between Artificial Intelligence and sentience. The AI that we use to automate our everyday life seems like it has all the elements of intelligence, but it simply is not.
The Case for Regulation
In fact, the biggest need that should be the point of concentration is the need for some sort of regulation on AI to stop companies from pushing out every automated service they possibly can.
Not only is this the main cause of concern for the environment, but also for the type of information that is being dispersed. Two examples of not having regulations are AWS and IBM; both companies are leading suppliers of AI-driven technologies, including commercial AI chatbot tools such as Amazon Lex. They promote convenience while providing less information about water usage impacts and alternatives. Something like this could become more common if there is not regulation.
As we can see in the table above, unregulated AI usage is a problem. China’s president Xi Jinping has been the first to propose a global regulation AI hub in Shanghai. Without proper regulation of AI, we will continue to see AI fail to live up to its potential. Even less, if companies just see it as an easy way to minimize costs and maximize profit.
Bias, Access, and Better Use
Artificial Intelligence uses what is called a Large Language Model and has been used by the government since as far back as the 50s. With the first chatbot around 1966, these models inherited human biases. Meaning that a lot of the misconceptions that have been developed over humans’ existence have also been coded into these models.
This would only go to show just how easily information, and quite frankly AI in general, could continue to become just another useless tool that ends up being more like the movie Idiocracy.
The best and most important thing to prevent this future is to avoid becoming overly reliant on AI. We should be pushing for full support of AI regulation from all levels of the AI community. This includes lawmakers. Regulation could, in fact, calm a lot of the concerns surrounding the level to which people are using AI.
We should be teaching people how to use AI critically and learn how to collaborate with technology and information, instead of trying to use it to further the gap between classes.
If we consider communities that may not have access to information outside of an internet connection, AI gives information to those communities. However, the importance should not be on the abandonment of AI. Instead, the focus of AI should be on making it the best version possible.
According to The Commonwealth Institute’s article “Unequal Opportunities,” students in Virginia’s high-poverty areas only have access to a third of fully accredited schools that offer the proper courses. Compared to low-poverty students, where almost all schools are fully accredited by the state, this shows how unequal educational access can become.
Focus
It’s important to remember not to become overly reliant on AI, as this could continue to push the state of AI further away from what makes it truly a powerful tool. That is, if we can push for a more regulated form of AI so that we can teach it, and it can teach us, creating a more collaborative environment.
Connecting information from the world’s greatest minds to higher poverty areas could eventually help us use AI as a collaboration partner. It could even help us learn to create a more balanced, unbiased justice system, or a fair, equal health care system.
This would require what is known as Artificial Generative Intelligence, which would still be a far-off expectation with the current state. Currently, Artificial Intelligence will only be as smart and capable as the information that is provided to it. Until then, it is important to understand how to use AI to teach you rather than having it solve the problem for you.
AI can potentially help close the gap that is seen between high-poverty and low-poverty communities. If we use the examples of how we have had AI in our media and learn from those mistakes, then we need to start considering who can distribute what types of AI.
Forcing leading producers of AI services, such as AWS and IBM, to put out better and more efficient systems while looking for other alternatives could take some of the pressure off the data centers.
Media Sample
Sources
- Starter post: starter_post.md
- Video link: youtube.com/watch
