The Ethical Implications of Artificial Intelligence

However, there are some concerns arising associated with the ethics of AI. One of the biggest problems taking the news media by storm is students using AI to write term papers. While this can be a significant problem in schools, there are other ethical issues of AI rising that include:

• Transparency
• Bias
• Fallibility
• Market collusion
• Privacy
• Plagiarism
• Control
• Jobs

Let’s look at how each of these issues within artificial intelligence ethics can affect our world now that AI is here to stay.

Transparency in algorithms To say that AI algorithms can be complicated is an understatement. Social media algorithms can be easily explained by sharing what boosts a post and what slows it down. However, the deep learning processes of AI algorithms can be difficult to understand, even if they’re plainly laid out. The “hidden layer” of the algorithm, where all the processing happens, is programmed by the AI’s creator and has their influence on it. One of the ethical issues of AI is that none of this information is disclosed, so you don’t always have context for the output.

Creator bias Speaking of creator influence… Every software engineer will have a certain level of bias in the code they create for an AI bot. Whether they mean for it to happen or not, pieces of their personal biases may come through. It’s easy to see how this could cause problems with providing false or biased information. As with anything done creatively, the biases of the creator will come through in the final result.

Fallibility No computer software is flawless. Databases get outdated, games have bugs, and websites crash. The same goes for an AI algorithm. You’ll find that AI is no different. Generative AI chatbots like ChatGPT are limited in their “knowledge” and can produce false information. While this might not seem like such a big deal when a student’s writing a paper or someone’s trying to compile recipes, it can be a massive problem when companies are trying to run simulations for business models, projections, and analytics. The fallibility of AI isn’t consistent, and users might not realize the faults until it’s too late.

Free market competition Companies using AI to gain market insights and trends will have a competitive advantage over those that don’t. While this is part of how a free market works and increases competition, it could also lead to monopolies, collusion, and other shady practices based on information gathered in AI simulations and data analysis.

Data privacy and security AI bots gather information in droves. While this can be helpful in creating comprehensive products, it’s not always clear where the information comes from. Does AI have access to your bank account to provide income and demographic information to competing banks? There are privacy concerns with AI that aren’t fully addressed in many cybersecurity plans because we haven’t reached a point where it’s become a rampant problem.

Plagiarism in content creation AI bots can’t create fully original work. They scour a database or the internet (whichever they’re programmed for) to learn how to create content based on what already exists. Who gets credit for the work? The creator of the algorithm? The bot? Does it need to be attributed to the original artist? It’s hard to say with the ethics of AI art because it’s nothing more than a compilation of content into a single piece. More questions arise with monetization. Does the creator of the AI bot have the right to monetize or allow monetization of the content? These issues are just the tip of the iceberg when it comes to plagiarism and copyrights to AI content.

Maintaining control The sci-fi genre has done a great job of scaring humanity about the possibilities of artificial intelligence taking over humanity. The “robot revolution” is a plotline in many books and movies that’s a result of AI maturing beyond the need for humans and taking over the world. While this makes for a great story in fiction, it might not be too far from reality. AI systems work through deep learning that makes them improve their systems over time, which means the AI software you use today will be even better a year from now. So, how do you limit learning? Algorithm engineers will have to find a way to cap the AI’s learning to keep us from falling into a world ruled by robot overlords.

Taking jobs While machine automation has been creating jobs for more than a century, it’s also been taking them. One of the big questions surrounding the arrival of AI, especially generative AI, is: will it start taking jobs? Creatives like writers, artists, and musicians as well as software engineers have had job security for years because nobody can do what they do. With generative AI, a computer can reproduce much of what the people in these positions can create in a fraction of the time. Regulations would limit the use of AI in content creation to a tool to assist workers rather than allowing it to perform tasks autonomously.

The ethical issues of AI will continually be addressed as we see more and more uses for it. Keep in mind that the term AI hasn’t even been around for a century, so we’re in the very early stages of learning how to properly handle it.