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Artificial Intelligence
Home›Artificial Intelligence›The Dark Side of AI: 3 Ways Artificial Intelligence Harms Education

The Dark Side of AI: 3 Ways Artificial Intelligence Harms Education

By Matthew Lynch
June 4, 2022
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Listen to the tech gurus, and they’ll tell you that artificial intelligence in education is the future. They may not be too far off base because educators have discovered many benefits of using AI, including improved compliance, efficient workflow procedures, and personalized learning. 

Many educators appreciate the ease with which they can gather and analyze learner data. Artificial intelligence serves as the educator’s assistant in the classroom, patiently working with learners to relearn concepts. Artificial intelligence also helps educators manage the day-to-day operations of their classrooms. 

What’s not to like?

Although artificial intelligence in education may be streamlining the work educators once laboriously undertook by hand, AI may also have a nefarious side. 

Problems with Artificial Intelligence

1. Cheating

One of the many significant concerns among educators is the likelihood that learners will use artificial intelligence to game the system and cheat. 

In school, learners’ search engines also value Wolfram Alpha for its capacity to answer questions and show how to solve them. The site for computational intelligence offers answers in every school subject, and learners can rely on the artificial intelligence program for virtually anything, from solving for –x to synonyms of deception. 

Similarly, chatbots like Watson Assistant serve as teaching assistants in the classroom by telling learners the answers to their questions and determining when they need additional help. Some educators argue that chatbot help is still cheating.

Artificial intelligence by itself doesn’t produce cheating. Learners cheat, and they’ll do it with or without artificial intelligence. Instead, educators must determine how and when learners will access artificial intelligence for help with class assignments.

2. Cyberbullying and Online Harassment

The anonymity of social media has catapulted cyber bullying into the forefront. One-third or more of middle/high school learners report being bullied and harassed on an online platform. 

Nowhere has cyberbullying been more prolific than on Instagram, a favorite learner social media platform. Artificial intelligence can identify instances of cyberbullying. Although Instagram has written new artificial intelligence algorithms to minimize and prevent cyberbullying, the risk still has grim consequences. Victims may experience depression, and bystanders can be guilty of not speaking out against the bullying and harassment.

Determining what cyberbullying is can be subjective, and you must teach artificial intelligence what it is looking for. The artificial intelligence used to halt cyberbullying can increase it, as evidenced by hateful comments taught to chatbots Tay and Xiaolce. 

3. Tech Addiction 

Despite the glitches and possibilities of gross error, AI in education promises to make teaching easier. The demands on educators are high, and the responsibility for making sure every learner gets what they need is enormous. It’s only natural that educators rely more on artificial intelligence to help them get their jobs done. 

The overuse of artificial intelligence, however, can lead to tech addiction. Learners find it easier and faster to turn to their tech devices for almost everything, from looking up info to socializing with others. Although artificial intelligence can benefit both the learner and the educator, artificial intelligence can also become consuming. 

Finding a balance between artificial intelligence-induced tech and human interaction is critical for each person’s well-being.

Summary

Artificial intelligence is a valuable and progressive tool for the classroom, but it is not without faults. By recognizing how artificial intelligence integration might bring out the worst in education, educators and administrators can offset the negative experiences. 

With great progress comes immense responsibility. Integrating machine learning and artificial intelligence into education requires both foresight and reflection in order to overcome potential problems.

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