Should I Use ChatGPT for My Essays?

Artificial intelligence has finally come to the world of academia. Students have been tempted to use LLM-based instruments such as ChatGPT for writing essays and other research papers by simply writing a prompt and clicking “Generate.”

The burning question, however, revolves around the quality of work that AI can produce. Is the technology advanced enough to deliver on its promises, or does it fall short of expectations? Students are grappling with the decision of whether to entrust AI with their essay writing and contemplating the potential trade-offs involved.

In this article, we offer you the opportunity to explore if chat gpt good at writing essays, the pros and cons of AI writing tools to gain a deeper understanding of why it’s more of a hindrance for students rather than a salvation. For those of you who would like to jump straight to the conclusion, using a service provided by human authors rather than machines is still a better alternative than trusting such a foundational component of any course as an essay to a machine.

What Is Generative AI and How Does It Work
Generative Artificial Intelligence (AI) is a subset of machine learning that focuses on creating systems capable of producing new and original content rather than simply analyzing and interpreting existing data. What is generative AI compared to other forms of artificial intelligence? Unlike traditional AI models that rely on predefined rules and patterns, generative AI can generate novel outputs by learning from vast amounts of diverse data. This form of AI is often employed in tasks such as text and image generation, where the goal is to create indistinguishable content from human-created content.

The functioning of generative AI is rooted in neural networks, which are designed to mimic the human brain’s structure and function. These networks consist of interconnected nodes organized into layers, each processing and extracting features from the input data. Generative models typically employ a type of neural network called a “generative model,” which learns to understand the underlying patterns and structures in the training data. During the training process, the model refines its understanding of the data and becomes capable of generating new, coherent outputs by making predictions based on the learned patterns.

Generative AI Setbacks
Now, let’s move on to the pros and cons of Chat GPT as the most popular GenAI instrument. It operates through sophisticated neural network architectures to produce text content, with recurrent neural networks (RNNs) and transformer models being commonly employed. The primary objective of generative AI in this context is to generate coherent and contextually relevant text passages autonomously.

The model is trained on large datasets containing diverse examples of human-written text, learning the intricacies of language, grammar, and contextual relationships. While generative AI can produce impressive text content, it’s important to note that it doesn’t possess true comprehension or consciousness but rather mimics linguistic patterns learned from its training data.