Scholar GPT Fails To Deliver – A Wake-Up Call For The Trustworthiness of AI in Academia

Here we go again. It was supposed to be the shining beacon of academic research, a tool that could sift through mountains of data, offer accurate citations, and provide credible sources to enhance scholarly work.

Scholar GPT, the supposed breakthrough in AI-driven academic assistance, was meant to revolutionize the way we gather information. It was supposed to be a reliable resource that combined the power of cutting-edge technology with the expertise of years of research, right?

WRONG.

Once again, we are confronted with a harsh reality that we have all come to dread when it comes to AI:

It can’t be trusted.

In a shocking revelation, Scholar GPT—this supposed paragon of academic assistance. However, when I was using it I found it to be providing inaccurate information and statistics. The very thing it was supposed to excel at—accuracy—has turned out to be a total farce.

This is not just a minor blip. This is a massive blow to the credibility of AI as a source of reliable academic content. Scholar GPT, which touts itself as being trained on the most valid and credible sources, was providing data that didn’t match up with reputable research and statistics

And let’s not ignore the glaring fact that the platform claims to reference “credible” academic papers, yet several of these so-called references were completely fabricated or misquoted.

At this point, anyone still believing that AI like CHATGPT, or in this case, Scholar GPT, is a trustworthy partner in academic research is either naive or seriously misinformed. I’m sorry, but when you trust a tool that generates fake statistics or pulls sources out of thin air, you are opening the door to disaster in your academic work.

Sure, you might say, "But these AI models are constantly improving!" Really? Because the last time I checked, they’re still feeding you half-baked data that could ruin your credibility in a split second. It’s one thing for AI to make a mistake on trivial things, but when it comes to providing factual, verifiable information to the world of academia, there is no room for error.

The repercussions of getting this wrong aren’t just some theoretical debate about technology—they can have real-world consequences. Imagine citing a non-existent study or quoting a statistic that’s completely fabricated—your academic integrity, your reputation, and your work could all go down the drain.

How does AI expect to replace credible research when it doesn’t even know what reliability looks like?

And don’t even get me started on how CHATGPT itself is still far from trustworthy. The promises of AI revolutionizing everything from writing to research have clearly been wildly overstated. Sure, it might be able to string together sentences that sound decent, but that’s about it.

When it comes to fact-checking, cross-referencing, and providing legitimate citations, it falls flat on its face. Even after all the hype and supposed advancements, AI still struggles with the most basic and vital aspect of academic work: accuracy.

It’s no longer just a matter of missing the mark on a few minor details—AI systems like Scholar GPT and CHATGPT are actively contributing to the spread of misinformation, and that is unacceptable. The reality is that we cannot afford to blindly rely on AI in fields that demand precision and scholarly integrity.

So let’s all take a deep breath and stop pretending that these so-called "academic tools" are the holy grail of research. They’re not. They are not ready to replace the critical thinking, in-depth knowledge, and meticulous verification that true scholars have spent years honing.

And, quite frankly, they may never be. Until AI can be trusted to consistently provide accurate, reliable, and verifiable information, it remains nothing more than a tool that could derail your academic efforts.

If you’re still putting your faith in Scholar GPT or any other AI-driven platform for your academic work, I hate to break it to you—but you’re on shaky ground. The truth is, AI just isn’t ready for the world of academia yet.