AI detection tools help people identify whether content has been created by an artificial intelligence. They’re especially useful for educators, students, and writers who want to maintain academic integrity by avoiding misappropriation of AI-generated content.
A popular AI detector called GPTZero claims to be the most reliable tool for detecting AI content. It can detect ChatGPT, GPT-2, and its offshoots like Claude. Check out more at ChatGPT detection tools.
Text Detector
The advent of AI detection tools is a big deal and will affect how people use content. Especially as Google is cracking down on sites that contain AI-generated text, these tools will come in handy.
Most AI detection tools are powered by machine learning (ML) and natural language processing (NLP). They also rely on labeled training data to sort text into predetermined categories. They then use those patterns to spot AI-generated text in new content.
QuillBot’s AI Detector is fast and user-friendly, providing clear information by giving a percentage likelihood for text it identifies as AI-generated. Plus, it’s free to use with no sign-up required.
Sapling is trained on the outputs of different language models to display reliable and precise results. This is especially important given that each language model has its own quirks. For instance, newbie writers may tend to use predictable sentence structures and jibberish. That could cause perplexity in an AI detector, and lead to false positives.
Image Detector
After launching an incredibly useful AI text detection tool, Content at Scale decided to expand their scope by releasing a free Image Detector. Essentially, it allows users to upload any image and tells them whether it’s human or AI-generated with a simple score.
Despite being fairly basic, this tool is quite accurate and can be used to spot any suspicious photos. It also features a few different functions that allow users to verify the specific image-generating model, detect specific parts of an image that were likely generated by AI and more.
A slightly better option is Optic AI or Not, a more advanced free tool that can not only detect AI images but also identify the specific model used to create them. However, it’s not as accurate as some of the other options on this list. It also doesn’t include an ROC matrix, which is important for evaluating the accuracy of image-based AI detection tools.
Video Detector
As AI-generated content becomes increasingly common, it’s vital to be able to identify this type of content. The use of this type of content can have negative impacts on informational ecosystems if it’s not identified properly.
Many AI detection tools use statistical analysis to determine whether text has been authored by an algorithm or not. However, this method is not foolproof. A number of factors can affect the accuracy of this tool, including word frequencies, the likelihood of specific words, and the complexity of the text.
Another powerful AI detection tool is Crossplag, which uses a combination of several algorithms to detect plagiarism and AI-generated content. This software scans content and highlights any detected AI-generated text with red, while highlighting the original text in blue. The software is available for free, but users must pay a subscription to use the full features. It also supports multiple languages and file formats. This makes it an ideal choice for institutional use.
Voice Detector
A voice detection tool is a powerful AI detection software that can determine whether an audio file is human or artificial. This helps prevent false information from being broadcast or used in scams, fraud, and misinformation campaigns.
There are a number of tools that claim to be able to detect AI generated voices. However, a recent experiment conducted by NPR shows that most of these are flawed and will not be able to accurately distinguish between real and fake audio clips.
Most of these audio deepfake detection tools rely on spectrograms to distinguish between real and fake audio. Spectrograms are visual representations of sound, and they can help detect subtle differences that machines may miss. These tools are also susceptible to noise, which can confuse them and lead to inaccurate results. In addition, the quality of the original audio can also impact the accuracy of the result. This is why it is important to use high-quality audio samples when testing AI generated content.