meta_pixel
Tapesearch Logo
Log in
In Machines we Trust

The Future of AI Detection: Innovations and Challenges on the Horizon

In Machines we Trust

In Machines we Trust

Technology

00 Ratings

🗓️ 22 February 2024

⏱️ 6 minutes

🧾️ Download transcript

Summary

In this episode, we speculate on the future of AI detection, discussing potential innovations, technological advancements, and emerging challenges that will shape the next generation of detection systems and evasion tactics.

Transcript

Click on a timestamp to play from that location

0:00.0

are chat gpt detectors accurate that's a question a lot of people are asking right now as chat gpt has

0:06.3

come out specifically for teachers that are looking at if their students used an AI model like chat

0:13.0

gptor write an essay or not so this has a lot of actually implications beyond just education as well

0:17.8

google specifically said that they have an AI detection software

0:21.5

that is able to detect if content online is written by AI and they demote that content in their

0:28.2

search algorithm. So theoretically speaking, if you wrote articles using chat GPT, posted them on

0:34.4

your blog in hopes of having your pages on your website show up on Google.

0:39.3

Google is supposed to demote those and devalue those because they were written by AI.

0:43.3

Now, people have different opinions on that, but today what we're going to talk about is how to detect AI writing,

0:49.3

how accurate those tools are, and things that people are doing to get around them.

0:53.3

Because listen, there's obvious incentives to have your content look human generated.

0:58.6

And when there's incentives, it's always going to be a cat and mouse game of people trying to go back and forth,

1:04.6

catching them, and then people trying to evade their safeguards.

1:08.0

So what's good to know or what's important to know on this is that the advancement of technology is really accelerating right now we know.

1:15.6

And so what's first important to understand is how AI writing tools work or AI writing detectors

1:23.6

detectors work. So these tools typically use machine learning algorithms to analyze text for features

1:29.6

that are indicative of AI generated content. So for example, some AI writing detectors look for

1:35.5

patterns in the word use and also sentence structure that are typical of AI generated text. And

1:41.0

others use deep learning techniques to analyze the text and compare it to a large database of known AI-generated text to make a determination.

1:48.0

So what this actually looks like in real life is, for example, this is what Open AI did with their recent tool they just launch.

1:55.0

They went and had it trained on a massive set of AI written content, right? They obviously can just pull that from

2:02.7

their own data set of chat GPT. And they compare that to content written online. Now, that being said,

...

Please login to see the full transcript.

Disclaimer: The podcast and artwork embedded on this page are from In Machines we Trust, and are the property of its owner and not affiliated with or endorsed by Tapesearch.

Generated transcripts are the property of In Machines we Trust and are distributed freely under the Fair Use doctrine. Transcripts generated by Tapesearch are not guaranteed to be accurate.

Copyright © Tapesearch 2025.