It is common knowledge that autoblogging has a dubious reputation.

Autoblogging refers to information that is automatically scraped (usually via a plugin) and then published on your blog. The sort of stuff you may access is nearly limitless, including posts, photos, and other media.

During the mid-late 2000s, this strategy, also known as content aggregation, was a rather strong way to establish and maintain your blog. Admins would simply configure their preferred tool and then sit back and relax while making minimum effort.

As end-users began to notice increasingly repetitive (or otherwise low-quality) information inside search results, search engine behemoths like Google began to change.

Websites that depended only on autoblogging were either eliminated from search results or driven down into obscurity. But thanks to the development of AI Content writing tool services, this has begun to change in recent years.

What is Autoblogging?

Autoblogging is a blogging technique in which blog material is created automatically utilizing RSS feeds from other blogs or websites. This material is often generated using software tools built expressly for autoblogging, which aggregate information from multiple sources and then regularly publish it to the user’s blog.

Autoblogging can be a good method to create regular blog material without having to write it all yourself. However, it is crucial to remember that autoblogged information is frequently of poorer quality than manually produced content, so you must carefully pick the sources you utilize for autoblogging. 

Also, certain search engines may penalize websites that have a high volume of autoblogged information.

Modern AI Content Writing

In 2020, OpenAI, a major, well-funded research organization, published a version of GPT-3, a language model capable of producing written language on a gigantic scale. Its power comes from the breadth and depth of the information it has at its disposal, as well as the learning models it has created. 

With more than eight years of crawling the whole Web, billions of books, and the full content of Wikipedia, the creation of GPT-3 was a massive endeavor and a springboard for thousands of new businesses. 

That does mean that the content it creates has been built on plagiarism and copying writers without their consent, which is a major issue that AI needs to tackle in the immediate future. The results have their uses, however.

The Issues with AI Content

Even today, AI content is created with no actual intelligence behind it. AI tools are a sort of advanced predictive text, and all they can do is string together plausible sentences. 

That means that if you are using AI to draft articles, you must fact-check and edit them carefully. AI tools have no way to distinguish between facts and misinformation, and it is essential to manually check their sources before you publish anything.

The Uses of AI in Content Creation

Once the material is prepared and ready for distribution, “meta content” that characterizes the content must be generated. AI may assist with the generation of meta descriptions for SEO, numerous names for articles that can be A/B tested, email subject lines, and article abstracts. 

With the haste to publish, relevant meta-material suffers, and this is one of the most significant gaps in a content strategy. AI can tackle the tedious metadata parts of content writing reliably.