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The State of Automated Content Creation

As the importance of content marketing grows and online content continues to explode exponentially, more and more businesses are seeking out automated methods of content creation. Making use of these tools might save time and expenses — but is it actually worth it?

Content marketing (CM) consists of lots and lots (and lots) of planning, analysis, prep, scheduling and more besides, so it’s definitely fair to say that it is time-consuming, let alone a costly strategy to take up. In meeting these demands, some marketers turn to AI-generated content which, in general, is cheaper and saves a lot of time and effort.

AI systems are constantly developing and learning to produce high-quality content, some for years now, and some with a bit of success depending on the field. Every one of us actually encounters some of these AI content tools on a daily basis: ever noticed how Gmail, WhatsApp, Facebook or Google Docs, for instance, make suggestions on how to finish your sentence or respond to someone?

These rarely implemented AI systems can be useful from time to time but often get it horribly wrong – in which case most people prefer to write a response all by themselves. This can be directly applied to automated CM tools where we encounter the same gamble: yes, some content creation might be on point, whereas some – well, let’s just say you don’t necessarily want your business to rely on it just yet.

The main problem here is that AI is not yet able to interpret and reproduce human sentiment in every way. AI systems are indeed improving in mimicking human styles of writing, but not every meaning can be conveyed in the right way. Intonation, context, relevance are all a challenge before you even consider the linguistic framework. In the end, humans are the ones that have to revise any errors done by the AI. This in turn costs time and effort.

Researchers at Auburn University have recently found that contemporary AI doesn’t really understand language at all, for instance. They’ve discovered the flaw when they noticed that AI systems attribute the same meaning to different sentences consisting of the same words, but completely jumbled up.

Case in point, now that the pandemic has increased the necessity of a well-established online presence for almost any business, it makes sense to contemplate how to invest into improving it, but I’m not quite sure if content automation is the right way, especially if you rely on high-quality content to power your marketing.

Essentially, it comes down to what you want as a business. If you just want to increase content volume, no matter whether poorly written or not, and with cheesy click-bait headlines, then this could be for you – otherwise, it might be best to stick to human content creators for now. Automated CM tools simply increase the volume of produced content, so they could be suitable for small and low priority content. So, just ask yourself the question; do you want quantity or quality?

Apart from the marketing side, it’s worth mentioning some interesting developments in terms of AI in the creative industries. The use of neural networks has enabled AI systems to create art. AIVA, for instance, is an AI that composes music of many genres and the first non-human to ever be awarded the official title of a composer. AICAN is an AI developed to produce visual art and regularly exhibits and even sells some of its ‘artworks’. The creators of both AI systems emphasise repeatedly that their systems are not there to replace human creatives but rather collaborate with them.

The bottom line is, AI systems are not yet ready to take over all of our jobs, particularly not the creative ones. They can, however, be of use in assisting in creative work. To what extent and how this is done always depends on the circumstances and each individual, but with the right amount of consideration it can lead to success.

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