The Bigger Picture: Content automation with artificial intelligence

Artificial intelligence is on everyone’s lips, and the digital transformation is noticeable in every corner of our lives. We encounter and use more and more AI-based applications – often without us being aware of it. There is undreamt-of potential for communication, in particular: machines use natural language processing (NLP) to analyze, generate, and speak our language. So what is the use of artificial intelligence for content automation? How do we make profitable use of the technologies – already now?

3d rendering mini robot in human hand

To begin with, there is the question of the definition of artificial intelligence. It is a generic term for various research fields that deal with how machines can achieve services that correspond to those of human knowledge. So there is not this one AI – instead, artificial intelligence is a collective term for numerous intelligent applications – from autonomous driving to humanoid robots to machine processing of human language.

Man or machine – who is smarter?

All currently existing systems can be assigned to the so-called weak artificial intelligence. In contrast to the “all-round solution AI”, which is often communicated in the media, these systems were developed to fulfill a clearly defined task and use the same methods to solve problems. They act purely reactive, so they do not gain a deep understanding of the actual problem and do not have independent consciousness. People are versatile – we can drive a car, write novels, or learn different languages. Machines can either do one or the other or – in most cases – neither.

On the other hand, systems that mimic the entirety of human intelligence and can solve new problems independently instead of just simulating individual social skills fall under the category of strong or general  AI. They are often referred to in the media as “superintelligence.” We’re not that far yet. And it remains to be seen whether we will ever get this now.

So as long as artificial intelligence has difficulty concentrating on more than one task at a time, we don’t have to worry about super-intelligent machines and dwindling jobs. Especially since various studies have confirmed that automation will lead to a change in the world of work, but a long-term increase in employment. This creates new job profiles and exciting challenges, as well as new ways of working and demanding constant and flexible learning.

So back to the current developments: How far does artificial intelligence go? There is no question that machines represent an expansion of our potential since they can do things that exceed our capabilities – conversely, we also outperform the tools in many ways.

Technology is ahead of people in data-driven and standardized tasks – people’s strengths lie in creative, original, and creative assignments. And of course, it is not only the complicated and demanding things that are reserved for us humans but also the conscious feeling and experience of the beautiful things.

In this sense, the term “artificial intelligence” may be misleading – instead of a machine image of human intelligence, it is much more about efficiently expanding or supporting our skills because personal information is a complex, challenging to define construct and will probably never be wholly reproducible or copyable.

An interpretation of “AI” as “Augmented Intelligence” instead of “Artificial Intelligence” would be more precise – depending on your perspective, we are ultimately more intelligent than AI, but AI is also more intelligent than we are. The question remains, how can we use this fact profitably and intelligently expand our intelligence.

Is artificial intelligence revolutionizing communication?

If you pair artificial intelligence with linguistics, we are in the research area of ​​”Natural Language Processing.” The NLP deals with the mechanical processing of human language – It can analyze it, develop semantic connections, and generate it.

You have stumbled upon this yourself when using apps and websites with chatbots or smart assistants. Language-based on AI is often generated within these applications. The technology behind it is called “Natural Language Generation” (NLG). More and more websites use automatic text generation to provide targeted, personalized, or merely a wide range of high-quality content.

When news portals use NLG software to produce sports news, weather reports, or stock market updates, there is often talk of “robot journalism”. Real estate portals, tourism providers, and online retailers use the same technology to create offers or product descriptions. Banks and insurance companies legally secure financial texts and agencies implement new content strategies with automatic support.

Really?

“These skinny fit jeans from Tamaris prove to be a real stroke of luck when you try them on for the first time. It immediately becomes an essential part of every new favorite outfit with its flattering fit and cutting-edge cut. It is not for nothing that the extremely tight fit of this cut is beautiful, as it skilfully highlights the curves of the wearer and is also comfortable to wear. […]”

Yes. Because this text comes from the pen of a machine.

NLG opens up completely new possibilities: Personalized content can be created in different languages in real-time – tailored to a specific region or a particular market.

The numerous advantages are apparent: With NLG, message-driven portals can expand their coverage to niche topics and increase their reach. Direct coverage of current events increases reader satisfaction and loyalty, as well as user engagement with the offer.

Online retailers can quickly and easily customize content and update their catalogs when needed, e.g., For example, they can respond to conversion optimization data or promote seasonal promotions. Unique texts can be generated for the same data record at the push of a button, which enables individual texting on multiple play channels. The often cumbersome analysis of the data situation in various contexts is also carried out automatically, and the results are presented to users in an easily understandable, naturally formulated text form.

The result is increased productivity and more time-efficient work: the technology takes over routine tasks, and people have more time for demanding and creative work.

So what are the prerequisites for companies to successfully implement NLG and to benefit from all these advantages?

One factor is crucial: structured data. They form the foundation of every NLG application; with them, the entire text generation project stands and falls because only structured data can be processed mechanically and used efficiently.

“Structured” means that the information is available in an organized, for example, tabular form. When creating a weather report, this would be, for example, the temperature, the probability of precipitation, or the expected number of hours of sunshine at a specific location. Stock market news can be the price fluctuations or values ​​such as the increase or decrease in an index while texting product descriptions, article characteristics such as color, material, size, or weight.

Ergo: If something is measurable, it can be recorded in data. And if it can be recorded in data, then it can be automatically texted. Areas of application for automatic text generation arise wherever recurring and standardized form of communication is required.

To transform this structured data into naturally formulated texts, an NLG system must be set up in advance for the specific area of ​​application – the desired format of the content must be structured, threshold values ​​defined, and variant formulations added. The scalable text generation is then possible. Depending on the available data and the complexity of the specified conditions, Natural Language Generation can present facts or interpret numbers in detail.

To return to the initial question, it is by no means an exaggeration to speak of a revolution in our communication; of evolution but perhaps more appropriate. Because stagnation would be a cause for concern – that society is developing and changing is only desirable. And Natural Language Generation is just one area of ​​application for artificial intelligence because digitization runs through all areas of our daily life and creates an unbelievable number of different opportunities to improve and expand our communication even further – for example, through chatbots, smart speakers or machine translation.

“AI for everyone”?

The existence of new technologies is one thing: the possibility of using them is another. Such a “privilege” can be restricted to selected groups of people who have specialized (programming) knowledge, pursue specific research purposes, or can afford to buy expensive applications. Thanks to digitization, more knowledge is available globally and publicly – everyone can experience innovation not only passively, but also actively shape the developments.

This is also the case with the Natural Language Generation: NLG software is offered as a Software-as-a-Service application (SaaS) and can be connected to any CMS and operated intuitively, without any programming knowledge. This enables users to create NLG content independently. In contrast to purchasing a complete NLG service solution, users are responsible. Because even if NLG experts and developers are experts in what they do, they cannot be experts in every particular area that needs automated texts. Industry-specific, perhaps competitive background knowledge and relevant relationships, are best known to industry specialists. Who could set up such an NLG project better than the experts themselves? 

Of course, the users are not on their own. An intelligent analysis of the data and text input automatically takes linguistic peculiarities into account. Other complex functions and the possibility of automatic translation are bundled in an intuitive web interface. Onboarding and advice from the NLG service provider should be part of the excellent service to enable users to use the technology successfully. And this is how this successful assignment can sound:

“Bathroom taps like this fit in every bathroom. The timeless design nestles wonderfully into the ambiance without attracting too much attention. Thanks to the stylish shape and the beautiful gloss in chrome, the basin mixer is a welcome eye-catcher at the washbasin. Benefit from Grohe’s branded products and purchase this copy from the Euroeco Special series.”

Online shops such as calmwaters.de from Badorado GmbH use NLG solutions such as the textengine.io from Retresco to meet their permanent need for current product descriptions – especially in sales have to convince not only technically, but also on an emotional level. Every shop operator knows the challenge of texting a large number of products in a uniform address – and that as flexibly and efficiently as possible. Automatic text generation enables them to distinguish themselves from the competition and standard manufacturer texts.

In the media environment, process optimization, in particular, is a decisive argument in that journalists are given more time for in-depth research and creative tasks by doing less routine work. However, natural language generation can also be used to offer users an optimized customer experience through an additional service: For example, ImmobilienScout24 automatically texts the critical data entered by its advertisers into appealing property exposés. The application options for text generation are diverse and open up enormous potential for various industries with a little imagination.

This is how content automation with artificial intelligence succeeds.

The content creation today is not a purely editorial task more; the process through automation can economically make sense. 

In the course of the digital transformation, it is essential to remain agile and actively shape progress. New technologies are to be understood as valuable tools that can make a significant contribution to the individual (content) strategy.

Automation per se, however, does not mean progress if it is not used correctly. Natural, human intelligence will always be seen as the basis for the strategic application of artificial intelligence – however, the intelligent combination of the two enables companies to advance their sustainable business success.

Author: AmerBekic

I am an online marketer and web developer who writes reviews and tutorials on web hosting, WordPress, online marketing and web development because I want to help people better manage their own websites.

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