Thoughts + words/visuals = expression = content.

Since the birth of humans, that is how it has been. Until now. Machines are on the way to taking over our manual tasks; we even have self-driven vehicles today.

It`s the final onslaught now; from taking over doing manual work, algorithms have started moving in everywhere, including content. So far, it`s limited to content management, but will the machines eventually start to think and generate content on their own?

I decided on this topic - “AI in content” - for this edition of my newsletter after reading a news report about an AI company called ‘RADAR’, an acronym for Reporters and Data and Robots.

Let me get the ‘About Us’ out of the way first. RADAR is an automated news service set up by one of United Kingdom`s oldest news gathering service for the provincial papers, Press Association and Urbs Media. The latter is a “new form” journalism outfit that relies on open source data and automation for news reporting.

It`s an interesting marriage, this. Last year, RADAR had kicked off its 2nd phase of experimentation with the launch of a website, allowing regional and local news outfits in the UK to access news reports written jointly by humans and machines.

The report that I got interested in in the Financial Times spoke of how “robo-reporters” of RADAR had written the front page news of the day, “clearly underlining the role for AI and automation in journalism.”

A former “old-world” journalist myself who has been the architect of many a front page story, I am interested in developments on this front. As one who likes to brand himself as a “born again content provider”, “digital nomad”, “ Internet consultant” or '“in-bound marketer”, depending on which hat I am wearing on a given day, it has become obvious to me that people of my ilk can no longer turn a blind eye to the advent of AI.

Over the years, as a tech writer, I have kept tabs on the insertion, then, the progress of AI in content. Not only the big news outfits but even the smaller ones have started dabbling in introducing AI in content. What`s more, even digital marketers and advertisers have signed up.

“The automation of content’, though a misnomer, is here to stay. In newsrooms, it started with sports reports such as horse racing, and business developments like the daily stock market index movement.

The Associated Press and Fox News have been using robo-reporting for some years now.

The AP relies on the “Wordsmith” platform by Automated Insights to robotize its stock reports. This tool uses natural language generation (NLG) “to transform raw earnings data into thousands of publishable stories, covering hundreds more quarterly earnings stories than previous manual efforts.”

Now, robo-reporters have gone and done it - written a front page story. For years, journalists had bet against this happening; they find themselves on the losing side now.

It started with the small stuff; itsy bitsy press releases of no consequence, the sweat stuff that no hardcore reporter wants to touch; local weather reports, voluminous company reports that nobody has the time to look at in the hurly burly of daily news. The machines got better and better, and better, till they could write a proper news report. Front page news at that.

The reason why I have devoted so much of this newsletter only to journalism is to use it as an example to underline my forecast that AI is eventually going to gobble up a lot of jobs in the field of content and its marketing. I have no doubt about it.

Proponents tell me I have the hyperventilating syndrome. They say there`s no need for panic; it`s like when desktop computers were first introduced to journalism, they explain, so don`t sweat it. Traditional job functions will simply get re-designed and re-assigned, as before.

No, I do not subscribe to this point of view. AI cannot be compared to the replacement of a typewriter or a microfilm library by a computer. That, in fact, would be an insult to AI.

Here`s another example to reinforce the point I am making:

Software major Adobe has tools called “smart tagging” and “Auto Tag” that can be deployed for a number of content purposes. (I shall try and be brief about this.) Searching for images is one of them.

For any photographer, web or classical designer, it takes hours to find that “right” image in a library, crop it, do all those fancy thingamajig before including it in a long-form article or in a product catalog.

That`s where Auto Tag with Adobe Sensei capabilities come into the frame.

“Thanks to machine learning and deep learning”, in Adobe`s own words, “Adobe Sensei has learned to automatically identify what`s in a photo.”

But get this….identification is not merely limited to “understanding” the object in the image like a person but “the concept of the photo, including context, quality, and style, itself”

The process allows for “custom auto tagging”, which, for retailers and e-commerce sites, opens up a whole new way to market or sell. Adobe explains this, “…custom auto tagging (also) allows you to gain a deeper understanding of your audience and market trends in social media, without having to rely on tags and text. If you run a social media feed through Adobe Sensei, it will tag places your brand is pictured – even if it's not mentioned or tagged – allowing you to see what is trending.”

Allow me to summarize - what all of this means is better customer engagement, better customer experience, more efficiency, and a tremendous jump in Return on Investment. Just with this one tool.

Here`s what we’ve learnt so far. AI is:

• Writing the news for you

• “Reinventing” and “re-purposing” images by smart tagging

• Mining text for you, classifying and categorizing it in a smart way

• Re-writing the same content, be it as part of a financial summary or a social media post, in a thousand different ways….

…and this is just the tip of the proverbial iceberg. What lies below the ocean surface is far deeper (and disturbing) than what lies above.

So it is not as simple as a proof-reader`s job gone poof, and the work being re-assigned to a sub editor, no sir. This is the penultimate step in the final assault of AI on content creators.

Machines primed to oversee the articulation of thought (verbal and in writing) will eventually take-over the process of human thinking itself.

For now, AI and humans are paired up by conjugation. The machine relies on content already created by humans to make itself “clever” in these matters. It relies on guidance and inputs by humans to learn. It is being trained to mimic humans in intent and feelings, and a whole bunch of emotions.

When “the machines” have finally ingested and processed all of this (and they can do that a zillion times faster than a single human brain), the “apparatus” would have accessed every thought, every emotion, every kind of content known to mankind.

Bereft of a mission, it is then that the machine will attempt to create something new…from the old….without any human intervention at all; nay, as some say, even encouraged in its pursuit by enervated humans.

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