The Machines Aren’t Coming, They’re Already Here


This past Monday, our team had a chance to visit The Inbounder 2017 conference in New York City. The event featured great speakers, valuable takeaways, and an awesome after-hours event sponsored by SEMRush.

I could probably go on and on about the sheer variety of information covered in the single-day conference; for instance, Melanie Deziel had a great speech about branded content that I’d love to dissect, Ricardo Tayar discussed how his team measured stress levels on test subjects to determine design effectiveness, and Rand Fishkin dropped a wealth of great tools on the audience that I will be making use of in the near future.

But, even with all of that, the day still belonged to the machines and one thing is for sure, the machines aren’t coming, they’re already here.

Terminator Machine

It’s happening right under our eyes, and some of us haven’t got a clue as to what they are, who’s making them, and what it means for the future of marketing. Although, you’re probably already familiar with the following household names. One is better at Jeopardy than your grandfather and one can order you a new non-fat, non-dairy, french vanilla creamer faster than you can search for it on your computer.

Know who I’m talking about? Let me name a few:

  • Alexa
  • Siri
  • Cortana
  • Watson

What do these all have in common? They’re all artificial intelligence (AI) – some more advanced than others. The above-named AI are far from the traditional Brady Bunch and they’re just the beginning of what’s to come. The machine revolution is in full force and as Inbounder speaker Lexi Mills pointed out — they’re “already smarter than we are.”

AI Machine Falling

…Most of them, anyway!

What exactly is AI? Well, here is the Google aggregated definition of artificial intelligence:

“The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making and translation between languages.”

AI can be used to power voice assistants, chatbots, integrated home technology, robots, and even self-driving cars. The general purpose of AI is to interpret human thinking and behavior. But, just how smart are these systems and how are marketers using them to improve their day-to-day campaigns and achieve client success?

For that, I turn your attention to the topics covered by the speakers of The Inbounder conference:

AI and Machine Learning

“Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed.”

Until recently, machine learning was just something you could only find in science fiction movies, but now, it’s being integrated into various software systems for marketing, content development, and reporting.

One of the most intriguing and albeit confusing topics from the conference was by Mike King of IPullRank. His speech, “Machine Learning for Marketers,” focused on the use of machine learning and its ability to solve advanced marketing problems by training software to identify data and make decisions without the need for much human intervention.

I won’t even pretend to tell you that I understood everything he was talking about, but I know that it involved a great deal of data, for which he even employed his own in-house data scientist. This employee’s job is to sort and analyze data to effectively facilitate and measure the machine learning programs that power the agency’s campaigns.

So, in English, what can machine learning do? Well, according to Mike’s presentation, it can do a great deal more than the average marketer, with a higher level of statistical certainty than us mere mortals.

Things like:

  • Predictive Analytics
  • Marketing Campaign Performance Predictions
  • Customer Churn Predictions
  • Customer Segmentation
  • Natural Language Processing & Generation
  • Clustering and Classifying Keywords

It can be used to run just about any software based marketing tool from chatbot AI, to retargeting, to email marketing and automation, and it can even write your content (though he warned against it). The most fascinating thing about what Mike discussed was that machine learning could be integrated, layered and stacked onto many of the existing applications marketers use today and could cut down on the amount of time required to accomplish difficult tasks.

AI Powered Chatbots and Virtual Assistants

Purna Virji of Microsoft further elaborated on the potential for artificial intelligence to power the future of marketing tools, including chatbots and virtual assistants. In the first few minutes of her presentation, “Loving the Bots: Your Guide to the AI Revolution,” she challenged the audience to try and spot the differences between AI and human created content, art and poetry. Turns out, the vast majority of the audience was unable to distinguish between human and AI created works.

Purna later went on to discuss how more and more often, humans are beginning to rely on artificial intelligence and how further development of natural language AI and machine learning would help to achieve higher tech adoption rates.

Within her presentation, she demonstrated the latest Cortana features, which could intelligently make calendar scheduling decisions, intuitively power online voice search and interpret natural language conversations much more fluidly than in previous versions. Purna also showed off the machine taught chatbot features that Microsoft is currently powering with its full suite of developer tools, essentially providing a brain to the otherwise useless chatbots we’ve seen in recent years.

My personal favorite topic was Microsoft’s recent release of cognitive services APIs that could be used to help impaired individuals achieve a higher quality of life. The best example was a pair of glasses that allowed a visually impaired person to view the world like never before. The wearable could essentially describe what was happening around someone with a single swipe along the temple of the glasses.

AI and Online Filter Bubbles

What is a filter bubble?

The term “filter bubble” was first coined by Eli Pariser in his book “The Filter Bubble,” and later popularized during his 2011 TED Talk “Beware online filter bubbles.” However, NiemanLab described it best:

“All of us now depend on algorithmic personalization and recommendation, such as Google’s personalized results and the Facebook news feed which decides for us whose updates we see.”

Lexi Mills touched on this during her thought-provoking presentation, “PR SEO Tactics That Work with AI Online Filter Bubbles.” The presentation was a wake-up call for all marketers and PR people who believe they have any control over the content their audiences see. Lexi elaborated on the difficulty for brands to cut through the clutter of the growing level of trivial content available online.

Her solution: If you can’t beat ‘em, join ‘em!

Specifically, she said, “We need to understand the very nuances that make up our audiences’ behaviors.” She went on to say that PR professionals shouldn’t always focus on something noteworthy but instead focus on something that would drive click traffic – making a case for why we need to be pitching content that we sometimes don’t care for, but what our audience wants.

During her captivating presentation, Lexi described how more and more often, content is being aggregated by and events are being created by AI. The truth is that we are losing control of what our audience sees because of the increased level of competition from AI machines. She even went on to discuss that the way to compete is to start hacking human behavior and capitalizing on filter bubbles. This will help to regain the attention of our online content consumers.

AI at Overit and Final Thoughts

My first exposure to practical AI application was during a recent Lunch & Learn presentation hosted by three Overit team members that developed a Watson-powered tool at Hack Upstate. The tool could fact check content on the fly as it was being written to improve accuracy. I was blown away by the amount of data Watson could pull from the internet in real-time and started to realize just how important programs like this would be in shaping the future. Of course, after hearing some more about machine learning and AI during The Inbounder conference, it appears that this is just the beginning of what we can do when we use machines to control our marketing initiatives. I’m excited to see what comes next.