3 Problems Even Good AI and Machine Learning Content Suffers From

Every morning, I have an artificial intelligence and machine learning reading list and every morning I see the same 3 problems in AI and machine learning content.

Around 8 am each morning, I make my way to the office, usually listening to the Dan Le Batard show,  make my incredibly delicious Bali Blue Moon coffee in my Aeropress and I sit down to look at my aggregated AI and ML articles.

And here we come to problem # 1:

Problem # 1: Bad Headlines!

The first problem I notice is the headlines of some of the best and most interesting articles.

Here’s an example from this morning on Medium

Do you know what Numpy is as a new reader?

How about I/O?

I won’t even mention back propagation.

One of the Big Picture problems with marketing AI and Machine Learning is that the marketing materials are WAY too technical and complicated.

The Waymo article is REALLY close to having a good headline all they need to do is eliminate the term Google I/O re-cap which lowers the value of the content and is confusing if someone is looking for a more accessible easy to understand article which it is.

When it comes to writing headlines you want to take a cue from the high traffic sites like Buzzfeed.

An easy way to start creating more interesting headlines is to use this old Gawker trick: Begin with a question that would false if you removed the question mark.

You can also use Co-schedule’s awesome headline analyzer tool for free Here

Problem # 2: In Article Algorithms and terminology keys.

I come from the Ivy League world of academia, I understand the drilled into you process of showing your work in academic papers.

Guess what blogs and content marketing pieces aren’t

I’ll give you a second.

Did you guess academic papers?

Because academic papers make TERRIBLE content.

You don’t need to show your work in content pieces. All you need to do is show the BENEFITS of your product and those who are interested and so technically inclined will figure out how to get in touch with you and have their data scientists call your data scientists so to speak.

I know it can feel scary to strip out what you believe is the most important parts of your content but it’s not what the audience is trying to hear.

Your ideal clients want you to talk about what your AI or ML can do for them and their business.

Trying to show them HOW it works is like trying to sell hot stew during the Pawnee Summer

They don’t care about how brillant you are.

Sorry.

Problem # 3: There is no “Toaster” 

My friend the super smart marketer Tony Almeida has a concept he calls the “Toaster” for his content.

The concept of a toaster is that it is one easy to understand or implement idea that the person reading or watching your content can take away and use without even reading the whole article.

He calls it a toaster after the way that banks used to give out free toasters in order to get new clients to join the bank.

One of the things I’ve noticed from reading about an hour of AI and ML content a day for the past 2 years is that if the article or video does have a “toaster” it is usually in the form of some algorithmic breakdown that you need a CS degree to even begin to understand.

For every piece of content you create you want to have a toaster.

And you need to make that Toaster simple enough for anyone who might stumble upon it to understand like this short video on where AI uses sentiment analysis to determine that Ben Affleck is in fact displaying the emotions of sadness in the infamous “Sad Ben Affleck” video.

Now that is a GREAT toaster that anyone can understand.

Ok so let’s quickly re-cap the 3 big problems I see in even good AI and ML content

Having read a ton of AI and ML content over the last few years I noticed the following 3 big problems:

  1. Bad Headlines. Either Too technical or not focused enough on the benefits.
  2. In article algorithms and terminology keys. Just no.
  3. Not enough “Toasters” or overly technical toasters.

So now you know to spice up your headlines, remove the algorithms and terminology keys and include 1 simple easy to understand idea or take-away in each article.

If you do just those 3 things you will see a huge leap in the quality and reaction to your ai and ml content.