Without a doubt, Machine Learning is an ongoing component of our understanding of technology and the world around us. From the ability to spot speeding cars in traffic to facial-recognition software that can unlock smartphones, Machine Learning is at the heart of many cutting-edge technologies.

But before I get into what Machine Learning can do for content creators, let me define exactly what I mean by Machine Learning. Machine Learning is the scientific study of algorithms and statistical models that computer systems use to perform a specific task effectively without using explicit instructions, instead relying on patterns and inference. Many people conflate Machine Learning with Artificial Intelligence (AI); rather, Machine Learning is a subset of the puzzle that is true AI. 

Another term to define is Natural Language Processing. NLP applies Machine Learning to understand how grammar and speech work together in an attempt to gain a better understanding of content’s meaning.

Machine Learning meets content creation

At Four Kitchens, we’re naturally interested in the crossover between content creation and the world of Machine Learning. How can we teach machines to find a brand’s voice? How can we build content for humans through algorithms and prediction mathematics?

Not that we plan to set up a room filled with 100 machines, just hoping one will randomly churn out a work by Shakespeare. But we’d love to use Machine Learning to alleviate some of the repetitive tasks in your content-creation workflow, so that you have more time to focus on creating great content.

Building Machine Learning into publishing and content management system (CMS) platforms can help with various aspects of the content-creation process:

  • Auto-tagging parts of content in a page or article
  • Correlating images with text to better represent content 
  • Automatic building of semantic metadata 
  • Building a voice within your organization’s articles 
  • Generating article summaries or bylines based on content text 
  • Moderating user-generated content

These key aspects of creating content can often be a drag. Instead of spending time on “housekeeping” tasks like these, most content creators would rather focus on creating better articles, blog posts, and pages to engage visitors. Taking care of logistics that can stifle the creation process is an important part of producing richer, more vibrant content.

With the integration of Machine Learning into the content-creation lifecycle, your teams can delegate those tedious tasks. You get more time to zero in on the messaging they’re creating and on connecting with users and communities. We frequently hear that content producers are under tighter and tighter deadlines and shrinking budgets. Machine Learning offers a way to give yourself some breathing room.

More time for creativity

Machine Learning won’t write the next great American novel. But it can enable you and your team to spend more time doing the creative stuff that makes your content unique.

Your CMS can now read your text, look at your uploaded pictures and videos, and understand the content and context of both. We’re still early days, but I believe that in the long run, Machine Learning will profoundly affect how we create content.

I recently spoke about the benefits of using Machine Learning in the content-creation pipeline at Yale Digital. You can see that presentation here.

What about bias?

Much concern has been expressed around implicit bias in Machine Learning—and rightfully so. Any project that uses Machine Learning must include careful consideration of bias and diversity. At Four Kitchens, we treat this need as an integral part of every Machine Learning effort.

If you’re interested in learning about our off-the-shelf modules or working with us on custom Machine Learning workflows that might help your content process, contact Four Kitchens. We’d love to tell you more.