Have you ever visited a favorite e-commerce website, and noticed the website was recommending some products you had looked at before?
Have you taken a picture of your friend with your smartphone, and the phone asked you to confirm whether or not it was, in fact that friend by name, based on pictures you had tagged before?
There are many names for the magic behind this wizardry, including artificial intelligence, machine learning or cognitive technology.
Regardless of what you call it, robots, software and computing devices are evolving to become more autonomous than ever before. Technology which can receive input from users and their environment, process the data and learn from it - is here. Have no fear and get used to it.
Machine learning has been around a long time. In 1959, Arthur Samuels, a pioneer in computer gaming, defined machine learning as a:
“Field of study that gives computers the ability to learn without being explicitly programmed”.
Machine Learning Changes Lives
What happens when machines are learning more than games, and taking over job? It’s not just self-checkouts at grocery stores, or kiosk ordering at McDonald’s. There are apps which are evaluating the quality of web content, evaluating university papers and even virtual journalists.
The way civilization reacts to the influence of sentient technology has been the fodder for science fiction movies, television and books for years. Consider how many pundits have expressed how the internet and Google have impacted our memory and attention span.
Search engine algorithms have advanced to the point where they personalize search results based on historical searches, your location and other demographic information. Personalized search results are a double-edged sword, as biased results may limit your options. Thankfully you can always go incognito.
Digital Marketers Take Note
Inbound marketing professionals need to pay particular attention to machine learning. Natural language Programming (NLP) by search engines puts added pressure on content marketers to create content which is:
- Well written
- Original, and published at the right time
- A reliable, insightful source of information on a particular subject
- Effectively tagged and profiled with meta descriptions
With the amount of content available on the internet, B2B buyers are waiting until they are an average of 57 percent of the way through the decision-making process. For sales people and their product and field marketing counterparts, web content quality and consistency increases in importance.
Leverage tools to publish the right content, and when your audience is looking for it, is vital to building and sustaining your audience. Keep prospective customers engaged with your company using thought leadership, and build your authority in your industry. Encourage and moderate feedback from your blogs, and track your conversions through web analytics tools.
Just as machine learning helps applications and devices understand what makes for good content, or when to present content to customers which incites engagement, humans learn from the experience too.
Cognitive technology may evolve to take over many of the “grunt work” articles like stock market reports or delivering sports scores. Just as when IBM Watson collaborates with a physician to diagnose a patient, content writers can learn from content optimization applications, and write more compelling content.
Talented wordsmiths with industry expertise shouldn’t fear being replaced by robot journalists though, should we? What do you think about the influence of machine learning to evaluate, schedule and even writing content? Tell us what you think in the comments section below!
About The Author:
Mark Burdon is a technology professional based in Barrie, Ontario. He has worked in sales and marketing for companies including IBM, Open Text and most recently The Portal Connector for Microsoft Dynamics CRM .Mark has provided B2B content marketing services to companies including Intuit, HireVue, and gShift . He is a freelance writer with Cloudworker Solutions. Follow him on Twitter: @mark_burdon