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Written by xScion
on September 25, 2018

 

Science fiction writer Ray Bradbury once wrote, “Science fiction is any idea that occurs in the head and doesn't exist yet, but soon will, and will change everything for everybody, and nothing will ever be the same again. As soon as you have an idea that changes some small part of the world you are writing science fiction. It is always the art of the possible, never the impossible.”

 

I have to admit, I’m one of those people who has been seduced by the terms “Machine Learning” and “Artificial Intelligence” and in many ways, these terms have that science fiction ring to them. With all the new names, phrases and acronyms that come out every year to describe the latest advances in technology, very few elicit that same sense of true innovation and advancement like these two terms. But when you peel back the layers and look at what Machine Learning and artificial intelligence really are, and how most of us are already benefiting from them in our daily lives and may not even be aware of it, you’ll see that there’s a surprising simplicity that underlies the seemingly intimidating nature of the terms themselves. Consequently, I feel that this misunderstanding about the simplicity of these benefits is keeping many organizations from pursuing them altogether. In many ways, when it comes to Machine Learning and AI, the truth is much simpler than the fiction that currently exists.

 

At their core, what exactly is Machine Learning and Artificial Intelligence and how can even the smallest of organizations both benefit from and afford these new technologies?

 

What is Machine Learning?

You can find a number of explanations as to what Machine Learning is, some more technical than others and yes, generally speaking it’s all about the ability of an application or program to learn and become more intelligent over time. But how exactly does an application or program do that? At its core, Machine Learning is nothing more than a labeling function or a classification function applied to a set of data. That’s really it. As an example, if you or I were to see a photo of a dog online, we instantly know that it’s a photo of a dog. Dogs have certain characteristics, so we are also able to recognize other dog photos as well. In a similar way, when a Machine Learning algorithm is applied to a data set and in this case, perhaps a set of photos, the first time that algorithm labels or characterizes a certain photo as that of a dog, it is now able to recognize those same characteristics moving forward to both more intelligently assess a given set of photos and possibly predict things about that set of photos. Typical Machine Learning algorithms use criteria or “feature sets” as inputs to find certain output; e.g. a “dog.” This same function and outcome can be applied to any data set.

 

How Can You Benefit?

Every company and organization, large and small, has data sets that are both valuable and growing every day. The ability to make sense of that data in a way that benefits the goals and mission of a given company or organization is incredibly valuable. It’s also incredibly costly and time consuming to have human beings manually managing these functions. All too often I hear about people and teams who spend hours every day and week pouring through spreadsheets and tables, trying to connect dots and make sense of things. Machine Learning, on the other hand, can be a very cost-effective way for any organization to begin to label, sort and make sense of their data in a totally automated way, and in a way that will provide an increasing level of value and intelligence over time.

 

Additionally, Machine Learning can reduce “time to value.” Given the rapid nature of change in the world we currently live in, Machine Learning can help organizations identify certain actionable outputs more quickly. For example, fraudulent transactions, incorrectly filed claims or customer feedback. This is critical in an environment where the volume of information is greater than ever before and the pace at which information is changing is faster than ever before.

 

Real World Example

My team and I recently met with a medium-sized nonprofit organization that decided to look into the benefits of Machine Learning and AI. This is an organization that in part, serves the needs of the elderly population. They are looking for a way to use the data that they have on their constituents to provide a more personalized experience on their website, and ultimately be able to recommend the specific benefits and programs that are available to certain people based on their age, location, health history and other factors. Ultimately, the goal and mission of this organization is to increase constituent participation in the benefits and programs that are already available to them, but which many of them may not be aware of due to the complexity of the current manually-intensive research process. Machine Learning can be used to streamline and automate this process, therefore increasing constituent participation, a key KPI that this organizations uses to measure success. This is also where they will realize the ROI of any initial investment.

 

What Exactly is Artificial Intelligence?

Artificial Intelligence, as it relates to Machine Learning, is really nothing more than the output of various Machine Learning functions, like the ones described above. Many of us benefit from Machine Learning and AI every day and may not even realize it. For example, when Netflix recommends a movie or show we might like, or when Amazon recommends a new book or product we might like, that’s all being driven by Machine Learning and AI. Or, it might even be more seamless than that. You might be enjoying highly simplified or streamlined experiences on certain websites or in certain apps, all of which is being made possible by Machine Learning and AI functions on the backend. In the not-to-distant future, you will most likely recognize the absence of Machine Learning and AI as opposed to their existence in any given experience (a warning to any company or organization fighting for market share but lagging in technology investment).

 

Conclusion

As indicated in the case study shared above, the benefits of Machine Learning and AI are not purely commercial. They help to solve many of the common business challenges that all companies and organizations are facing. How can we better serve our customers or members? How can we create new efficiencies and cut costs? How can we create more personalized experiences? How can we more intelligently utilize the data that we already have in order to make better and more strategic decisions?

Machine Learning and Artificial Intelligence may be fancy words, but their functions and benefits are highly practical and accessible to all companies and organizations.

 

Additionally, Machine Learning & AI should really be only but one aspect of an organization’s data maturity planning. While the promise of Machine Learning and AI are bright, they are only as good as the data that they plug into. That being said, as your company or organization seeks to modernize data operations and move along the data maturity curve towards a desired future state, Machine Learning and AI are capabilities that should be part of that larger discussion. And these capabilities aren’t science fiction or the absolute bleeding edge of the technology spectrum, where only the largest and most complex organizations have access to their benefits. You too could be benefiting from Machine Learning and AI, and eventually you’ll have to. Don’t wait until it’s too late and don’t be mislead by the words themselves.

 

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