Computers are getting smarter and smarter, and some people are understandably confused about the role that artificial intelligence will play in our everyday lives. When you consider the benefits of machine learning it’s best to think about it in terms of how it can make what you already do better. Not as a replacement for an entire workforce.
The truth is that machine learning simply helps you to better manage your staff’s time by completing tedious, time-consuming tasks that humans need not be concerned with. This frees up the humans in your organization to do the important work, leaving the most irritating tasks to machines.
However, there are always advantages and disadvantages to implementing something new and that applies to machine learning as well. In this article, we’re going to talk about the pros and the cons of the process so you can decide whether this is the right move for your company. First though, let’s talk about what machine learning actually does.
What exactly is machine learning anyway?
Machine learning is a type of computer algorithm. While there is, of course, some work to getting them set up to work for your company they are unique in that they can “learn”. Or, actually that they are just very good at predicting outcomes without additional programming. This permits them to use certain rules to make predictions and perform tasks for you.
This can be pretty useful given the right circumstances, and by using machine learning you could actually automate away many of your workforce’s most tedious tasks. Just try to think of the most time-consuming and mind-numbing work your staff is forced to do, and you’ll quickly have some excellent ideas as to how machine learning can free up your valuable work hours.
Why might you want to use machine learning for your organization?
If you’re still not sold on machine learning then how about some real-world examples to help you better understand its many advantages.
Regulatory paperwork and compliance
In many industries, there’s an overwhelming amount of regulatory paperwork which must be completed and even more documentation which must be read and adhered to. Worse yet, this documentation is constantly changing and evolving to meet new challenges.
This makes it very easy for important new additions to be missed by humans, especially if they’ve already spent so many hours poring over the document that they’re having a tough time focusing.
Unfortunately, this is not an excuse that flies with regulatory agencies and any failure to comply could end in very serious legal complications for your organization. What if there was an easier way for you to be sure everything was being taken care of though?
With a properly configured machine learning process you could use a computer algorithm to process all new documentation. It can check for changes or alert you to things that it thinks you should know, freeing up your staff’s valuable time for more important matters.
Recommendations and Error Location
Even if you’re not in an industry with hefty regulations, you can still take advantage of machine learning in order to improve your current business functions.
A properly trained algorithm can pour through all of your documentation, searching it tirelessly for contradictions or potential problems. This can not only save a ton of time versus doing it with human labour, but it could also save your company a lot of money.
Machine learning allows you to catch potential problems before your project gets to the point of no return in its development. This prevents you from making costly mistakes and wasting money on plans which clearly are not going to pan out.
That’s not all though, because an algorithm can also make recommendations for you when it comes to budgeting and efficiency. Computer algorithms are really good at spotting patterns. If the algorithm notices an area where things could be improved, it will help you to identify it.
By using these patterns you can more easily find areas where perhaps your supply chain has been slipping, causing you big losses. Or, maybe you can pinpoint a more efficient way to handle certain business processes, allowing you to save valuable time and resources.
The benefits of using machine learning for these tasks is virtually endless, and they can often do a much better job than humans at tedious, yet low skill tasks. Plus, once your algorithm has been trained it can continue to do the same job over and over without further input from you.
Are there any reasons to not use machine learning?
While it’s possible to do a lot of awesome things with machine learning, there are a few downfalls to the process as well. The largest, of course, is that it can take a substantial amount of time to actually train your algorithm to complete your tasks. (Unless…)
This obviously takes resources and somebody has to develop a model to use for the processes and then test it to make sure that it works. That means that in order for your machine learning process to pay for itself you’ll need to make sure that you’ll be using it regularly.
If the process in question isn’t going to be used very often then it might not actually be worth your time to train an algorithm to do it. In these cases, you might just need to assign infrequent tasks for manual labour completion.
It’s also important to note that an algorithm is only as smart as the person who programmed it.
So, while machine learning can take a lot of work off your plate it needs to be programmed correctly to do it. This includes defining clear goals for the process so it knows what to do when and where.
If the process you’re trying to automate does not allow for this, then machine learning may not be the best choice. Work that requires decisions which may not be absolute is best left to humans because an algorithm will simply not produce the required results. It can only function based on what it knows.