Many people consider artificial intelligence as little more than a science fiction trope. And it’s true that artificial intelligence, or AI, tends to feature prominently within speculative fiction. But in recent times AI has stepped out of the realm of science fiction and into the realm of science fact. And like any breakthrough in technology one can find business applications. The applications of modern AI are nearly limitless. But there’s a few particular points to keep in mind which can help give you a head start.
Some of the following points will show how we make use of a basic knowledge base. But the very first step for any practical AI technique involves knowledge. Consider how much humans can do with no knowledge or memory. We’re basically just infants at that point. We can learn, but we can’t really interact with the world until that knowledge has had a chance to amass.
AI is in a similar predicament. Even the most powerful AI can’t do much without additional input. But even that puts the cart before the horse. Humans are born with the ability to sort out data according to our senses. But an AI needs knowledge representation and reasoning, or KR&R, to understand data. This essentially gives an AI the understanding or even intuition needed to parse any data it encounters. For example, it might use fuzzy logic in fields where the best one can do is an educated guess. Or it might use more strict criteria if the end results need more mathematical precision.
Next, you’ll need to have an actual source of the data to feed into the KR&R system. Some firms and contractors specialize in finding data sources for AI. This is for situations where you need data that comes from outside of your company. For example, the data might come from news sources. This is typically useful in predicting business trends. This could include the market as a whole or actions of specific competitors.
An AI can also be your employees best friend. Consider how much trouble many employees have with their time sheets. But knowing when an employee is at work or what actions they need to perform is perfect for an AI. It simply needs to tie into employee time tracking software as a data source.
From that point it can determine when an employee is at work. It can also help go over trends to determine what points an employee might have issues with. It can even compare overall workflow to help determine team composition for overall project efficiency.
This sets up a powerful combination of human and artificial intelligence. But it’s still somewhat limited by human communication. We simply don’t communicate with computers very well. So far it’s been limited to searching for information rather than simply asking for it.
But you can take care of this fairly easily with speech recognition and processing systems. These help computers translate spoken and written words into a format it can understand. And it then helps the computers understand the actual intent behind those words and phrases. This can create a powerful frontend that can help employees actually speak or write to the company’s AI.
You might be able to further integrate AI into any and all internal systems. It’s important to keep in mind that this often isn’t possible without access to a program’s source code. This can limit you to integration with open source software packages or software developed on-site.
But you’ll still have a powerful asset even if you just stick with the previously mentioned examples. And this is especially true if you combine them into a single system which monitors outside trends and internal workflow. This can create a system capable of predicting outside trends, analyzing internal strength, and then offering suggestions about how to best use your resources accordingly.
Credit: BecomingHuman By: Kevin Gardner
