What are the advantages and disadvantages of artificial intelligence (AI)?

We’ve all seen the headlines about AI, both the good and bad. Regardless of what you think of the risks of using AI, no one can dispute that it’s here to stay. Businesses of all sizes have found great benefits from utilizing AI, and consumers across the globe use it in their daily lives.

But even people who are excited about AI can ask the question: what, exactly, are the advantages and disadvantages of using it?

In this article, we’ll discuss the major benefits and drawbacks of adopting AI, both in everyday life and in business. We’ll also talk through some use cases for AI, to give you an idea of how AI can help in your life. 

In this article we’ll cover:

1. What is artificial intelligence?
2. What are the advantages and disadvantages of AI?
   1. Advantages
   2. Disadvantages
3. Use cases for AI
4. Implementing AI

What are the advantages and disadvantages of AI?

There are always pros and cons to any technological advancement. There is a ton of debate about the benefits and risks of AI at every level. But beyond the headlines that either peddle hype or fear, what does AI do?

The advantages range from streamlining, saving time, eliminating biases, and automating repetitive tasks, just to name a few. The disadvantages are things like costly implementation, potential human job loss, and lack of emotion and creativity. So where do we net out?

Eliminates human error and risk

The first major advantage of implementing AI is that it decreases human error, as well as risk to humans.

“To err is human…” - Alexander Pope, Enlightenment poet.

Everyone makes mistakes on occasion. That’s not always a bad thing, but when it comes to producing consistent results, it certainly can be. Using AI to complete tasks, particularly repetitive ones, can prevent human error from tainting an otherwise perfectly useful product or service. 

Similarly, using AI to complete particularly difficult or dangerous tasks can help prevent the risk of injury or harm to humans. An example of AI taking risks in place of humans would be robots being used in areas with high radiation. Humans can get seriously sick or die from radiation, but the robots would be unaffected. And if a fatal error were to occur, the robot could be built again.

Unbiased decision making

Humans disagree and allow their biases to leak through in their decisions all the time. All humans have biases, and even if we try and solve for them, they sometimes manage to sneak through the cracks.

On the other hand, provided the AI algorithm has been trained using unbiased datasets and tested for programming bias, the program will be able to make decisions without the influence of bias. That can help provide more equity in things like selecting job applications, approving loans, or credit applications. 

Though if the AI was created using biased datasets or training data it can make biased decisions that aren’t caught because people assume the decisions are unbiased. That’s why quality checks are essential on the training data, as well as the results that a specific AI program produces to ensure that bias issues aren’t overlooked.

Cost reduction

As we addressed above, AI can work around the clock, creating more value in the same day as a human worker. And since AI can help to take over manual and tedious tasks, it frees up workers for higher-skilled tasks. That, ultimately, creates more value for the end-user or consumer. 

Costly implementation

The biggest and most obvious drawback of implementing AI is that its development can be extremely costly. Depending on what exactly you need AI to do, the cost changes. One estimate says that the cost for a fully implemented AI solution for most businesses ranged from $20,000 to well in the millions. 

The cost balances out later on down the line once the AI is fully implemented and can help streamline the workflow. But the up-front cost can be intimidating, if not prohibitive.

Degradation

This may not be as obvious of a downside as the ones cited above. But machines generally degrade over time. For example, if AI is installed into a machine on an assembly line, eventually the parts of the machine will start to wear. And unless the AI has a self-repairing function, it will eventually break.

Likewise, the AI itself can become outdated if not trained to learn and regularly evaluated by human data scientists. The model and training data used to create the AI will eventually be old and outdated, meaning that the AI trained will also be unless retrained or programmed to learn and improve on its own. 

Reduced jobs for humans

This is yet another disadvantage many people know immediately, thanks to many headlines over the years. As AI becomes more commonplace at companies, it may decrease available jobs, since AI can easily handle repetitive tasks that were previously done by workers.

Now, many reports show that AI will likely create just as many new jobs as it makes obsolete, if not more. But then you run into the problem of having to train humans on these new jobs, or leaving workers behind with the surge in technology.

Use cases for AI

There are dozens of possible examples of AI in business. We talked above about the uses of AI in helping to automate repetitive tasks, freeing up human workers for more complex tasks. Some other use cases include:

• Early diagnosis of diseases in healthcare using AI that analyzes patterns and data to predict when/how a patient is likely to develop a specific disease.
• Virtual assistant chatbots in customer service can handle simple and common requests, and help route requests to human resources for more complex tasks. These also help to provide support during off-hours and weekends.
• Early detection of fraud in financial institutions. The AI analyzes patterns around fraud to catch it as early as possible, and prevent it from happening entirely.
• Creation of predictive analysis to help a business project possibilities for their future, helping to prevent poor decisions and support strong ones.