Demystifying AI: Exploring Why It’s Not as Scary as You Think 

By Machielle Thomas
A scared woman

New technology has terrified humans for as long as technological advancements have been a thing. Consider the first moving motion picture: audiences in the theatre literally thought the train driving along on screen was going to pop out and hit them. It didn’t, and of course it wouldn’t, but the fear was nonetheless very real and important. 

It’s important to accept and understand our fears when it comes to technology while not being beholden to them. For the very many, whatever technology is causing worry is because it’s not as widely understood as those who minutely and consistently work with them. This is true of artificial intelligence (AI). 

Back to movies for a moment: AI gets a bad rap because what we’ve seen on screen has shaped our perception of it. That’s what good fiction can do. But in creating a narrative that AI is simply a machine that’ll become sentient, soon to take over our lives, we’re at risk of really losing the plot.

Let’s dig into what AI is and isn’t in an effort to reassure and understand the technology. Ahead, we’ll give a clear and concise understanding of AI, how it can best be used, some real ethical considerations everyone should know, and why education is the key to releasing any fears.

What artificial intelligence (AI) is and isn’t

Artificial intelligence is an advanced computer science focusing on technologies, like computers or robots, with the help of an algorithm that simulates human-like intelligence.

It’s with the help of specific models, like machine learning model (MLM), large language model (LLM), and processes like natural language processing (NLP), that AI is able to do what it is. AI requires a near infinite amount of data to be able to do what it does, which is respond to things like human queries with the same tone and syntax as the person asking the question. 

AI is a bit of a catch-all term. AI can be reactive, meaning it will respond in real-time. AI can have different “minds,” such a theory of mind, which allows the AI to store information and have a memory bank, so to speak, more advanced in its machinations to understand and respond to complex human emotions. The last one, which is perhaps the scariest to some people, is self-aware AI. This AI pretty much acts the most human-like with its ability to store information, generate human-like responses, including emotion, and generally be as it’s titled: self-aware and able to make its own decisions. 

It’s crucial to understand that AI can’t be anything but a machine running on an algorithm without the people who program it and the data used to inform it. AI isn’t sentient on its own, it needs a lot of human intervention to get there. 

How and where AI can be best used 

With all of that said, AI is best used for task-based behaviors. AI makes for an excellent tool to work with repetitive tasks and manual labor, turning them into something more efficient and less time-consuming. 

Let’s take a look at the most common ways AI can best be used. 

  1. Analyzing. AI is really good at looking at whatever it’s offered (from copy to design to sound and pretty much anything in-between) and analyzing it to make suggested improvements or providing insights.
  2. Patterns and predictions. AI can look for patterns in the information it has been provided by users. From the datasets the AI is offered, the tool can also make predictions. 
  3. Automation. You’ll need to train it to do this because AI isn’t so self-aware as to act on its own just yet but the technology can be used to automate tasks and workflows. 
  4. Design. Give AI a prompt and it can create images or any design elements based on that phrasing. 
  5. Copy. Similarly, and likely one of the most widely known uses, AI can generate text based on prompts given to the tool. 

Real-world applications of AI

AI has been steadily adopted by a number of different industries, all embracing the above ways the tool works to streamline processes, provide written communications, or analyze data to ensure queries are answered with factual accuracy. 

Below are some examples of industries currently using AI and how they are doing it. 

  1. Customer support. One of the best real-world applications of AI is in customer support, and this adoption has yielded remarkable results. More closed queries and issues, complex issues escalated, chatbot assistance for general help, and more. This has allowed for customer support agents to work with more focus on the customer issues that need their attention.
  2. Healthcare. AI helps so many touch points across the healthcare industry from assistance in appointment booking to patient care management (including information) to diagnosis for moderate ailments.
  3. Finance. Today, AI is a very useful tool to have across the financial sector for companies to strengthen their security, find patterns and algorithms that help with trading, and even aid in risk assessment.
  4. Entertainment. The entertainment industry is fairly broad and AI’s application is wide-ranging. This can include helping generate copy for creative or marketing work, or more financial decisions on what projects to focus on. The latter includes analyzing datasets and pattern recognition to understand audience engagement rates and preference.
  5. Manufacturing. AI has been helping manufacturers quality check and control their shipments, optimize scheduling, and perform an inventory check.

Ethical concerns of AI that do matter

Let’s get this out of the way: there are many ethical reasons around AI that are concerning. To dwell too hard on those is just as bad as if we focused too much on the good stuff AI does. There needs to be a balance between what the technology legitimately offers and its limitations and risk potential, especially in the hands of bad faith actors. 

The silver lining here is that limitations can be improved upon and iterating on technology to perform better and be safer to use is possible. 

These are a few of the major ethical concerns with AI:

  1. Bias. AI works with the data it has been given and that data is programmed by people who may have a bias toward their own culture or against others. To ensure that AI is as complex and nuanced as people who exist in an incredibly diverse world, it’s important that a wide variety of data is presented to the tool.
  2. Privacy. Because AI relies on a lot of data to do its job well, the privacy of non-public individuals may be at risk in that data sweep. It is paramount to protect user information and not provide it to the AI.
  3. Accuracy. Factual accuracy is the sibling of bias as a legitimate ethical concern for AI. It’s not often disclosed what information is used to inform the algorithm or LLM the AI uses. If the information it’s provided from, say, certain corners of the Internet, it may repeat something that’s not true. 
  1. Copyright. Authorship is an important ethical consideration. Who owns what information is generated by the AI? With respect to the information used to inform the AI, it may infringe upon intellectual property rights, leading to legal considerations.
  2. Jobs. The primary ethical concern is if AI is replacing people. This could be in the grocery store, lessening the need for in-store customer service reps, or even writers, if AI can generate copy with far more speed. 

Collaborative potential of AI

It has been repeated a few times in this blog but bears a bit more emphasis: AI is programmed by humans. It can’t exist without human intervention, and that’s a good thing.

Here, we can see that AI is actually meant to perform more holistically as one of its key functions: a digital assistant. 

With a collaborative perspective, AI can then: 

  • Help marketing teams write strong, more efficient and converting copy
  • Optimize sales calls with the right information on a targeted customer 
  • Execute on automated email marketing campaigns 
  • Generate draft designs to help strengthen a brand’s overall visual story

Education is empowerment: AI resources

Knowledge is very powerful. That’s what the AI is predicated on, and it’s something we should all take into consideration when trying to understand a new tool. 

Consider the following resources for all things AI: 


Remember the train in the movies? Just like in that example, AI won’t shoot off the rails and off the screen to cause us harm. But validating the fear and then working to understand it will always be a helpful way to embrace something new. 

AI is best used as a tool that will help people do their work better, not replace them. 

Dive in.

Interested in generative AI for customer support? Check out this guide to learn about the 3 key pillars you need to get started.

Get your copy
Decor Half Circle Orange
Call to action decor Call to action decor