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6 Things Everyone Gets Wrong About AI


There are very few subjects in Science and Technology that are causing as much excitement right now as Artificial Intelligence (AI). AI has the potential to transform the way we work, communicate and live.

When most people think of AI, movies such as Blade Runner, Ex Machina, or Transcendence might come to mind. However, contrary to popular depictions in film, machines aren't going to rule over humans (anytime soon).

Does AI keep coming up in your business conversations? But, its execution is put on hold because of certain misconceptions associated with it? When you strip away the fear and mistruths, you'll soon realise that AI can be a valuable tool that you can use to stay ahead of the competition.

In this article, we are going to list some common misconceptions about AI, as well as the reasons why you shouldn't buy into them. But, before we separate myth from reality, let's explain what AI is all about.

What Is Artificial Intelligence?

Artificial Intelligence (AI) is technology that learns from experience, can perform human-like tasks, and learn, reason and act autonomously.

Who Can Use Artificial Intelligence?

Artificial Intelligence has been around since the 1950s but has recently gained a lot of traction in the last few years. I'm sure you have used Siri / Alexa on your mobile device or clicked on a personalised recommendation whilst browsing on Amazon. Well, these are just some of the ways companies are harnessing the power of AI.

The good news is EVERY industry has a high demand for AI capabilities. It will not only help give you better business results, but it will also improve the human experience as a whole. Here are some sectors that are already using AI to deliver business value:


A wide range of Healthcare Services is using AI to identify patterns to help diagnose and treat medical conditions, medication management or even robotic surgery!


Marketing Departments are leveraging this technology to improve the customer journey, from AI-enhanced digital advertising to behaviour analysis and predictive analytics.


AI and Retail can work together to optimise customer experience, from forecasting and inventory management to recognising shoppers' emotional responses when purchasing items.


Banks can use AI and Machine Learning to track financial transactions and analyse user data. For example, AI will help them to anticipate the risks associated with issuing loans, such as customer insolvency or the threat of fraud.

Now, shall we dive into the six things everyone gets wrong about AI?

MYTH #1 - Machine Learning And AI Are The Same


Have you been caught up in the confusion between Artificial Intelligence and Machine Learning? I don't blame you. These two terminologies are usually used interchangeably, but they do not refer to the same thing.

Artificial Intelligence (AI) studies ways to build intelligent programs or machines that can creatively solve problems (this has always been one of the advantages of being human).


Machine Learning is the subset of AI that provides machines with the ability to learn and improve with experience (without being explicitly programmed). In Machine Learning, there are different algorithms such as Neural Networks that help solve problems.

MYTH #2 - AI Can Solve ANY Problem

AI is still in its infancy - it doesn't have the ability or human intelligence to solve unknown problems. Computers don't actually experience things the way we do, and this limits their understanding. You need to remember that AI is not a silver bullet. It's not going to magically deliver solutions if you collect enough data. There are some cases where alternative solutions might be more effective. AI must be built in a responsible way, and you need to know where it can be reasonably applied.

MYTH #3 - AI Is Going To Replace Humans In The Workplace

To be honest with you, you have very little to fear from AI. The first computer was built in 1991, and this didn't replace humans in the workplace. Artificial Intelligence isn't going to take your job. Humans and machines will need to operate hand-in-hand in the workplace. Years from now, humans will still be required to complete the higher value work, whereas machines will carry out monotonous tasks. There will also be new job roles introduced, for example, AI Ethics or AI Trainer. Don't worry; humans will always be a valuable commodity.

Myth #4 - It's Impossible To Trust AI

AI can be quite difficult to explain, and some deep learning algorithms are too complex even for their creators to understand. How can we trust AI when we don't truly understand how it works? Is there a dark side?

The answer is simple. No one can actually trust AI.

The point is that no human should need to trust AI because it's possible to engineer AI for accountability. We need to know that we can hold the humans behind that system to account.

Of course. There are some applications of AI, which obviously raise concerns, such as:

⮕ Identification Without Consent
⮕ Covert AI Systems
⮕ Normative & Mass Citizen Scoring Without Consent
⮕ Lethal Autonomous Weapon Systems (LAWS)

This is why the EU Ethics Guidelines For Trustworthy AI (EU) exist...

In order for AI to be deemed "Trustworthy", it must have two components:

(1) it should respect fundamental rights, applicable regulation and core principles and values, ensuring an "ethical purpose" and

(2) it should be technically robust and reliable since, even with good intentions, a lack of technological mastery can cause unintentional harm.

Myth #5 - Businesses Don't Need AI Strategies

If you still believe that AI is just for the likes of Google or Facebook, think again. AI is going to transform every business, in every industry. It's not really a matter of "if"; it's a matter of "when" you will need to create a strategy for AI. Every day, more and more businesses are turning to AI to meet their needs, whether that's personalised experiences for their customers or automating customer support.

Before you build your AI strategy, it might be worth asking yourself the following questions:

✔️Is your infrastructure robust and stable enough to handle AI?
✔️How are you going to deal with ethical and legal issues?
✔️What is your current data strategy?
✔️How are you going to plug the skills gap?
✔️What roadblocks are going to stand in your way?

    Myth #6 - Superintelligence Is Coming Soon

    For starters, there are three types of AI:

    1. Narrow / Weak AI - Narrow Range Of Abilities
    2. General / Strong AI - Equal To Human Capabilities
    3. Artificial Superintelligence - More Capable Than A Human

      At present, we have only realised Narrow / Weak AI. Even though these machines may seem intelligent, they still operate under a narrow set of constraints and limitations.

      Here are a couple of examples of Narrow AI:

      ⮕ Siri
      ⮕ IBM's Watson
      ⮕ Self-Driving Cars
      ⮕ Email Spam Filters
      ⮕ Drone Robots

        General / Strong AI are machines with that of human intelligence and have the ability to learn and apply their intelligence to solve a problem. In truth, we do not know what the human consciousness is, and we are unable to program a full set of cognitive abilities.

        And (drum roll...) Artificial Superintelligence are machines that are able to understand human intelligence, have become self-aware and can surpass humans in both intelligence and ability. I hate to disappoint, but we are a long way off of that happening.

        Have you fallen victim to one or more of these AI misconceptions? It's never too late to learn the truth.

        Our Artificial Intelligence (AI) training courses are developed and delivered by Dr Andrew Lowe, who has 20 years plus of experience working with high-performance computing. He has worked with high tech start-ups and large high tech engineering organisation using some of the world's most powerful computers.

        We have a range of Artificial Intelligence (AI) training courses for you, and the good thing is that you don’t need to learn to code:

        Artificial Intelligence (AI) Essentials
        Artificial Intelligence (AI) Foundation

        The BCS AI Foundation Pathway is also currently in development. You will be able to choose from 12 awards set within four key areas of AI:

        Artificial Intelligence (AI) Business Innovation
        Artificial Intelligence (AI) Data
        Artificial Intelligence (AI) Ethics
        Machine Learning And Other AI Techniques

        Each of the 12 awards is a qualification in its own right, carrying between 3 and 5 credits.

        If you take four awards (20 credits), one in each key area, you’ll get the BCS Artificial Intelligence (AI) Foundation Certificate.

        And if you continue further along the pathway and take eight awards (36 credits) - you can achieve a Foundation Diploma In AI.