What is the big fuss about AI? Is it going to replace you at work? These are some of the questions we are trying to address in this AI conversation.

The first thing that comes to mind when anyone mentions AI is Will Smith’s movie, I Robot, released in 2004.

The movie had a Robot called Sonny, which was more advanced than the other robots.  Sonny did not follow the three rules of robotics: A robot shouldn’t injure a human, follow orders from a human, and protect itself without breaking the first two laws.

It seemed like Sonny was rational, with emotions like it had a human mind. These are features of Artificial Intelligence.

Unlike what the movie was trying to paint, AI isn’t just all about robots. It has more extensive applications than you could imagine: navigation, automation, traffic control, language processing, and Chatbots like Chat GPT, among others.

Is AI an interesting Venture? Yes, it is. Is it a threat to job security? We are going to find out. But first, let us see where AI came from, what it is, and how it works.

Brief Evolution of Artificial Intelligence 

In 1937, The Wizard of Oz film had a Robot called Tin Man as part of the cast. Tin Man was a robot that had emotions. The film probably got engineers thinking about AI.

In 1950, a young man called Allan Turing wrote in His paper, ‘Computing Machinery, and Intelligence,’ that it was mathematically possible for Computers to reason and solve problems like humans. However, the idea was ahead of time, and had to wait for technology to catch up. 

In the 1980s, a programmer, John McCarthy, wrote the first AI programming language.  By this time, computers were cheaper, faster, and capable of storing data.

Between 1982 and 1990, the Japanese government invested $400 million to further develop AI in the FGCP (Fifth Generation Computer Project). They did not meet their objectives but indirectly led to further AI research and development. 

Photo by Pavel Danilyuk: https://www.pexels.com/photo/a-person-playing-chess-8438944/

In 1997, a chess-playing computer program defeated the world chess champion, Gary Kasparov. It was a massive step in terms of computer decision-making.

Let’s fast forward to the 2000s when AI research expanded in natural language processing, computer vision, and automation. 

Today, AI has made huge strides and is looking to grow even more. AI is applied in industries like manufacturing, Healthcare, transport, Agriculture, Finance, and research. Chat GPT developed by Open AI is a popular language processing tool that provides human-like conversations.

Artificial Intelligence

Artificial means made by a human being as a copy of something natural. Intelligence is the ability to acquire and apply knowledge.

Artificial Intelligence is the ability of a computer to acquire and apply knowledge to model the human mind. 

Can machines think and act like humans? Can they be rational? Is this a possibility, based on the progress we have seen so far? Let us find out how AI works.

How does AI work?

Computers learn and adapt by repeatedly processing massive amounts of data to identify patterns and using them to make decisions. For instance, AI can play games multiple times and figure out how to play and win.

The point of AI is to model a human mind and use it to solve complex problems. The computer can quickly analyze and process massive amounts of data continuously and draw conclusions that determine its next step. The more it interacts with data, the more it learns and makes better decisions. That’s how our mind works. Right?

You must be asking yourself how exactly these computers solve the problems. They use algorithms which are sets of instructions for solving a problem. 

Algorithms are the building blocks of any computer program. You must have heard the word algorithm, mainly associated with social media. Social media platforms set rules to determine which type of posts their users can see in their feeds. Therefore, if your post aligns with these rules, more people will see it. 

Let’s say you want to make your Mum’s favorite meal. She hands you the recipe. The recipe, in this case, is the algorithm. It will determine the ingredients (input) that determine how sweet the food served is( output). Makes sense? Let’s continue. 

AI has subsets called Machine learning and Deep learning that allow computers to take in information, similar to the human brain. Don’t worry, we will get into the details shortly.

Machine learning 

Photo by Alex Knight: https://www.pexels.com/photo/high-angle-photo-of-robot-2599244/

Machine learning is a subset of AI that allows machines to learn from data and improve performance without being precisely programmed.

Remember this quote? ‘Experience is the best teacher.’ That is what happens when Machines automatically learn from past data or experiences by being guided by algorithms that help them to analyze data and make decisions. 

Imagine a child learning how to read by memorizing the names with the teacher’s help. When the child is old enough, they can read books independently. Similarly, Machine learning can be supervised, unsupervised, or reinforced.  

Supervised learning is where we train machines by giving them data points associated with the output. The computer learns the correct input features matching the output by identifying patterns. Supervised learning is used in email spam detection and predicting house prices.

In unsupervised learning, we do not provide any data points for the computer, so they identify the patterns themselves. It is used in clustering data.

In unsupervised learning, the machine interacts in a given environment and gets feedback in the form of a reward or a penalty. An example of reinforcement learning is AlphaGo and robotics.

Machine learning applications include speech recognition, self-driving, automatic language translation, and virtual personal assistant, among other tasks.

Deep Learning

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Deep learning is supervised computer learning that allows automatic training inputting unstructured data. The machine then uses the data to distinguish different categories of data.

Imagine you want to learn to play the saxophone. You’ll start by learning music basics. After that, you can now play some simple melodies. After that, you can now advance to the complex songs.

Similarly, in Deep learning, we add layers to learn from data. In the same way, you learn music in bits, computers learn in layers. These layers of data are what we call Neurons. An Artificial Neuron network has nodes similar to an actual human brain. The three layers include the input, hidden, and output layers.

Deep learning algorithms use the training or optimization method, where they train by adjusting their weights and biases from large amounts of data. The process allows machines to differentiate between predicted outputs and actual outputs.  

Deep learning applications include computer vision, natural language processing, voice, and image recognition. 

Categories of AI

Weak AI

Artificial Intelligence is Weak when it only performs specialized tasks. These tasks often have predestined answers and are predictable. Some examples of Weak AI include Siri and Alexa, voice-based personal assistants.

Strong AI 

On the flip side, Strong AI is a theoretical branch of AI. This type of AI can mimic human intelligence allowing machines to learn and make decisions independently, adapt to changing environments, and improvise.  Remember Sonny at the beginning of this article? He would be a perfect example of what Strong AI would look like.

Will AI replace humans at work?

Photo by Pavel Danilyuk: https://www.pexels.com/photo/a-robot-holding-a-cup-8439093/

The truth is that some jobs are at a higher risk of being replaced by AI than others. However, you should realize that AI wasn’t meant to replace but to supplement human beings. As we speak, AI is being used in some manufacturing, data entry, marketing, and customer service jobs. 

AI can only work with the data input. It doesn’t have a mind to discover new data or improvise the way human brains do. If your job requires complex emotional skills, creativity, cultural background, and empathy that machines cannot offer currently you don’t have to worry. It would take many years to develop AI that can replicate this. 

So what next? Do we fight against AI? No. We need to embrace them and harness them as tools to make our work easier and more efficient, similar to what we did with computers and mobile phones. 

You can let AI do the repetitive work for you as you focus on creative tasks. AI can automate most of your tasks, like scheduling when your social media post will be published, as you focus on a task that needs your attention. The good news is that these tasks still require human interaction, decision-making, and empathy that only humans can offer.

As much as AI can do most of the work, it still can’t deliver accurate human judgment. It also needs human supervision to ensure it aligns with societal goals and values.

What does AI look like in the future?

The future of AI is Artificial General Intelligence. It is a hypothetical idea, and it would be interesting to see it come to reality. 

AGI can perform complex tasks, learn from different kinds of data, and effectively communicate the output with humans. AGI would improve sectors like Education, Medicine, Research, and Transportation.

We saw AI deployed in the Facetime feature of the Apple Vision Pro, where the device produces a digital avatar of your face since the cameras can only see your eyes. The Apple Vision Pro will be released next year. 

AI can quickly analyze data and come up with patterns and links that could be useful in the medical field. Thus, it will hasten the research and discovery process. Medical staff could use AI to give consultation services. AI wearables could help detect diseases like cancer at an early stage. 

AI could help offer other medical services such as Therapy, drug prescriptions, and even fitness and wellness to their patients. It would help in giving disease management a holistic view by offering treatment plans and coordination of the patient’s health.

Our take

The purpose of creating machines is to make our work easier and that is what AI is doing. The best cause of action to take is to embrace the change and explore how to use AI in your line of work. 

So far AI has had a great impact on how human beings work, and we highlighted that AI wasn’t created to replace human beings but to help us. A collaboration between Humans and AI would help us reach our potential. Why don’t you start using AI  to make your work more efficient?