Ever notice how your phone suggests the next word you're about to type? This simple feature is an example of Artificial Intelligence (AI).

AI refers to the development of intelligent machines capable of tasks traditionally requiring human cognitive abilities, such as visual perception, speech recognition, and language processing.

Even though AI is everywhere these days, from schools to workplaces, a lot of people are still unsure what it all means and how it applies to them. This guide will help you simply understand what AI is, showing how it applies to parts of your everyday life and greater parts of society.

What is AI?

AI, or artificial intelligence, is the development of computer systems that can perform tasks that normally require human intelligence. These tasks may include visual perception, speech recognition, decision-making, and language translation.

The term "AI" originates from the concept that if intelligence is a natural aspect of organic life, then its existence elsewhere is artificial. The effectiveness of AI depends on the quality of the algorithms and machine learning techniques that govern its operations. The capabilities of AI in performing specific tasks are limited by the quantity and quality of the input data it receives, as well as repetition.

How does AI learn?

AI learns through Machine Learning, which refers to training a set of algorithms on large amounts of data to recognise patterns, that help guide predictions and decisions, they store past commands, similar to how the human brain learns by memorisation.

How Machine Learning (ML) works

The Programme is taught to make reasonable predictions by the data it is given, which it analyses to find patterns. Based on these patterns, the program builds a set of internal rules—like a "guessbook" for systemic predictions, it then evaluates the accuracy of these predictions by running through the set of labelled training data provided and determines if the predictions match its sample data. This comparison helps assess how well the programme's internal rules perform at identifying data. 

The programme uses the evaluation results to optimise its performance and learn from its errors. It adjusts its internal settings, to refine the programmerogram's predictions for future encounters. Through this learning process, the machine learning program gradually becomes more adept at whatever task it's trained for based on the data it's exposed to.

Types of Artificial Intelligence

AI is grouped into three capability types: General AI also known as Artificial General Intelligence or AGI, Narrow AI also known as Artificial Narrow Intelligence or ANI for short and Super AI known as Artificial Super Intelligence, ASI for short.

Narrow AI is designed to excel at specific tasks within a well-defined scope of expertise and lacks general intelligence. Examples include voice assistants like Siri, Alexa, and Google Assistant. ChatGPT is also an example of ANI, as it is programmed to generate text responses to prompts it's given.

General AI possess a form of general intelligence, allowing them to adapt, learn and apply knowledge across various domains, it is essentially AI capable of human-level, general intelligence. Theoretically, AGI could perform any human job, from cleaning to coding, although there are currently no real-life applications of such use cases.

Artificial Super Intelligence (ASI) is a hypothetical AI system that surpasses human intelligence. The Matrix movie franchise (1999) explored this concept. It showcased ASI with advanced cognitive abilities, capable of manipulating reality, controlling humans, and surpassing any human capabilities.

Underlying AI technologies

Neural networks

Modelled after the human brain, neural networks are made up of interconnected artificial neurons. These artificial neurons, learn by receiving, processing, and transmitting information to other tiny machines within the network. By constantly adjusting these connections, the network learns to identify patterns within data. This makes them spot patterns in things like photos. For example, they can classify objects in photos, detect faces, and even differentiate between a Golden Retriever and a Poodle. It’s no wonder companies like Google, Apple and Facebook use them to make your photo searching and tagging easier.

Deep Learning

Deep learning builds on this idea of Neural networks. But in this case, multiple layers of these neural networks stack up against each other and build knowledge layer by layer. This clever structure allows deep learning systems to tackle complex problems. For example, by analysing millions of medical images, they can spot subtle patterns that doctors might miss, and potentially help to identify diseases earlier. 

Special types of deep learning models, like GPT-3, can understand the flow of conversation, just like you do when you chat with a friend. This lets them do amazing things like analyse emotions in text or even translate languages on the go.

Reinforcement learning

The AI system learns through trial and error, just like a child exploring its surroundings. The system interacts with a simulated environment (or sometimes the real world) and receives rewards for desired actions and penalties for mistakes. 

This feedback loop allows the system to learn optimal behaviours over time.

AI has numerous positive impacts. It enhances efficiency across sectors, improves accessibility to technology, and offers economic opportunities for African businesses and startups. 

Now, let’s explore specific AI applications.

How is AI used today?

The applications of AI are rapidly expanding, we have begun to see applications of AI from healthcare, with advanced diagnostic systems, to self-driving cars, from assisting with school projects to streamlining tasks in the workplace, increasing efficiency and potentially freeing up our time for other endeavours. 

Specific applications of AI include:

• Business & Manufacturing: 

Automation helps streamline repetitive tasks like fraud detection, market analysis, and even power production lines. AI goes a step further by predicting equipment failures and cyber threats, keeping businesses one step ahead. In retail, AI now personalises shopping experiences, manages inventory, and optimises advertising. You would notice when browsing through Jumia or SHEIN, that the system suggests relevant products based on your preferences and browsing history. This dynamic personalisation keeps shoppers engaged and increases the likelihood of conversions.

• The Creative Industry:

In sectors such as design, advertising, and media, AI-powered tools are streamlining tasks that range from mundane administrative duties like note-taking to complex creative processes. By so doing, freeing up human creatives from manual efforts to focus on ideation, innovation, and strategic decision-making, to boost productivity.

AI also helps to minimise errors and enhance operational efficiency across creative projects. Rather than replacing creativity, AI partners with human creatives to expand possibilities. By learning from data and suggesting novel approaches, AI enhances the creative process and fosters innovative outcomes.

Tech African startups too, are harnessing AI across sectors to build more applications and drive competitiveness regionally.

• Education: 

AI-powered tutors like Amplify LEAP and Duolingo offer AI-powered learning assistance and personalised support and feedback, and others like Owl Tutor provide interactive coaching in various subjects.  

Virtual Reality simulations can further enhance education with their ability to provide students with hands-on experiences through simulations, allowing them to explore and interact with complex concepts, environments, and scenarios that may not be readily available or feasible in a traditional classroom setting.

• Transportation & Agriculture: 

Today, AI can optimise traffic flow unlike conventional traffic lights, which operate on fixed schedules or basic sensor-triggered mechanisms, AI-enabled systems revolutionise traffic signal control by continuously adapting to real-time traffic dynamics. These sophisticated systems rely on AI algorithms that continually assess incoming data streams from diverse sources, including traffic sensors, cameras, GPS devices, and other IoT technologies, predict vehicle maintenance needs through specialised systems, and improve overall logistics. 

AI tools can analyse weather, soil, and crop data to help farmers better planting, irrigation, and fertilisation. Farmers can make data-driven decisions to maximise crop yields, reduce resource usage, and mitigate risks by harnessing the power of machine learning algorithms and data analytics.

• Entertainment: 

AI recommends movies, music, and books based on user preferences. Netflix for example utilises machine learning algorithms to analyse and monitor users' preferences and watching habits and recommend personalised suggestions intended for specific audiences.  

While AI enhances movies and games with realistic CGI, it has gone further than just making cool special effects in movies and games. It's creating more lifelike characters, personalising entertainment experiences, and even building entire worlds that respond to you.  

What concerns surround AI in Africa?

AI in Africa brings both opportunities and challenges. Governments are working to create rules that ensure AI is used responsibly, protecting people's data and managing risks. International cooperation is essential to establish global standards and share knowledge.

Educating the public about AI is vital, so people understand its benefits and potential issues. This includes using media and community discussions to spread accurate information.

Key ethical concerns include:

• AI biases can lead to unfair decisions in areas like hiring, loans, and law enforcement.
• AI thrives on vast amounts of data, and if this data is collected, stored, or used without proper safety measures, it can lead to privacy violations.
• Tasks that are repetitive, rule-based, and require minimal human judgment are particularly susceptible to automation. This could lead to significant job losses in such sectors.

By addressing these issues, AI is sure to benefit everyone and minimise harm.

FAQs: Common Questions about AI

Will AI take over our jobs?

AI and automation are changing the job landscape. While some tasks will become automated, new opportunities will emerge. To thrive, adaptability and skill development are crucial. 

Can AI become sentient?

It’s unlikely. Current AI focuses on tasks and lacks emotions or consciousness. While it will get more sophisticated, true sentience remains a scientific debate.

Is AI dangerous?

AI has vast benefits, but misuse is possible. Ethical development prioritising fairness and human well-being is essential.

What type of AI is ChatGPT? 

ChatGPT is a generative AI. Users input prompts to receive humanlike images, text, or videos created by AI.

How do you make an artificial intelligence?

Generally, creating an AI involves identifying the problem you want the AI to solve, collecting data, then training algorithms using the data you organised. Platforms like Microsoft Azure and Google Cloud assist in building and deploying AI.

Who invented artificial intelligence?

British pioneer Alan Turing laid early AI groundwork. John McCarthy coined the term “artificial intelligence” in 1955.

What are the key trends shaping the field of Artificial Intelligence in 2024?

Expect innovations in personalised medicine, industry automation, cybersecurity, education, and sustainable applications.