Types of Artificial Intelligence (With Pros and Cons)

By Indeed Editorial Team

Published 6 May 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

The use of artificial intelligence (AI) is increasingly prominent in the workplace, especially in the digital age as companies seek new ways to improve their efficiency. Some professionals may value AI for its efficiency and accuracy, while others may fear the potential disadvantages this new technology can bring. Learning more about artificial intelligence can help you to make use of it effectively in the workplace. In this article, we discuss the definition of AI, explain the different types of AI available and describe its pros and cons.

What is artificial intelligence (AI)?

In contrast to the natural intelligence of human beings, artificial intelligence (AI) is led by machines. This process combines intelligent practices within the field of computer science and engineering. AI works through machine learning as the system develops an environment that simulates human intelligence to constantly improve with each learning experience. This enhances its ability to perform human tasks with increasing accuracy. For AI to function, it requires both specialised hardware and software programming to build machine learning algorithms. Examples of AI applications include natural language processing, speech and image recognition, robotics and remote sensing.

Grounded by the machine's ability to think rationally, AI allows efficient processing of data in large volumes, with algorithms to learn from repetitive patterns and correlations. Through a combination of algorithms and previous learnings, for example, on demographics and psychographics, AI develops a propensity model that can make predictions on future actions, beyond past behaviours. This exponentially expands the use of AI, not just for repetitive tasks, but also predictive actions. For example, a chatbot can begin to reply like a human after processing large amounts of questions and answers that commonly occur in text exchanges.

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Types of AI and their uses

The types of AI are dependent on the different levels of technology used. On a broad spectrum, AI can be differentiated into two categories, namely artificial narrow intelligence (ANI) and artificial general intelligence (AGI). The former refers to existing AI applications, which can perform human tasks based on programming but are unable to perform unprecedented tasks. AGI is a work in progress that functions in the same agility as a human brain, with cognitive abilities to learn and apply logic across domains, allowing improvisation in unprecedented situations. These are the four types of AI:

1. Reactive machines

These machines are the most basic type of AI. They're task-oriented and are not programmed according to previous memory. Rather than training it with previous learnings, this AI reacts to the given stimuli within the environment. One example of a reactive machine is a computer chess program. Other than the basic rules of chess, its machine learning doesn't include any human input. Instead, it considers all possibilities of each step and works out the next steps that provide the highest chance of winning.

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2. Limited memory

AI with limited memory doesn't only have the ability of reactive machines, it can retain the memory of past learnings by processing large amounts of historical data as a reference. This allows the AI to learn from the past and build experiential knowledge that enables the making of better, well-informed decisions. It's the most common type of AI in modern automated applications, such as smart self-driving cars and robotic cleaners. Combining both observational and pre-programmed knowledge, these automated machines can observe the environment to detect patterns or changes in their routes and adjust accordingly.

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3. Theory of mind

A theory of mind AI is not yet applicable in the present day, as it requires the AI to have the human emotional capacity to understand the thoughts and emotions that contributed to decision-making. Understanding this helps to predict human behaviours more accurately, which is essential in teamwork and communication. Given the complexity of human emotions and motivations, this type of AI is still hypothetical and requires large data sets to learn and remember the correlation between human emotional output and their corresponding behaviours. This can enable it to provide better responses to a wide variety of situations.

4. Self-aware

A self-aware AI is the most advanced version that's not in existence yet. It's where the AI isn't only capable of understanding human emotions, but also has its own thoughts, emotions and desires. This leads to the development of self-awareness. With the ability to not just replicate human behaviours, self-aware AI is an extension of the theory of mind AI as it possesses consciousness to achieve self-controlled thoughts and emotions.

Pros of artificial intelligence

With AI becoming increasingly prominent in all industries, especially in the areas of automation and robotics, here are some of the benefits of AI that explain its widespread adoption:

  • Availability: Unlike humans, machines can work continuously without any breaks or distractions and provide consistent quality of work. This ensures high productivity at all times, without requiring additional human resources and people to work overtime.

  • Accuracy: Through constant iterations and learnings, AI can achieve high accuracy in assigned tasks, keeping the likelihood of errors to a minimum. The increased precision is useful in detail-oriented roles and even medical applications, such as surgery simulations and radiosurgery, which allows for clean removals of tumours without damaging surrounding tissues.

  • Consistency: Once programmed, these machines function at high consistency, especially for repetitive tasks. By doing these tedious tasks, AI can free up the time for working professionals to focus on work that requires advanced thinking and collaboration, thereby improving their job satisfaction.

  • Efficiency: AI is able to process large volumes of data with accuracy and consistency within a very short time, beyond what any human can do. Based on rational thinking, it can analyse a situation quickly and objectively using a wide range of data to determine the best possible solution.

  • Risk-taking: In place of humans, AI machines can assist in dangerous missions that may risk human lives, such as minesweeping, bomb defusions and even space explorations. These machines can take part in such missions with higher speed and accuracy, hence increasing the probability of success as well.

  • Multitasking: While there are limits in the human capacity to multitask, AI machines can carry out multiple programmes simultaneously and with high accuracy. This allows working professionals to expedite the completion of menial tasks and paperwork to focus on in-depth research and analysis.

  • Evolution: The brilliance of AI is its ability to constantly improve with every iteration, enabling new innovations among every industry that help to enhance current working processes and resolve complex issues. AI brings about the evolution of the workplace, as the advancement of AI technology encourages working professionals to contribute in more significant ways.

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Cons of artificial intelligence

While the advantages of AI are numerous, it's important to be aware of its pitfalls to ensure AI is effectively and correctly used in the workplace. To fully fulfil the potential of AI, both companies and working professionals may wish to be mindful of its cons while planning to maximising the benefits to gain an edge over their competitors. These are some of the pitfalls of AI you may consider:

  • Job displacement: It's inevitable that with the deployment of AI, repetitive tasks that people undertook previously are now automated by AI, thereby causing role redundancies. To remain relevant, working professionals may equip themselves with more advanced skills and knowledge to build and operate AI, instead of getting displaced by it.

  • Functional limitations: The lack of emotional depth of digital assistants limits customer satisfaction, so there's still a need for human intervention where human interactions are necessary. AI is also task-specific and is only able to react based on past learnings, rather than infer future actions and behaviours, thereby limiting its ability to perform impromptu tasks beyond the programming.

  • Cost requirements: The initial setup cost for the development of AI is extremely high due to its high complexity. As it requires constant development to improve its efficiency and accuracy, the maintenance and iteration processes are also costly to sustain.

  • Data security: Using AI technology for data processing makes the system susceptible to external threats such as data hacking and computer viruses. Severe consequences in the over-reliance on AI may lead to compromised data, unauthorised access to personal data due to hacking and medical misdiagnosis due to erroneous codes.

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