What is artificial intelligence (AI)?

Artificial intelligence is a branch of computer science that aims to create a technological equivalent to human intelligence. But what exactly is intelligence and how can it be reproduced using technology? Numerous theories and methodologies have been developed to address these questions, however, establishing a precise definition of artificial intelligence has proven difficult due to the complex nature of intelligence itself.

How is AI defined? A look at different definitions

Most artificial intelligence has been developed to carry out technical tasks. The focus has been less on mastering human communication, and more on performing highly specialized tasks efficiently. For these types of technologies, a restricted Turing test is used to test if a system possesses the same abilities as humans in a specific field, for example, in medical diagnostics or chess. If it does, it’s considered an artificially intelligent system. This is just one type of artificial intelligence though. A distinction is made between this type of artificial intelligence, which is considered “weak” and another type which is considered “strong”. Below, we’ll take a look at these two different definitions of AI.

The vision: Strong AI

The definition of strong artificial intelligence, also referred to as general AI, refers to a type of intelligence that, due to its diverse capabilities, is in a position to replace humans. Intelligence has various dimensions, encompassing cognitive, sensory, motor, emotional and social capabilities. Most current applications of artificial intelligence are in the area of cognitive intelligence, i.e., logic, planning, problem-solving, self-sufficiency and perspective formation.

The reality: Weak AI

On the other hand, weak artificial intelligence, also known as narrow AI, is defined differently and refers to the development and application of artificial intelligence for clearly defined use cases. This is the current state of artificial intelligence. Nearly all of the current uses of artificial intelligence can be defined as weak AI but also undoubtedly specialized. A good example of weak AI is the development of self-driving cars, AI for medical diagnostics and intelligent search and automation algorithms.

Over the last few years, research has made groundbreaking success in the area of weak AI. The development of intelligent systems in individual sectors has shown itself as not just immensely practical but also as less controversial, ethically speaking than the research into superintelligence.

How does artificial intelligence work?

How artificial intelligence works depends on how knowledge is represented within the AI system. There are two fundamental approaches to representing knowledge:

1. Symbolic AI: With this approach, knowledge is represented by symbols and operates with symbol manipulation. Symbolic AI approaches the processing of information using a top-down approach, operating with symbols, abstract correlations and logical keys.
2. Neural AI: With this approach, knowledge is depicted using artificial neurons and connectors. Neural AI approaches the processing of information from the bottom up, simulating individual artificial neurons, which organize themselves into larger groups and together form an artificial neural network.

Symbolic AI

Symbolic AI is considered the classical approach. It is grounded in the idea that human thought can be reconstructed from a higher-level framework based on logic and concepts and doesn’t need to rely on concrete experiences (top-down approach). Knowledge is represented by abstract symbols, including written and spoken language. Machines learn to recognize, understand and use these symbols on the basis of algorithms. The intelligent system retrieves its information from expert systems.

Classic uses of symbolic AI are word processing and speech recognition but it has also been used for other logical activities like playing chess. Symbolic AI works based on set rules, and with increasing computing power, can solve problems of increasing complexity. With the help of symbolic AI, IBM’s Deep Blue was able to win a game of chess against Garry Kasparov, who was the world champion at the time.

Neural AI

In 1986, Geoffrey Hinton and two of his colleagues revived research into neural AI and with it the research field of artificial intelligence. The further development of the backpropagation algorithm created the basis for deep learning, which nearly all AI works with these days. Thanks to this learning algorithm, deep neural networks can continually learn and grow by themselves.

Neural artificial intelligence splits up knowledge into tiny functional units known as artificial neurons. These neurons then form groups, which become increasingly larger (bottom-up approach), resulting in a diverse and branched network of artificial neurons. Unlike with symbolic AI, the neural network is trained. In robotics, for example, this is done with sensory motor data. With the help of machine learning, the AI generates a knowledge base that continuously grows. And this is exactly where the big breakthrough happens. While this training requires a significant amount of time, the system is now in a position to learn independently.

What are some examples of artificial intelligence?

Whether it’s facial recognition, voice assistants or translation software, AI has become a part of our everyday lives. Even if you consciously avoid using such tools, it’s difficult to escape the influence of artificial intelligence in digital environments. For example, AI systems play a significant role in shaping the product recommendations you receive from online stores as well as recommendations from platforms like YouTube and Netflix. These systems are designed to provide you with suggestions that are increasingly tailored to your preferences.

Below are some examples of how artificial intelligence is currently being used:

• ChatGPT: ChatGPT is an AI chatbot that was developed by Open AI. The large language model (LLM) can understand text inputs and answer questions as well as generate, rewrite and translate texts.
• RankBrain: RankBrain is an artificially intelligent algorithm from Google that was originally developed to better understand search queries that may be unknown at the time of the first search. In 2015, Google announced that Rankbrain, after links and content, was the third most important factor of over 200 ranking factors in Google Search. This means that RankBrain has a big influence on SEO.
• DeepMind: Purchased by Google in 2014, DeepMind is a company that has created many innovative AI technologies including AlphaGo, the computer program that mastered the board game Go. In April 2023, Google announced that they were merging the company with their in-house AI division, Google Brain. DeepMind has distinguished itself in the field of AI research by equipping their AI systems with short-term memory.
• DALL-E: The AI system DALL-E can create impressive and unique 2D and 3D images from written input in a matter of seconds. The open beta version of OpenAI’s software has been available since September 2022. According to the development team, over two million images are created with the application every day.
• Amazon’s Alexa and Apple’s Siri: AI assistants Alexa and Siri use voice control to help users with everyday tasks like retrieving information. Using speech synthesis, they can provide answers in natural language.

What opportunities and risks does AI pose?

Predictions about how AI will change our lives are both positive and negative. Below, we outline the key advantages and disadvantages of AI as well as the opportunities and risks associated with it.

What are the advantages and possibilities of AI?

There is a whole range of advantages and possibilities when it comes to AI. The most important advantages are undoubtedly in the world of work, where it can be highly efficient and dramatically improve economic prospects.

Job creation and reduced workload

AI could bring about valuable new jobs and in general, lead to an economic upsurge. One thing that all experts agree on is that the technology will have a radical impact on the job market as a whole. The improvements and simplifications that AI is capable of bringing about could also mean more free time for people.

Comfort

Supporters of AI view each technical advancement as an opportunity for greater ease and comfort in everyday life. Examples of this include self-driving cars and intelligent translation software. In general, such developments make life considerably easier for consumers.

Extraordinary performance

When it comes to tasks for the greater public good, artificial intelligence also provides significant benefits. There is no denying the fact that machines have a much lower error rate than humans, and their performance potential is enormous. In the healthcare and legal sectors, in particular, the versatility of intelligent machines is seen as especially promising. While experts don’t expect that judges will one day be replaced by machines, artificial intelligence can help judges to more quickly recognize patterns in a court case and reach objective conclusions.

Economic advantages

There is also the promise of large financial gains for the industries that are creating the technology. The AI industry is experiencing remarkable growth worldwide, with the Global Artificial Intelligence Markets Report citing that global funding for the industry had doubled in 2021, reaching $66.8 billion. In the subfield of generative AI, funding increased eightfold from 2022, reaching $25.2 billion in 2023.

Futuristic projects

Last but not least, artificial intelligence inspires the natural curiosity of humans. Already it’s being used for exploring oil sources and controlling robots on Mars. It’s safe to assume that the continued development of the technology will lead to an increase in the number of fields and use cases that it can be used for.

What are the disadvantages and risks associated with AI?

Prominent experts have warned about the risks of artificial intelligence, despite being directly involved in its development. Such criticism has also found support amongst larger organizations and initiatives. The Future of Life Institute (FLI), for example, regularly mobilizes renowned critics to call for a responsible approach to technology.

Here are just some of the risks associated with artificial intelligence:

Human inferiority

One potential risk that many people fear, and which has often been a favorite subject of science fiction writers, is the development of a superintelligence. This term refers to a technology that optimizes itself to the point where it is no longer reliant on humans. Although most researchers view an intentionally malicious AI as being highly unlikely, many view the possibility of artificial intelligence becoming competent enough to carry out activities independently as highly plausible.

Technological dependency

An ever-growing dependency on technology is another cause for concern. One example is in the area of healthcare, where the use of nurse robots is already being tested. In this context, humans are increasingly becoming the monitored subjects of technological systems. As a result, people may be in danger of losing some of their personal privacy and autonomy.

Data protection and the distribution of power

Intelligent algorithms are now able to process growing datasets more efficiently than ever. This is particularly good news for the online retail sector. However, the processing of data through AI technology is becoming more and more difficult for consumers to understand and keep track of.

Filter bubbles and selective perception

Online activist Eli Pariser has drawn attention to what he sees as a further risk of artificial intelligence: filter bubbles. If algorithms only show content to a user based on their previous online behavior (personalized content), it is very likely that their view of the world will get narrower and narrower. Or at least this is the concern. AI technologies could promote selective perception, reinforcing a growing distance between individuals who have different ideological views.

Influence how opinions are formed

Additionally, AI technologies have the ability to control public opinion. The reason for this sort of thinking is the existence of technologies that have very detailed information on their users, as well as the presence of social bots that can influence public discussions.