What is artificial intelligence and what does the future of AI hold?

While computer processing capacity far exceeds that of humans, in many areas, the human brain remains superior. But is this set to change sometime soon? This question is often the topic of conversation when it comes to discussions about artificial intelligence (AI). It’s also an important question for the field of AI research, which aims to find ways to replicate the brain and its functions using computer science, neurology, psychology and linguistics.

What is artificial intelligence?

Artificial intelligence can be defined as a branch of computer science, whose goal is to create a technological equivalent to human intelligence. But what exactly is intelligence and how can it be reproduced using technology? A singular explanation doesn’t exist, and many theories and methodical approaches have been developed to answer these questions.

An exact definition of artificial intelligence is practically impossible given how hard it is to define the word “intelligence” itself.

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If artificial intelligence is to model human intelligence, how similar should AI be to human beings? Should the machine be built in a way that is identical to a human brain? Such an approach to simulation aims to achieve a complete replication of the brain’s functions.

Perhaps the machine should only have the appearance of a person, with a surface similarity to humans being sufficient? This phenomenological approach is centered on what humans actually perceive or experience when interacting with artificial intelligence. The underlying technical processes of the AI, however, do not need to display any similarities with its human counterpart.

Current AI technology is primarily being developed for technical tasks. This type of AI technology is less focused on mastering the art of human communication and more so on carrying out highly specialized tasks in an efficient manner. For these technologies, a restricted Turing test is used. If a technical system is able to perform at a level on par with a human (for example, when making a medical diagnosis or playing a game of chess), it is considered to be an artificially intelligent system. The ability to exhibit human-like competency in a specific task or area of knowledge has led to the development of two definitions of artificial intelligence: strong AI and weak AI.

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The vision: Strong AI

The definition of strong artificial intelligence refers to an intelligence that, with its diverse capabilities, is in a position to replace humans. While the universal approach of considering humans as machines has existed since the Enlightenment, it currently still remains a fiction.

Intelligence is not one-dimensional. It covers cognitive, sensory motor, emotional and social capabilities. Most of the current applications of artificial intelligence are in the area of cognitive intelligence, i.e., logic, planning, problem-solving, self-sufficiency and individual perspective formation.

The reality: Weak AI

On the other hand, the definition of weak artificial intelligence is one where the development and application of artificial intelligence take place in clearly defined, marked out sectors. This is the position that artificial intelligence finds itself in at this moment in time. Nearly all of the current uses of artificial intelligence can be defined as weak but also undoubtedly specialized. A good example of this is the development of self-driving cars, medical diagnoses and intelligent search 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 harmful, ethically speaking, than the research in superintelligence. The sectors where artificial intelligence is being applied are extremely varied. At the moment. AI is experiencing considerable success in medicine, finance, transport, marketing and, of course, online.

How does artificial intelligence work?

How does one even begin describing the operating principles of artificial intelligence? AI is only ever as good as the nature of its technical representation of knowledge. For this, there are two fundamental methodical approaches, namely the symbolic approach and the neuronal approach.

  1. With symbolic AI, knowledge is represented by symbols and operates with symbol manipulation. Symbolic AI approaches the processing of information from above, operating with symbols, abstract correlations, and logical keys.
  2. With neuronal AI, knowledge is depicted by artificial neurons and their connectors. Neuronal AI approaches the processing of information from below, simulating individual artificial neurons, which organize themselves into larger groups and together form an artificial neuronal network.
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Symbolic AI

The classic AI approach is symbolic AI. This touches on the idea that human thought can be reconstructed from a logically superior conceptual level, regardless of 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 also other logical activities like playing a game of 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.

Neuronal AI

Geoffrey Hinton and two of his colleagues revived neuronal AI research in 1986 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 operates with these days. It’s thanks to this learning algorithm that deep neuronal networks can continually learn and grow by themselves, overcoming the challenges where symbolic AI once failed.

Neuronal 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 neuronal network is trained. In robotics, for example, this is done with sensory motor data. From these experiences, the AI generates an ever-growing knowledge base. 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 is difficult to escape the influence of artificial intelligence in digital environments. For example, AI systems play a significant role in shaping the product recommendation you receive from online stores as well as the recommendations you receive 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 software 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 AIs with short-term memory.
  • Voice.ai: With the Voice.ai program, you can speak with a different voice, for example, that of a Hollywood star or another famous celebrity, in real time. The AI-based software is trained with user input, offering users the option to provide their own voice recording for new voice profiles.
  • 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.

The two sides of the AI coin

From blind optimism about progress to a simple refusal to acknowledge AI technology, intelligent technology elicits a range of emotions and reactions. This can be primarily attributed to there being both positive and negative future projections about how these technologies will change our lives. Here we have compiled the most important points from both AI enthusiasts and skeptics.

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

The new technology 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. Many supporters of a universal basic income see AI technology as a big opportunity, believing that the traditional model of paid labor will soon be replaced. 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 those using the technology.

Extraordinary performance

When it comes to tasks for the greater public good, artificial intelligence also has a significant advantage. 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 go so far as to 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. According to the World Robotics Report 2022 , the number of newly installed robots worldwide reached 517,385 units in 2021, a new record high. The AI industry is also experiencing remarkable growth worldwide, with the Global Artificial Intelligence Market Report citing that global funding for the industry had doubled, reaching $66.8 billion dollars.

Futuristic projects

Last but not least, artificial intelligence inspires the natural curiosity in humans. Already it’s being used for exploring oil sources and controlling Mars robots. It is 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 like the Silicon Valley icon Elon Musk have warned about the risks of artificial intelligence, despite being directly involved in its development. These critical voices also have the support of larger organizations and initiatives. The Future of Life Institute (FLI), for example, regularly mobilizes renowned critics to call for a responsible approach to technology.

Quote

“The pace of progress in artificial intelligence (I’m not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like DeepMind, you have no idea how fast - it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five-year timeframe. 10 years at most. This is not a case of crying wolf about something I don’t understand.” Elon Musk, Tesla founder and AI investor, during an interview in 2014

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

Inferiority of humans

One potential risk which many 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. The relationship between humans and this superintelligent technology could become problematic, with skeptics believing that it could eventually lead to humans being at the mercy of AI. 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.

Dependency on technology

An ever-growing dependency on technology is another cause for concern. One example that critics cite is the area of healthcare, where the use of nurse robots is already being tested. In this context, humans are increasingly becoming monitored subjects of technological systems. As a result, critics argue, humans are in danger of giving up a large chunk of their personal privacy and autonomy. It is not just in the area of healthcare that such concerns are being voiced, but also with the use of AI-supported video surveillance and intelligent algorithms online.

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. According to critics though, the processing of data through AI technology is becoming more and more difficult for users to understand and keep up with.

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, critics argue that 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. Critics argue that the more intelligent such technologies become, the higher the risk for influencing how opinions are formed.

Summary: Artificial intelligence

AI is one of the most exciting technologies out there and will continue to be in the coming years. It’s already being used in various industries and for a variety of purposes. AI, like all new technological advancements, will bring about major changes in our personal and professional lives. Humans, however, will not be replaced by AI in the future, but will instead be tasked with operating and working together with AI. The automation of recurring tasks is likely to save us a lot of time, time that we can invest in other areas of our lives.

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