In today’s world, where artificial intelligence permeates all areas of our lives, numerous myths and misconceptions have emerged around it. Many people succumb to illusions about AI’s capabilities and limitations, either due to ignorance or influenced by media portrayals. The following text identifies and debunks the most common misunderstandings about artificial intelligence, which often lead to exaggerated expectations or unfounded fears.

1. Myth: AI is smarter than humans

Many people believe that artificial intelligence is already smarter than humans. In reality, it’s a statistical tool that connects words and concepts based on probabilities and patterns recognized in its training data. If some AI outputs seem impressive, it may be due to low expectations or comparison with the average communication we typically experience.

AI cannot truly understand abstract concepts like quantum physics or resolve subjective questions like “does pineapple belong on pizza?” although it can compose convincing text on these topics. Artificial intelligence can write essays, but without a genuine understanding of the subject matter, meaning humans are still needed to help develop these complex topics further.

However, with AI, humans can certainly make some tasks in this process somewhat (significantly) easier, and AI can genuinely help accomplish a given activity faster (such as data analysis, text summarization, search, finding fact-checking resources, etc.) or assist in developing one’s own thoughts.

2. Myth: AI is truly creative

The creative abilities of artificial intelligence are often overestimated. When AI creates a poem or musical composition, it’s not an original expression of creativity, but rather a sophisticated recombination of existing patterns (i.e., again something created by humans, or by AI based on input from humans or other AI, which again needs some instruction/input from humans in that initial version). It’s similar to a musician composing a song primarily from proven melodies and choruses – the result may sound good but lacks an authentic creative breakthrough.

AI doesn’t experience “aha” moments or any inspiration. The creation of artificial intelligence is essentially assembling a puzzle from pieces that have previously proven successful, without truly understanding their meaning or emotional impact. It lacks motivation, emotional connection to the work, and authentic artistic vision.

3. Myth: AI has real emotions

When AI appears friendly, empathetic, or angry, it’s merely simulating these states, not experiencing genuine emotions. The system was designed to use language in a way that meets human expectations in social communication.

Attributing emotions to artificial intelligence is a form of anthropomorphization – the tendency to assign human characteristics to inanimate objects. In reality, it’s a collection of algorithms without subjective experiences. A language model has no feelings, even if its responses may create the impression of personal interest or affection.

4. Myth: AI understands what it writes

AI has no real understanding of the text it generates. It resembles a highly sophisticated system for predicting subsequent words rather than a being with consciousness and comprehension. It cannot distinguish truth from fiction based on its own judgment – it merely reproduces patterns it has learned.

When AI claims something false or nonsensical, it’s not because it’s “mistaken” in the sense of human error, but because its algorithm evaluated this response as statistically probable in the given context.

5. Myth: AI has perfect memory

Despite advanced capabilities, current AI systems have significantly limited “memory.” Most can only work with information provided within a single conversation, and once the session ends, all history disappears. Even systems with activated long-term memory have considerable limitations.

AI doesn’t remember your previous interactions unless they’re part of the current context. It’s not like a human relationship, where the other party truly builds a long-term memory of your person and your preferences.

6. Myth: AI never makes mistakes

AI presents its answers with a conviction that can create an impression of infallibility. In reality, however, it often makes mistakes, both factual inaccuracies and logical inconsistencies. These errors can be all the more dangerous because they’re presented with a high degree of confidence.

The problem is that AI doesn’t know what it doesn’t know (or that it doesn’t know something). It lacks genuine metacognition – the ability to recognize the boundaries of its knowledge. Instead, it will attempt to generate an answer even in cases where it doesn’t have enough relevant information. Therefore, you must thoroughly verify everything that AI outputs.

7. Myth: AI will soon replace most human work

Concerns that AI will replace human work are partially justified but often exaggerated. Artificial intelligence excels in routine, repetitive tasks that can be precisely defined. Professions requiring creativity, empathy, social intelligence, critical thinking, and complex decision-making in unstructured situations remain the domain of humans.

AI likely won’t replace entire professions but rather change the nature of work. People whose jobs consist primarily of simple, predictable activities are most at risk.

Artificial intelligence will undoubtedly have a significant impact on how we use our brains and how our cognitive functioning will evolve. This influence can have both positive and negative effects on human thinking.

With the increasing availability of instant answers through AI assistants, there’s a risk that we will increasingly rely on external sources instead of building our own cognitive structures and knowledge. This phenomenon can lead to several significant changes:

• Weakening of deep concentration ability – the immediate availability of information can disrupt our ability to focus long-term on complex problems.
• Reduced motivation to build deep knowledge – why learn and remember facts when we can quickly look them up anytime?
• Superficial information processing – we get used to quick but shallow content consumption without thorough analysis.
• Dependence on external cognitive tools – the risk that we’ll stop developing our own mental abilities in favor of outsourcing thinking.

Cognitive specialization – people may begin to specialize in aspects of thinking that AI handles poorly, such as creativity, ethical reasoning, or interdisciplinary synthesis. While memory and computational abilities will be increasingly delegated to AI, humans can focus on uniquely human forms of intelligence.

New forms of literacy – there will be a need for a new type of literacy – the ability to effectively formulate queries for AI, critically evaluate its outputs, and integrate them into one’s own thinking. This “AI literacy” may become a key skill.

Cognitive symbiosis – instead of mere dependence, a more complex relationship may develop where AI and the human brain function in symbiosis, complementing each other and strengthening their respective strengths. For example, AI can process details and routine aspects of problems, while humans focus on strategic, creative, or value aspects.

Polarization of cognitive abilities – society may divide into those who can work synergistically with AI and develop their cognitive abilities, and those who become cognitively dependent and lose the ability to think critically on their own.

Transformation of educational systems – educational institutions will be forced to rethink their goals and methods. Instead of memorizing facts, education will likely focus on developing skills such as critical thinking, creativity, adaptability, and ethical reasoning, which AI cannot easily replace.

To minimize negative impacts and maximize benefits, it would be appropriate to consider the following approaches:

• Conscious use of technology – developing “digital hygiene” and strategies for maintaining cognitive autonomy.
• Redesign of educational curricula – greater emphasis on metacognitive skills, critical thinking, and the ability to learn.
• Promotion of “deep reading” and focused thinking – active cultivation of the ability for deep concentration and complex reasoning.
• Balanced approach to technology – finding a balance between leveraging the benefits of AI and maintaining one’s own cognitive abilities.
• Intergenerational dialogue – connecting digital natives with generations who have experience with pre-digital forms of thinking and learning.

The influence of AI on human thinking is not predetermined – it depends on how consciously and strategically we approach these technologies, and on the social and educational systems we create around them.

8. Myth: AI has its own opinions and values

When AI expresses an opinion on a controversial topic, it’s not a genuine stance based on values and beliefs, but a statistical prediction of what type of response is expected in the given context. AI has no values, interests, or convictions of its own.

The consistency of AI opinions depends on the system’s settings and training data, not on an authentic moral compass. With different inputs or parameters, the same system can hold contradictory positions. See also the term Neural Network/Neural Networks, and the article Machine Learning and Artificial Intelligence – how they are related, what differentiates them, and what their practical applications are.

9. Myth: AI is perfectly objective

AI is sometimes considered an objective source of information because it’s a “machine” without personal interests. In reality, however, AI reproduces and sometimes amplifies biases and distortions contained in the data on which it was trained.

These systems are created by humans and trained on data created by humans, which inevitably introduces human perspectives and values into their operation. The apparent neutrality is an illusion – AI is not a superhuman arbiter of truth.

10. Myth: AI perfectly handles technical tasks

In technical fields such as programming, AI can appear particularly competent, but even here it has significant limitations. Code generated by artificial intelligence often contains errors, inefficient procedures, or security risks that require human review and correction.

AI has no real understanding of the problem domain or the ability to test the functionality of its solutions. Programmers with critical thinking remain essential for developing reliable and efficient software.

11. Myth: AI will soon become conscious

With the growing presence of artificial intelligence in everyday life, there’s also an increasing number of myths, distortions, and misunderstandings about what these systems truly are – and what they are not. Modern language and multimodal models, such as ChatGPT, Gemini, or Claude, can create texts, translate, analyze documents, or create images and videos. These capabilities appear sophisticated, so it’s no wonder that in some media and public debates, there are claims that artificial intelligence “is almost thinking” or is “on the threshold of consciousness.” These claims are, however, fundamentally misleading.

For example, in 2022, a statement by Google engineer Blake Lemoine garnered strong media attention when he stated in an interview with The Washington Post that the language model LaMDA “is self-aware” and “wants to be respected as a person.” Google officially rejected this claim, stating that LaMDA does not have consciousness and that the engineer approached the system with human bias. Nevertheless, this opened a wave of speculation about whether we are witnessing the emergence of a new form of intelligence.

In reality, however, current artificial intelligence – even in 2025 – does not possess any consciousness, self-awareness, or understanding in the human sense.

AI today:

• has no subjective experience (qualia),
• does not perceive itself as an entity,
• does not create autonomous goals,
• is not aware of the consequences of its behavior,
• has no inherent motivation or values.

AI is a computational tool. Its outputs are based on the analysis of an enormous amount of data and learning based on probabilistic patterns. It cannot understand the meaning of words, does not think about the world, does not ask questions, and has no internal experiences. It merely mimics patterns it has learned from previously existing data. By being able to write human-sounding texts, it creates the illusion of understanding, but it’s just sophisticated mirroring.

It’s important to remember that AI itself does not want, feel, or desire. It has no motivations or goals beyond those explicitly assigned to it. And although in 2023, warnings about “uncontrolled superintelligence” were voiced from some technological circles (for example, a letter signed by Elon Musk, Steve Wozniak, and others), none of the existing systems comes even remotely close to autonomous decision-making. Even those who signed these letters often acknowledge that the risk is not in the current technology, but rather in how people handle it.

What would be needed for AI to have consciousness?

To even talk about AI potentially achieving consciousness, we would first need to resolve the question of what consciousness actually is. And we cannot do that yet. Philosophers, neurologists, and cognitive scientists have been trying to answer this question for decades, but without a consensus. We don’t know exactly what in the brain causes us to have subjective experience, so-called qualia. Without understanding this phenomenon, we cannot build an artificial system that would experience something similar.

Furthermore, conscious AI would likely need to have the ability for long-term self-reference, that is, awareness of its own existence in time and space, the ability to understand the consequences of its actions, and create autonomous goals. Current systems cannot do any of this. Artificial intelligence has no internal motivations because it has no “self.” There is no center of consciousness, no unified subject – only layers of neural networks calculating the probabilities of the next words.

When could it happen? Expert time estimates

Various scientists and technologists differ significantly in their estimates. All quotes below, however, are still based on pure speculation, because no one today knows exactly what will be technically possible and when. From developments in recent years, however, it’s clear that AI as a field is innovating at an incredible pace. Yet, no one knows how quickly, when, and who should work towards truly fully conscious artificial intelligence and what form it will actually take (i.e., complete consciousness, or will it just be some agent that can be given a goal/specific task it can handle on its own).

It’s therefore not clear who will develop it first – although hot candidates include the USA, China, possibly Israel, and Europe may not be far behind if it manages to jump on the already moving train in time – after all, the latest geopolitical changes due to the chaotic behavior of exotic figures like Elon Musk or Trump/Putin prove that even a functioning world economy can be sunk in just a few months, so the cards may be dealt in all sorts of ways over the years). However, many of these statements converge on one point – it’s not a question of whether it will happen, but when, and estimates range around 5-30 years (i.e., sometime around 2030-2060), and it’s apparent that as time goes on, the estimate itself is more or less shortening as the technology and AI sector advances by leaps and bounds. I definitely recommend reading the analysis “When Will AGI/Singularity Happen?” if you’re more interested in this issue.

• 2019 – Nick Bostrom (philosopher and futurist) updated his estimates in the publication “When Will AGI Be Created?” and stated that there is a “50% chance of achieving human-level intelligence by 2045,” defining this level as the ability to perform most economically relevant tasks better than humans.
• 2020 – Ilya Sutskever (co-founder of OpenAI) stated in an interview for MIT Technology Review that AGI (artificial general intelligence) could emerge “in the next 5-10 years,” emphasizing that it’s about the technological ability to solve problems, not consciousness.
• In 2021, Demis Hassabis (founder of DeepMind) suggested that “full-fledged AGI is possibly still decades away” and that current progress represents just the initial steps.
• 2022 – Sam Altman (CEO of OpenAI) estimated that systems with “human-level intelligence” may appear “in the coming decade,” but cautioned that these would be tools optimized for specific tasks, not necessarily conscious entities. Demis Hassabis (founder of DeepMind) suggested that “full-fledged AGI” is “possibly still decades away” and that current progress represents just the initial steps.
• 2023 – Geoffrey Hinton (pioneer of deep learning) warned that “within 5-20 years,” there is a 50% probability that AI capable of acting as an agent with its own goal may emerge. However, he did not say it would be conscious – just more autonomous.
• 2024 – Ray Kurzweil (Google futurist) reiterated his prediction that by 2029, artificial intelligence will emerge that “will pass the Turing test.” Kurzweil assumes that by 2029, computers will be able to perform most cognitive tasks as well as humans. This includes capabilities such as language comprehension, problem-solving, and learning. This prediction was first mentioned in his 2005 book “The Singularity Is Near” and confirmed in its 2024 update “The Singularity Is Nearer.” Ray Kurzweil, an American futurist and engineer, predicts that by 2045 we will achieve technological singularity – the point when human intelligence merges with artificial intelligence (AI), leading to an exponential increase in intelligence. This process involves integrating nanotechnologies and AI into the human body, allowing people to expand their cognitive abilities, meaning nanobots will be able to communicate with the brain and improve its functions, leading to a significant increase in intelligence and capabilities. What is technological singularity? Technological singularity is a hypothetical point in the future when technological growth becomes so rapid and complex that human intelligence will not be able to keep pace. Kurzweil assumes that in 2045, AI will reach a level where it will be able to improve itself without human intervention, leading to an exponential increase in intelligence and a fundamental transformation of society. Implications for humanity – this prediction has the potential to fundamentally change human existence. People could achieve “digital immortality” through backing up consciousness, eliminating disease and aging, and accessing unlimited knowledge. Kurzweil believes this transformation will bring new opportunities for developing human potential. It is important to note, however, that these predictions are speculative and raise a number of ethical, social, and technological questions. The discussion about technological singularity and its implications continues among experts and the public.

• 2025 – Dario Amodei, CEO of Anthropic, predicts that superintelligent AI, which will surpass human intelligence in most areas, could be developed as early as 2026. This AI could fundamentally change society, similar to the industrial revolution.

What would it mean if AI actually gained consciousness?

Although there is currently no evidence that any machine actually possesses consciousness, the question of its emergence is no longer considered purely hypothetical. A number of technology companies, research teams, and state institutions are actively working on developing systems that could approach consciousness in some form. Development is moving from narrowly specialized models to so-called artificial general intelligence (AGI), which would be capable of independent learning, complex decision-making, and application of knowledge across various fields.

It’s therefore not a question of whether it’s possible, but when, under what conditions, and with what consequences. This trend is fueling a global technological race in which individual states and corporations try to gain an advantage by being the first to develop a fully autonomous and intelligent system. The motivation is not only technological prestige but primarily the expected economic, informational, and military dominance that such a system could secure.

However, truly conscious or highly autonomous AI could pose a significant risk, especially if it acted outside the framework of human instructions or contrary to our values. Threats include not only technological failure but also fundamental ethical dilemmas – for example, in the question of the rights of an artificial entity, its legal status, responsibility for its actions, or the possibility of “turning it off.” Systems capable of independent decision-making without human control could be extremely efficient but also unpredictable.

Special attention should be paid to the potential for misuse of artificial intelligence in the military sphere. Development projects for so-called autonomous weapons systems already exist today, capable of identifying and eliminating targets without human intervention. If these technologies were combined with powerful AI, it would create space for conflicts conducted by machines that could escalate without human decision-making and without moral restraints. Such a scenario would mean a fundamental disruption of international law, security, and ethical norms. There is a risk that in the pursuit of technological superiority, security principles and regulations will be pushed to the sidelines.

To prevent scenarios that we know today primarily from dystopian visions, it is necessary to emphasize the development of so-called safe AI. The key is to focus on research of so-called alignment – aligning the goals and decision-making processes of AI with the values and interests of humanity. Transparency of development, thorough testing, international cooperation, and legal frameworks that clearly define the limits of deploying these technologies are also essential. At the same time, it is important to have a public debate about what boundaries we as a society are willing to accept – even if technology allows for creating something that truly approaches human consciousness.

12. Myth: AI is a threat mainly because of its intelligence

Many concerns about AI focus on scenarios where systems become “too intelligent” and take control. However, real risks often lie elsewhere – in how people deploy, use, and potentially misuse these technologies.

More realistic threats include the automation of disinformation, mass surveillance, manipulation of public opinion, discrimination through biased algorithms, or concentration of power in the hands of those who own the most advanced AI systems. These problems don’t require conscious AI – just a person who uses it for problematic purposes.

13. Myth: AI is energy efficient or environmentally neutral

Many people don’t realize the energy demands of operating advanced artificial intelligence systems. Training large language models consumes an enormous amount of electricity and water (for cooling). For example, training a single large language model can produce a carbon footprint comparable to several years of airplane flights around the world.

Current data centers with AI computations can consume an amount of electricity equivalent to a smaller city. This trend continues with each new, more powerful generation of models. With the growing implementation of AI in various sectors, its environmental impact is also growing, which is in direct conflict with global climate goals.

14. Myth: AI has access to all information

The average user often assumes that AI “knows everything” or has direct access to the internet. In reality, current AI systems are limited by their training data – they cannot “google” or search for current information in real-time (unless they are specially connected to a search engine).

This means that AI may have outdated or incomplete information about current events, new scientific discoveries, or changing circumstances. Some more advanced systems may be integrated with search tools, but independent access to current information is not a standard feature of AI.

15. Myth: AI is a purely digital phenomenon

AI is not just abstract software existing only in the digital world. Its operation has very real material and physical foundations – from rare metals in hardware, through data centers occupying thousands of square meters, to water resources used for cooling servers.

This material dimension has implications that are not only environmental but also geopolitical and economic. States and corporations compete for control over rare resources essential for the development of AI infrastructure, creating new forms of international tension and inequalities.

16. Myth: AI is always “better” than human decision-making

There is a tendency to assume that algorithmic decision-making is inherently more objective, efficient, or “better” than human decision-making. In reality, there are many contexts where human judgment, intuition, and ethical consideration provide better results.

AI systems can be effective in optimizing clearly defined parameters, but often lack the ability to consider the broader context, moral aspects, or non-standard circumstances that humans can intuitively process. Excessive trust in algorithmic decision-making can lead to the dehumanization of processes where human judgment is irreplaceable.

17. Myth: AI development is inevitably progressive and linear

Many discussions about AI assume that the development of this technology will automatically continue toward greater autonomy, complexity, and human similarity. However, the history of technologies shows that development is often non-linear, with detours, stagnation, and backward steps.

Social, economic, and regulatory factors can radically change the trajectory of AI development. It’s possible that the future will include more specialized, limited systems instead of general “superintelligence,” or that the preferred direction will be the development of hybrid systems that combine human and machine intelligence, rather than fully autonomous AI.