10 main myths about AI still believed by millions of people

AI thinks like a human

Many people believe that artificial intelligence thinks like humans. But in reality, AI makes decisions based on algorithms, past data, and predefined logic. Unlike humans, who think creatively and emotionally, AI has no consciousness or self-awareness.

For example, it can write poetry or compose music, but it does so by analyzing patterns in data, not through personal emotions or life experiences.

The apparent "intelligence" of AI is often mistaken for true understanding, but it is not. It is not aware of the meaning of its responses - for example, when translating text, AI relies on pattern recognition and statistics rather than understanding the linguistic context. That's why even systems like Google Translate sometimes make mistakes by misinterpreting idioms or metaphors.

AI will never be able to fully replicate human thinking. It is a tool designed to help people, not to replace them. So it's too early to be afraid of a "machine uprising."

Artificial intelligence will eventually take over the world

A lot of fantasies are associated with the dominance of AI, but in reality, this is mostly a myth. AI works within the framework established by humans. While models such as GPT-4 can function similarly to humans, they do not have autonomy or intent.

In most cases, the fear that AI will take over the Earth and become our evil master is more Hollywood propaganda and fictional stories than the reality of modern technology.

There are two types of AI models: Narrow AI and General AI. By 2025, almost all AI models you use will be narrowly specialized. These models can only perform a few specific tasks or goals.

For example, both ChatGPT and Google Gemini are highly specialized AI models, as they are customized to answer users' queries accurately. General AI is extremely difficult to create, and only a few such models exist today.

Artificial intelligence is always fair

Many people believe that since AI has access to a huge amount of information, it will always make fair decisions. However, this is not always the case. AI can learn from the biases present in the data it is trained on. If the training data contains social prejudices, the AI's conclusions will reflect them.

If an AI system is trained on hiring data from a company that has always favored certain demographics, it may carry over these biases into its recommendations. They can only be eliminated through careful filtering of training data, regular audits, and clear reporting.

Artificial intelligence will replace all professions

Although AI will automate certain tasks, it will not replace entire professions. Instead, AI will change the very nature of work. Professions that require problem-solving, emotional intelligence, and creativity, such as teaching, healthcare, and management, will not necessarily become automated.

During the Industrial Revolution, people thought that machines would completely eliminate the need for human labor. In fact, the opposite happened - there was an increase in industry, job creation, and employment. Thus, AI will only complement human capabilities, not replace them.

Automating workplaces with AI will simply empower humanity to perform more complex and new projects that AI will never be able to accomplish.

Artificial intelligence is a recent invention

Most people probably hadn't heard of AI until 2022 or 2023, when ChatGPT became widely used and the AI boom began. However, many people don't know that the term "artificial intelligence" was first used in the mid-twentieth century, in the 1950s.

A group of influential scientists and researchers in the field of computing at the time worked on the concept of AI for more than 50 years before it became a household name. Among these pioneers were Alan Turing, John McAfee, Marvin Minsky, Allen Newell, and Herbert A. Simon.

Alan Turing, the man considered by many to be the father of artificial intelligence (photo: Wikimedia)

Artificial intelligence perfectly understands context

This misconception that AI fully understands context is very rarely true. The program lacks nuance and context, especially when it comes to language. For example, a chatbot may misinterpret sarcasm or fail to understand rhetorical questions.

Models such as GPT-4 and Google Gemini are quite advanced, but they don't understand meaning the way humans do; they don't have experience with real human speech with its attributes such as sarcasm, irony, accents, etc.

Context analysis is a limitation for AI systems because it is based on statistical patterns rather than true understanding.

While AI can detect correlations and predict the most likely events based on data, it lacks the cultural, emotional, and experiential foundation on which human perception of context is built. This is evident when AI fails to adapt to unusual situations or makes inappropriate recommendations.

Understanding the limitations of AI helps to set realistic expectations for its use in communication and decision-making. Developers should continue to improve systems to better handle extreme cases and improve their ability to understand context.

Artificial intelligence is just for tech companies

AI can be used in almost any industry: from agriculture and healthcare to retail and education. For example, farmers use AI to monitor plant health, and educators use it to create educational materials.

The versatility of AI lies in the fact that it effectively analyzes data for patterns. Thanks to this feature, AI can be used in a wide variety of areas and scenarios.

AI is not limited to tech giants. Because it helps solve problems and makes processes more efficient, its value spans hundreds of different industries. Small businesses and startups can also use AI to stay ahead of their competitors.

Artificial intelligence is always getting smarter over time

AI systems don't improve on their own; at least, it rarely happens. They need constant training using new data and improved algorithms to improve efficiency.

Without human intervention, AI remains static: its data becomes erroneous, outdated, and inaccurate. Moreover, AI algorithms and code become outdated over time, and more advanced technologies come to the fore.

The recommendation algorithm in a streaming service will lose its relevance if it is not updated based on user preferences or new content trends. It is people who provide feedback that is incorporated into the training data of AI models and adapt them to changing conditions.

Human expertise remains crucial in building and maintaining AI systems, which goes against the concept of self-improving and autonomous machines. This is also one of the main examples of how humans and AI work together.

A chatbot helps people learn and make life easier, and people help build and maintain these systems so that they continue to fulfill their role.

Without humans constantly maintaining the AI model, updating its code, and expanding its dataset, AI starts to become outdated and eventually loses its relevance entirely (photo: Pexels)

Artificial intelligence is never wrong

AI is far from perfect. It is prone to errors, especially if the input data is incomplete or ambiguous. For example, AI diagnostics can misinterpret symptoms that require human intervention.

Most AI errors occur due to limitations in training data or hypothetical situations. Knowing these weaknesses is critical for the responsible use of AI. Trust in artificial intelligence should always be combined with awareness of its shortcomings and problems.

Everyone accepts artificial intelligence

Attitudes toward AI range from excitement about its potential to skepticism and fear. The topic touches on everything from ethical dilemmas in decision-making to job losses and privacy concerns.

Such contradictory reactions are indicative of a broader societal debate about the role of technology in shaping our future. Transparency, education, and ethical practices are essential to building trust and combating misunderstandings. With an open dialog, all stakeholders will be able to cope with the challenges and opportunities AI brings. Simply put, AI is not accepted everywhere.

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