The Differences Between Artificial Intelligence & Human Intelligence

The question of how powerful artificial intelligence (AI) will become is being asked across society as AI-driven assistants, self-learning systems, and robotics become integral to everyday life. The rapid integration of AI into our daily lives has given us an idea of its potential and how similar it is to human intelligence. 

While the technology is not yet at our level, AI experts believe it will soon equal our intelligence. AI expert Ray Kurzweil, the head of Google Engineering, believes that by 2029, computers will have human-level intelligence, and by 2045, AI will have achieved the “Singularity,” the point when “we will multiply our effective intelligence a billion-fold by merging with the intelligence we have created.” In some cases, it feels that we are much closer to AI being able to match human intelligence through the capabilities of large language models (LLMs) such as ChatGPT, which can already create content close to what a human can produce. 

While there is no question that AI is getting similar human intelligence, many differences still set us apart. Below, we will look at the similarities and then three reasons why AI is different from human intelligence.

How Artificial Intelligence and Human Intelligence Are Similar 

How humans and AI process and react to data and information are surprisingly similar. MongoDB’s extensive guide to AI details how the human brain and artificial intelligence both derive patterns based on surroundings and situations. The human brain receives input from what we observe, read, and hear and uses this information to form patterns, save memories, and comprehend new situations based on past experiences. AI works in a very similar way. It receives data and uses the information it has been given to find patterns, self-learn, and learn and comprehend new situations. When an AI is fed with enough data, it is capable of deriving certain outcomes based on the data patterns through algorithms. 

How Artificial Intelligence and Human Intelligence Are Different 

Contextual Understanding

AI relies on statistical correlations and patterns within data, not on understanding the meaning and context behind the data. This means that AI relies on the data being good in order to make the correct decision. It can’t pick up on ambiguity and the nuances of the data or use common sense to make a good judgment on the information given. For example, if a human gives an answer that is obviously sarcastic, AI would likely take the answer as a literal interpretation. It is this literal approach that makes problem-solving a challenge for AI unless it has been trained on a specific dataset to deal with that challenge.

Creativity 

While there is a very real danger that AI could replace creative jobs due to being able to create content with very little human input, it doesn’t have the same creative mindset as a human. A detailed Medium post on AI and human creativity explains how AI relies on human prompts and pre-existing data, which limits its ability to innovate beyond existing patterns. They describe human creativity as bringing new ideas to life, which requires human experience, emotion, and intuition. The post goes on to say that “True creativity involves not only recognizing patterns but also understanding and transcending those patterns,” which artificial intelligence can’t currently replicate. What AI can do better is produce a much larger quantity of ideas than a human in a much shorter time. 

Social and Emotional Intelligence

AI specialist Stewart Townsend on LinkedIn notes how our emotional intelligence and empathy are key for dealing with complex social situations. A big difference between AI and human intelligence is the ability to pick up and comprehend nuanced interactions. This is because AI is not designed to have emotions or to have empathy. AI is designed to give an answer based on data, not personal experience, which means that it won’t question the data unless programmed to do so. This makes it open to misinterpretations that human intelligence wouldn’t make based on experience. If an AI is trained on biased data, it will reflect those biases without question because it doesn’t have the social or emotional intelligence of a human. 

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