While ANNs and humans both have the ability to learn, the way they learn and represent knowledge is quite different. ANNs are designed to identify patterns in data, while humans can form complex mental models and understand relationships between concepts.

1. ANNs learn based on input data, while humans learn based on experiences, observations, and interactions with the environment.

2. ANNs represent features as mathematical equations, while humans represent concepts through a combination of mental models, language, and cultural norms.

3. ANNs receive feedback in the form of a loss function that indicates how well the model is performing, while humans receive feedback from social, emotional, and physical cues, which can be more complex and nuanced.

4. ANNs do not have an understanding of the concepts they are learning. They only identify patterns in the data, while humans can form mental models of concepts and understand the relationships between different concepts.

https://www.researchgate.net/publication/361603624

I believe that a person does not think with the help of the brain. The brain is nothing more than an intelligent controller or interface between a person's physical body and his Soul. An artificial neural network can be similar to a person in the aspect you are asking about only if an interface is created between the artificial neural network and the Soul.

About Saif ul Islam answer:

"1. ANNs learn based on input data, while humans learn based on experiences, observations, and interactions with the environment."

How about reinforcement learning in which the agent can interact with environment and collect new data in its own. Can this be said to be some kind of experience?

"2. ANNs represent features as mathematical equations, while humans represent concepts through a combination of mental models, language, and cultural norms."

I think you are comparing ANNs and human brain in different levels. Yes, at the low level ANN's use math. But cannot this be said for human brain as well at neuron level, There are additions of electrical signals, thresholds, in a way activation functions, etc, even if their mathematics are quite different. And at the higher level an artificial agent can have models, languistic operations and even cultural norms (not in the emotional sense.)

3. ANNs receive feedback in the form of a loss function that indicates how well the model is performing, while humans receive feedback from social, emotional, and physical cues, which can be more complex and nuanced.

I agree. But cannot loss function or rewards be equvalent to human values in a functionalist sense? I do not claim that an AI system thinks in the same way with humans, but second question: Is it possible for AI to think in a different way than human does?

4. ANNs do not have an understanding of the concepts they are learning. They only identify patterns in the data, while humans can form mental models of concepts and understand the relationships between different concepts.

And hardest point in my opinion. This goes to the conceptual analysis what is understanding. How do we deicde that we do not merely utter but understandingly express a statement. John Searle believes the key here is "intentionality" or "directedness." I believe he is right but the core is about the relationships between different concepts/features. If one simply says that E=mc2 we are not sure if he understands the concept but if she also knows E refers to energy and knows relationships between energy and enthrophy and also aware what mass is and knows that mass of an object is somehow connected with how hard it is to hold this object and, so on and so on.... If she have right kind of relationships between different concepts then we say that she does understand what she utters. Maybe such a concept is applicable to AI and to illustrate one can say GPT-3 or GPTChat has a level and type of understanding in that sense.

The keyword here is "learn". Humans have the ability to learn, adapt to changes, and create things. ANNs do NOT learn, they are just conditioned to execute a very specific task. ANNs do NOT adapt, they do NOT recognize changes in the pattern of input data. ANNs do NOT create anything, they just follow the task they work "trained" (not learned) to perform.