How AI learns and why humans learn differently?

Many people refer to artificial intelligence as a learning tool. But the way machines process information is fundamentally different from how humans learn.

Although AI uses data, algorithms and pattern recognition to learn, the learning process for humans is influenced by our experiences, feelings and meaning. Making the distinction between machine and human learning will help improve understanding of what artificial intelligence can do and where it falls short.

AI Training - How Does AI Learn (Data, Patterns, Probabilities)

Machine Learning is how AI learns. An AI system is trained using a large number of data sets to identify patterns in those data sets via algorithms or mathematical functions. Rather than forming a conceptual understanding of the subject (like how a human does), AI uses a probabilistic approach to determine which outcome is the most probable based on previously seen examples. The more data an AI system has, the better it will be able to predict an outcome from a given situation. AI systems rely upon the amount and quality of data and the presence of bias in the data in their ability to learn.

How humans learn - Through emotions, experiences and ideas

Humans Learn through both emotionally and cognitively stimulated experiences. Humans learn through curiosity (doing things based on their questions), trial and error learning (testing things to see what works), thoughtful consideration of their experiences (thinking back on what was learned) and also through the connection of related concepts via emotional bonds. The many different things that are learned through these different experiences are influenced in various ways by many different factors. The way we experience and understand the things we learn is based on the relationship between our culture (what we grow up learning from our surroundings), our memories (our understanding of events) and our socialization (the way we interact with other people). Humans do not just store information but also rank the information based on individual perception.

The difference between the way both AI and humans learn

Recognizing the difference in the capabilities of humans and AI systems for learning and processing information will reduce the risk of having unreasonably high expectations of the performance of an AI for specific tasks. While AIs have enabled humans to become much more efficient in processing data through their ability to analyze vast quantities of data simultaneously, AIs are incapable of providing the same standard of human reasoning and the same level of ethical consideration in their decision-making. Due to this, it is essential for the education system to differentiate between the intelligence of humans and AIs. They should also place greater emphasis on promoting the development of integrated thought, interpretation, and reflection; the qualities that AIs simply cannot exhibit.

Conclusion

Humans and AI both learn through different processes. However, their methods of acquiring knowledge are completely different. Humans gain their experience and understanding through meaningful experiences, while AI collects information based on pattern recognition of data. Understanding these differences will lead us as a society to appropriately apply AI towards improving human learning, rather than ascribing to computers a greater understanding of how humans learn or think.