Artificial Intelligence (Al) — a higher discipline!
The human mind is a wonder. For millennia, humans have reflected upon the world. We looked at the sun, the moon, the stars in wonder. We observed nature as the days grew and shrunk, changing seasons. We watched life around us — plants and trees and various animals. We always struggled for food and the desire to avoid becoming food.
We, the Homo sapiens, have learned to exploit this ability to reflect upon the world to make life better for ourselves. After the extinction of the dinosaurs, when mammals began flourishing, we were probably just one amongst the many species foraging for food and fleeing the predators.
Evolution gave us bigger brains, and we started changing the survival rules amongst the different species. We learned to form societies and developed language to communicate; we learned to protect and domesticate flora and fauna helpful for us; we learned to make and use tools.
As we became technologically more advanced, individual lifestyles diversified enormously. Though we are all born the same, we channelize our activity and occupations into many directions as we grow and learn.
The more technologically advanced we have become, the more specialized our professions have become. Technological advancement, combined with an organized society, has created spaces where sections of society can devote their energies towards things beyond our necessities. We have developed music, literature, painting, sculpture, theatre, and many other art forms to cater to our minds.
Research in science and society pushes the frontier of our understanding further and further. Technological development has sped up with this understanding. We have continuously asked questions about our existence and our minds. On this quest for understanding our minds, philosophers are now collaborating with mathematicians, and psychologists, and economists, and cognitive scientists, and most recently, computer scientists. We want to understand minds, brains, and intelligence and create minds, brains, and intelligence. This quest goes broadly under the name of artificial intelligence.
Trying to define “intelligence” is hazardous, but we can broadly consider it to solve problems. There are two approaches to solve — the first is to solve problems using first principles and logic. The second is to harness knowledge gleaned from experience (data) or other agents.
There are two approaches for AI — a cognitive and an engineering approach. The cognitive approach seeks to understand how intelligent behavior arises. In the engineering approach, the goal is to construct smart machines. Al provides a computational platform for these ideas. In both, the ideas manifest themselves as computer programs. These programs draw ideas from many disciplines — computer science, philosophy, psychology, economics, mathematics, logic, and operations research.
We often refer to an autonomous program that senses its environment and acts independently in a goal-directed manner as an agent. The agent chooses various actions subjected to the constraints to reach the desired state that satisfies the agent’s goals. This approach is the first-principles approach where an agent solves a problem by reasoning about actions, exploring combinations, and choosing the ones that lead to the goal. Reinforcement learning extensively uses these approaches. However, there is a danger of the combinatorial explosion that the agent has to contend with. We then refine and change the search-based policy to include heuristic knowledge, and then we move towards ways to deploy more explicit forms of domain-specific knowledge. These will consist of logic and reasoning, memory structures and the exploitation of experience, deeper knowledge in models and ontology, and the relation between language and knowledge.
Humans use language to communicate and represent knowledge, for example, in an article or a blog. There are various aspects of language, including text processing (which gained prominence with online information). For example, in a chatbot, a computer, to interact meaningfully, it will need to access the meaning of what is said. The specific formalism used is not the important thing. We express sentences in a language used to model the concepts in the underlying domain.
AI draws upon the strong mathematical and philosophical base of logical reasoning. It looks at ways to structure knowledge to connect.