Introduction to Artificial Intelligence

The term ‘Homo Sapiens’ itself is a pretty good indication that human beings are self-centredbecause it means ‘Wise Man’ in Latin.  It’s interesting that a mass of matter that has somehow come to understand, perceive, predict, manipulate the world around it and call itself “wise”.    The question now is when will a mass of Artificial matter – electronics and software we call a computer, robot and/or Artificial Intelligence (AI) become truly “intelligent” and call itself “wise”.  That is the gripping question about AI in our rapidly advancing technological world.

One of the leading futurist thinkers around AI, Ray Kurzweil (his blog), defined Artificial Intelligence as the following back in 1990:

Artificial Intelligence is the art of creating machines that perform functions that require intelligence when performed by people.

Kurzweil has also predicted what he calls the Singularity in AI where AI systems will be able to self-develop and improve without human interaction and lead to developments we can’t fully anticipate or predict and perhaps can’t control.

AI is a field of studyAI is a field of study that tries to emulate intelligent behaviour in terms of computational processes. It is the subfield of computer science concerned with the concepts and methods of symbolic inference by computer and symbolic knowledge representation for use in making inference. Artificial intelligence can be seen as an attempt to model aspects of human thought on computers. It is also sometimes defined as trying to solve by computer any problem that a human can solve faster, better or more accurately.

There are two general types of AI – weak AI or Narrow AI and strong AI or Artificial General Intelligence.  Narrow AI is typically an algorithm that is focused on a very specific task.  Perhaps its analyzing a set of data to determine specific facts or results.  Whereas Artificial General Intelligence is more focused on multiple tasks and more human like behavior.

Artificial intelligence is arguably one of the newest and still rapidly emerging fields of science and engineering. It really came into focus after World War II and developed gradually until the name was coined in 1956.

It’s become so popular that a recent survey of scientist’s place AI along with Molecular Biology as the “field I would most like to be in”.  It encompasses a huge variety of subfields, from the general (learning and perception) to the specific, such as probing mathematical theorems, writing poetry, playing chess, driving a car on a busy street, and even in medicine for diagnosing diseases. It is also regarded as a universal field of study because it is relevant to almost any intellectual endeavor.  The field of AI study focuses on four primary goals:

  1. Systems that act like humans in that they perform activities that require intelligence when enacted
  2. Systems that think like humans, automation of activities that we associate with human thinking e.g. decision making
  3. Systems that think rationally, computations that make it possible to perceive, reason in a rational way
  4. Systems that act rationally, taking steps to achieve the intended goals of the system

A key area of focus in AI is its use in robotics. The thought of the two combined might bring up a vision a robot fully functioning with human like intelligence.  But, it can be a little more mundane than that and be as simple as an AI powered robot vacuum.  This particular AI implementation has a number of focus areas including:

  • Interacting with humans and other robots
  • Perceiving, understanding and modelling open and constantly changing environments
  • Deliberate actions, planning, acting, monitoring and goal reasoning
  • Learning models that lead an AI empowered robot to adapt and grow

The basic concept behind Artificial Intelligence is that scientists are looking for a way to create robots and machines that acts and think like humans. In 1950, Alan Turing proposed a test called the Turing Test to provide a satisfactory operational definition of intelligence. The test is normally done by a human interrogator and the “AI is said to pass if the interrogator can’t tell whether the responses come from a person or from a computer.

The Turing test of course would deliberately avoid direct physical interaction between the interrogator and the computer put to the test to avoid any clues based on appearance or awareness of surroundings.  The messages would be passed between the human and machine via some type of simple text communication.  Some have proposed that with modern video technology the test could now add a visual component to test perceptual abilities since the visual sense is a key component of our human intelligence.  The test can be taken even further to include physical capabilities such as movement and manipulation of surroundings.  But the core of the original test conceived of by Turning was to basic intelligence regardless of physical surroundings.  In other words, can you intelligently “talk” with the AI and not know if its human or machine.

A key part of developing the field of AI is also studying the field of natural intelligence.  This is the opposite of Artificial intelligence in that it is the study intelligence in biological systems. Neuroscience is the study ofnatural Intelligence and how human and animal brains function.  Natural Intelligence is the foundation on which Artificial Intelligence is built and if we are going to say a given program can “think” like a human, then it is important to determine how we humans think. We need to get inside the actual working of the human mind. There are three primary ways to do this:

  1. Introspection – Studying and analyzing our own thoughts
  2. Psychological Experiments – Observing a person in action
  3. Brain Imaging – Observing the brain’sphysical actions

The study of these areas has helped to move forward the development of AI by learning how its already done by humans.  As we learn more about how we humans do it we can then model the same behavior in the AI system.

The Handbook of Artificial Intelligence by Avron Barr and Edward A. Feigenbaum divides up the study and development of AI into seven primary areas:

Knowledge Representation: Taking information and making it into a form that is can be utilized to solve complex tasks.

Understanding Natural Language:Understanding natural language is not just identifying and recognising the words but determining the implied meaning semantically.

Learning: Assimilating new information and storing it for future use.

Planning and Problem Solving: Real intelligence involves the ability to have a plan ready to accomplish a goal and solve problems with the plan.

Inference: Coming up with an answer based on limited or insufficient information.

Search: In AI, search means efficiently examining a knowledge representation of a problem to find an answer.

Vision: The most valuable and important sense for humans to assess the world around us.

Many of us interact with AIs each day, whether it’s Siri, or in finance to formulate financial strategies and give advice, in engineering to validate designs, offer suggestions in the creation of new products, in manufacturing when assembling, inspecting and maintaining facilities, in Hospitals for monitoring, diagnosing and prescribing drug and even in household for advice on cooking, shopping etc.AI in some shape or form is ofteninteracting with us and we don’t even realize it.  Because of this ongoing development, there are also many concerns about the fast progress and possible impacts of AI on humanity and our civilization.  One of the most vocal technology luminaries to speak out on AI is Elon Musk.

“The pace of progress in artificial intelligence (I’m not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast—it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five-year timeframe. 10 years at most.” —Elon Musk wrote in a comment on

The future of AI is one that seems to on the one hand hold a lot of promise for improving the lives of humans.  On the other hand, it is also fraught with fears and concern that the technology will outpace the ability of humans to control it.  It also comes loaded with a lot of ethical issues to consider on how to properly use AI and manage it.  There is no doubt in the coming years our lives will all be impacted by AI and it will be interesting to see the impact.