Machine 'learning' has issues, but AI here to stay

The future seems to be here when it comes to artificial intelligence. Although many think artificial intelligence, or AI, is still the stuff of books and film, it's actually used in a number of products and apps that most of us use multiple times a day. Dr. Miguel Garcia-Ruiz, a professor of computer science at Algoma University said, "We use practical and effective AI applications every day and we often don't notice it, from checking the weather forecast on a cellphone to washing clothes in a washing machine. "Currently, social networks such as Facebook use AI techniques for finding new contacts and people online, not to mention showing ads according to our preferences and Internet usage." A clear definition of just what is meant by artificial intelligence can help to clarify how it can be used for so many different applications. "It can be defined as a branch of computer science that deals with the simulation of human behaviour, where personal computers and other digital devices such as cellphones, digital toys, etc., carry out tasks that can be considered'smart,'" said Garcia-Ruiz. "AI may include perception, reasoning, planning, conducting complex tasks, learning, etc." Practical application can be dated to the 1950s when some computer programs were created to simulate intelligence, "including a computer program for playing checkers that was'intelligent' enough to challenge human players," said Garcia-Ruiz. But AI has come a long way since then. "AI is not that different from how humans learn, at least conceptually," said Garcia-Ruiz. "Computers capable of doing AI can learn like humans by using cameras, motion and light sensors and other types of sensors (the equivalent to our human senses) for acquiring information from the environment, memorize information, solve problems, learn from mistakes and from experience, compare already stored knowledge with new knowledge, etc." The computer then applies what it has learned in essentially the same way a human does -- "by comparing stored knowledge with new acquired knowledge, analyzing already-stored patterns," said Garcia-Ruiz. "One example of this is the face recognition feature found in cellphones.