what is AI?
Artificial intelligence is a subfield of computer science that studies the thought
processes of humans and recreates the effects of those processes through
information systems. We define artificial intelligence (AI) as the theory and
development of information systems able to perform tasks that normally require
human intelligence. That is, we define AI in terms of the tasks that humans
perform, rather than how humans think.
This definition raises the question, "What is intelligent behaviour?" The
following capabilities are considered to be signs of intelligence: learning or
understanding from experience, making sense of ambiguous or contradictory
messages, and responding quickly and successfully to new situations.
The ultimate goal of AI is to build machines that mimic human intelligence. A
widely used test to determine whether a computer exhibits intelligent behaviour
was designed by Alan Turing, a British AI pioneer. The Turing test proposes a
scenario in which a man and a computer both pretend to be women or men, and
a human interviewer has to identify which is the real human. Based on this
standard, the intelligent systems exemplified in commercial AI products are far
from exhibiting any significant intelligence
what is the difference between AI and human intelligence?
We can better understand the potential value of AI by contrasting it with natural
(human) intelligence. AI has several important commercial advantages over
natural intelligence, but it also displays some limitations, as outlined in Table
TG 4.1.
what is the difference between strong and weak AI?
,It is important to distinguish between strong artificial intelligence and weak
artificial intelligence. Strong AI is hypothetical artificial intelligence that
matches or exceeds human intelligence—the intelligence of a machine that
could successfully perform any intellectual task that a human being can. Strong
AI, therefore, could be considered to have consciousness or sentience. Weak AI
(also called narrow AI) performs a useful and specific function that once
required human intelligence to perform, and does so at human levels or better
(for example, character recognition, speech recognition, machine vision,
robotics, data mining, medical informatics, automated investing, and many
other functions).
Today, systems that are labelled "artificial intelligence" are weak AI. Weak AI
is already powerful enough to make a dramatic difference in human life. Weak
AI applications enhance human endeavours by complementing what people can
do. For example, when you call your bank and talk to an automated voice, you
are probably talking to a weak AI program. Researchers at universities and
companies around the world are building weak AI applications that are rapidly
becoming more capable.
Consider chess, which weak AI systems now play better than any human. In
1997, IBM's Deep Blue system beat the world chess champion (Garry
Kasparov) for the first time. Since that time, chess-playing systems have
become significantly more powerful. However, the way these systems play
chess has not changed. They search through all possible future moves to find the
best move to make next.
Today, however, the best players in the world are not machines, but what Garry
Kasparov, a grandmaster, calls "centaurs." Centaurs are teams of humans and
chess-playing programs. In freestyle chess matches, competitors can play
unassisted as humans, unassisted as chess-playing programs, or as centaurs. In
the Freestyle Battle of 2014, pure chess-playing AI software won 42 games,
while centaurs won 53 games.
In an interview in May 2018, Kasparov compared chess-playing entities (i.e.,
humans and software) using Elo ratings, which are scores that reflect the skill of
chess players.
Kasparov stated that his own highest Elo rating was 2,851.
Magnus Carlsen, the world human chess champion in 2018, had an Elo rating of
, 2,882.
IBM's Deep Blue's Elo rating was above 2,700.
Alphabet's (parent company of Google) DeepMind's AlphaZero had an Elo
score of 3,600.
Interestingly, the advent of AI did not diminish the performance of purely
human chess players—quite the opposite. Cheap, highly functional chess
programs have inspired more people than ever to play chess and the players
have become better than ever. In fact, today there are more than twice as many
grandmasters as there were when Deep Blue beat Kasparov.
Similar to centaurs, physicians who are supported by AI will have an enhanced
ability to spot cancer in medical images; speech recognition algorithms running
on smartphones will bring the Internet to many millions of illiterate people in
developing countries; digital assistants will suggest promising hypotheses for
academic research; and image classification algorithms will allow wearable
computers to layer useful digital information onto people's views of the real,
physical world.
Weak AI does present challenges. For example, consider the power that AI
brings to national security agencies, in both autocracies and democracies. The
capacity to monitor billions of conversations and to pick out every citizen from
the crowd by their voice or face poses serious threats to liberty. Also, many
individuals could potentially lose their jobs as a result of advances in AI.
Several technological advancements have led to advancements in artificial
intelligence. We take a brief look at each of them here.
Advancements in chip technology: AI systems employ graphics processing
units (called GPU chips). These chips were developed to meet the visual and
parallel processing demands of video games. In fact, GPU chips facilitate
parallel processing in neural networks, which are the primary information
architecture of AI software. (We discuss neural networks later in this
Technology Guide.)
Big Data: As we discussed in Chapter 5, Big Data consists of diverse, high-
volume, high-velocity information assets that require new types of processing to
enable enhanced decision making, insight discovery, and process optimization.
Big Data is now being used to train deep learning software. (We discuss deep
learning later in this Technology Guide.)
The Internet and cloud computing: The Internet (discussed in Chapter 6) and
Artificial intelligence is a subfield of computer science that studies the thought
processes of humans and recreates the effects of those processes through
information systems. We define artificial intelligence (AI) as the theory and
development of information systems able to perform tasks that normally require
human intelligence. That is, we define AI in terms of the tasks that humans
perform, rather than how humans think.
This definition raises the question, "What is intelligent behaviour?" The
following capabilities are considered to be signs of intelligence: learning or
understanding from experience, making sense of ambiguous or contradictory
messages, and responding quickly and successfully to new situations.
The ultimate goal of AI is to build machines that mimic human intelligence. A
widely used test to determine whether a computer exhibits intelligent behaviour
was designed by Alan Turing, a British AI pioneer. The Turing test proposes a
scenario in which a man and a computer both pretend to be women or men, and
a human interviewer has to identify which is the real human. Based on this
standard, the intelligent systems exemplified in commercial AI products are far
from exhibiting any significant intelligence
what is the difference between AI and human intelligence?
We can better understand the potential value of AI by contrasting it with natural
(human) intelligence. AI has several important commercial advantages over
natural intelligence, but it also displays some limitations, as outlined in Table
TG 4.1.
what is the difference between strong and weak AI?
,It is important to distinguish between strong artificial intelligence and weak
artificial intelligence. Strong AI is hypothetical artificial intelligence that
matches or exceeds human intelligence—the intelligence of a machine that
could successfully perform any intellectual task that a human being can. Strong
AI, therefore, could be considered to have consciousness or sentience. Weak AI
(also called narrow AI) performs a useful and specific function that once
required human intelligence to perform, and does so at human levels or better
(for example, character recognition, speech recognition, machine vision,
robotics, data mining, medical informatics, automated investing, and many
other functions).
Today, systems that are labelled "artificial intelligence" are weak AI. Weak AI
is already powerful enough to make a dramatic difference in human life. Weak
AI applications enhance human endeavours by complementing what people can
do. For example, when you call your bank and talk to an automated voice, you
are probably talking to a weak AI program. Researchers at universities and
companies around the world are building weak AI applications that are rapidly
becoming more capable.
Consider chess, which weak AI systems now play better than any human. In
1997, IBM's Deep Blue system beat the world chess champion (Garry
Kasparov) for the first time. Since that time, chess-playing systems have
become significantly more powerful. However, the way these systems play
chess has not changed. They search through all possible future moves to find the
best move to make next.
Today, however, the best players in the world are not machines, but what Garry
Kasparov, a grandmaster, calls "centaurs." Centaurs are teams of humans and
chess-playing programs. In freestyle chess matches, competitors can play
unassisted as humans, unassisted as chess-playing programs, or as centaurs. In
the Freestyle Battle of 2014, pure chess-playing AI software won 42 games,
while centaurs won 53 games.
In an interview in May 2018, Kasparov compared chess-playing entities (i.e.,
humans and software) using Elo ratings, which are scores that reflect the skill of
chess players.
Kasparov stated that his own highest Elo rating was 2,851.
Magnus Carlsen, the world human chess champion in 2018, had an Elo rating of
, 2,882.
IBM's Deep Blue's Elo rating was above 2,700.
Alphabet's (parent company of Google) DeepMind's AlphaZero had an Elo
score of 3,600.
Interestingly, the advent of AI did not diminish the performance of purely
human chess players—quite the opposite. Cheap, highly functional chess
programs have inspired more people than ever to play chess and the players
have become better than ever. In fact, today there are more than twice as many
grandmasters as there were when Deep Blue beat Kasparov.
Similar to centaurs, physicians who are supported by AI will have an enhanced
ability to spot cancer in medical images; speech recognition algorithms running
on smartphones will bring the Internet to many millions of illiterate people in
developing countries; digital assistants will suggest promising hypotheses for
academic research; and image classification algorithms will allow wearable
computers to layer useful digital information onto people's views of the real,
physical world.
Weak AI does present challenges. For example, consider the power that AI
brings to national security agencies, in both autocracies and democracies. The
capacity to monitor billions of conversations and to pick out every citizen from
the crowd by their voice or face poses serious threats to liberty. Also, many
individuals could potentially lose their jobs as a result of advances in AI.
Several technological advancements have led to advancements in artificial
intelligence. We take a brief look at each of them here.
Advancements in chip technology: AI systems employ graphics processing
units (called GPU chips). These chips were developed to meet the visual and
parallel processing demands of video games. In fact, GPU chips facilitate
parallel processing in neural networks, which are the primary information
architecture of AI software. (We discuss neural networks later in this
Technology Guide.)
Big Data: As we discussed in Chapter 5, Big Data consists of diverse, high-
volume, high-velocity information assets that require new types of processing to
enable enhanced decision making, insight discovery, and process optimization.
Big Data is now being used to train deep learning software. (We discuss deep
learning later in this Technology Guide.)
The Internet and cloud computing: The Internet (discussed in Chapter 6) and
