Finding a provably correct or optimal solution is intractable for many important problems.[15] Soft
computing is a set of techniques, including genetic algorithms, fuzzy logic and neural networks, that are
tolerant of imprecision, uncertainty, partial truth and approximation. Soft computing was introduced in
the late 1980s and most successful AI programs in the 21st century are examples of soft computing with
neural networks.
AI researchers are divided as to whether to pursue the goals of artificial general intelligence and
superintelligence directly or to solve as many specific problems as possible (narrow AI) in hopes these
solutions will lead indirectly to the field's long-term goals.[378][379] General intelligence is difficult to
define and difficult to measure, and modern AI has had more verifiable successes by focusing on specific
problems with specific solutions. The sub-field of artificial general intelligence studies this area
exclusively.
The philosophy of mind does not know whether a machine can have a mind, consciousness and mental
states, in the same sense that human beings do. This issue considers the internal experiences of the
machine, rather than its external behavior. Mainstream AI research considers this issue irrelevant because
it does not affect the goals of the field: to build machines that can solve problems using intelligence.
Russell and Norvig add that "[t]he additional project of making a machine conscious in exactly the way
humans are is not one that we are equipped to take on."[380] However, the question has become central to
the philosophy of mind. It is also typically the central question at issue in artificial intelligence in fiction.
David Chalmers identified two problems in understanding the mind, which he named the "hard" and
"easy" problems of consciousness.[381] The easy problem is understanding how the brain processes
signals, makes plans and controls behavior. The hard problem is explaining how this feels or why it
should feel like anything at all, assuming we are right in thinking that it truly does feel like something
(Dennett's consciousness illusionism says this is an illusion). While human information processing is easy
to explain, human subjective experience is difficult to explain. For example, it is easy to imagine a color-
blind person who has learned to identify which objects in their field of view are red, but it is not clear
what would be required for the person to know what red looks like.[382]
Computationalism is the position in the philosophy of mind that the human mind is an information
processing system and that thinking is a form of computing. Computationalism argues that the
relationship between mind and body is similar or identical to the relationship between software and
hardware and thus may be a solution to the mind–body problem. This philosophical position was inspired
by the work of AI researchers and cognitive scientists in the 1960s and was originally proposed by
philosophers Jerry Fodor and Hilary Putnam.[383]
Philosopher John Searle characterized this position as "strong AI": "The appropriately programmed
computer with the right inputs and outputs would thereby have a mind in exactly the same sense human
beings have minds."[ac] Searle challenges this claim with his Chinese room argument, which attempts to
Narrow vs. general AI
Machine consciousness, sentience, and mind
Consciousness
Computationalism and functionalism