Artificial intelligence applications have been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore." "Many thousands of AI applications are deeply embedded in the infrastructure of every industry." In the late 1990s and early 21st century, AI technology became widely used as elements of larger systems, but the field is rarely credited for these successes.
To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Such tests have been termed subject matter expert Turing tests. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results.
Performance evaluation
In his famous Turing test, Alan Turing picked language, the defining feature of human beings, for its basis. But there are many other useful abilities that can be described as showing some form of intelligence. This gives better insight into the comparative success of artificial intelligence in different areas.
In what has been called the Feigenbaum test, the inventor of expert systems argued for subject specific expert tests. A paper by Jim Gray of Microsoft in 2003 suggested extending the Turing test to speech understanding, speaking and recognizing objects and behavior.
Broad classes of outcome for an AI test may be given as:
- optimal: it is not possible to perform better
- super-human: performs better than all humans
- high-human: performs better than most humans
- par-human: performs similarly to most humans
- sub-human: performs worse than most humans
Optimal
- Tic-Tac-Toe
- Connect Four
- Checkers
- Rubik's Cube
- Heads-up limit hold'em poker: statistically optimal in the sense that "a human lifetime of play is not sufficient to establish with statistical significance that the strategy is not an exact solution".
Super-human
- Chess: top human can compete only with handicap in their favor
- Go: beat a top human 4â€"1 in a five-game match in 2016
- Jigsaw puzzles:
- Reversi:
- Scrabble:
High-human
- Bridge: world class
- Backgammon: probably world class
- Arimaa: "Beat 3 selected players...Currently the best Arimaa players are humans."
- Quiz show: question answering although the machine did not use speech recognition
- Texas hold 'em;
Par-human
- Optical character recognition for ISO 1073-1:1976 and similar special characters.
- Classification of images
- Crosswords: Solves 80% of New York Times clues.
- Handwriting recognition
Sub-human
- Optical character recognition for printed text (nearing par-human for Latin-script typewritten text)
- Object recognition
- Translation
- Driving a car: "Between September 2014 and November 2015, Google’s autonomous vehicles in California experienced 272 failures and would have crashed at least 13 times if their human test drivers had not intervened."
- Speech recognition
- Word-sense disambiguation
- Natural language processing
See also
- Applications of artificial intelligence
- List of artificial intelligence projects
- List of emerging technologies
References
