How Will Artificial Intelligence Affect Our Lives In The Next Ten Years?

The primary focus of this essay is the future ofspeeding up tasks still performed by people such
Artificial Intelligence (AI). In order to betteras the rule based AI systems used in accounting
understand how AI is likely to grow I intend toand tax software, enhance automated tasks such
first explore the history and current state of AI.as searching algorithms and enhance mechanical
By showing how its role in our lives has changedsystems such as braking and fuel injection in a
and expanded so far, I will be better able tocar. Curiously the most successful examples of
predict its future trends.artificial intelligent systems are those that are
John McCarthy first coined the term artificialalmost invisible to the people using them. Very
intelligence in 1956 at Dartmouth College. At thisfew people thank AI for saving their lives when
time electronic computers, the obvious platformthey narrowly avoid crashing their car because of
for such a technology were still less than thirtythe computer controlled braking system.
years old, the size of lecture halls and had storageOne of the main issues in modern AI is how to
systems and processing systems that were toosimulate the common sense people pick up in their
slow to do the concept justice. It wasn't until theearly years. There is a project currently
digital boom of the 80's and 90's that theunderway that was started in 1990 called the
hardware to build the systems on began to gainCYC project. The aim of the project is to provide
ground on the ambitions of the AI theorists anda common sense database that AI systems can
the field really started to pick up. If artificialquery to allow them to make more human sense
intelligence can match the advances made lastof the data they hold. Search engines such as
decade in the decade to come it is set to be asGoogle are already starting to make use of the
common a part of our daily lives as computersinformation compiled in this project to improve
have in our lifetimes. Artificial intelligence has hadtheir service. For example consider the word
many different descriptions put to it since its birthmouse or string, a mouse could be either a
and the most important shift it's made in itscomputer input device or a rodent and string
history so far is in how it has defined its aims.could mean an array of ASCII characters or a
When AI was young its aims were limited tolength of string. In the sort of search facilities
replicating the function of the human mind, as thewe're used to if you typed in either of these
research developed new intelligent things towords you would be presented with a list of links
replicate such as insects or genetic materialto every document found with the specified
became apparent. The limitations of the field weresearch term in them. By using artificially intelligent
also becoming clear and out of this AI as wesystem with access to the CYC common sense
understand it today emerged. The first AIdatabase when the search engine is given the
systems followed a purely symbolic approach.word 'mouse' it could then ask you whether you
Classic AI's approach was to build intelligences onmean the electronic or furry variety. It could then
a set of symbols and rules for manipulating them.filter out any search result that contains the word
One of the main problems with such a system isoutside of the desired context. Such a common
that of symbol grounding. If every bit ofsense database would also be invaluable in helping
knowledge in a system is represented by a setan AI pass the Turing test.
of symbol and a particular set of symbols ("Dog"So far I have only discussed artificial systems
for example) has a definition made up of a set ofthat interact with a very closed world. A search
symbols ("Canine mammal") then the definitionengine always gets its search terms as a list of
needs a definition ("mammal: creature with fourcharacters, grammatical parsers only have to deal
limbs, and a constant internal temperature") andwith strings of characters that form sentences in
this definition needs a definition and so on. Whenone language and voice recognition systems
does this symbolically represented knowledge getcustomise themselves for the voice and language
described in a manner that doesn't need furthertheir user speaks in. This is because in order for
definition to be complete? These symbols need tocurrent artificial intelligence methods to be
be defined outside of the symbolic world to avoidsuccessful the function and the environment have
an eternal recursion of definitions. The way theto be carefully defined. In the future AI systems
human mind does this is to link symbols withwill to be able to operate without knowing their
stimulation. For example when we think dog weenvironment first. For example you can now use
don't think canine mammal, we remember what aGoogle search to search for pictures by inputting
dog looks like, smells like, feels like etc. This istext. Imagine if you could search for anything
known as sensorimotor categorization. By allowingusing any means of search description, you could
an AI system access to senses beyond a typedinstead go to Google and give it a picture of a
message it could ground the knowledge it has incat, if could recognise that its been given a picture
sensory input in the same manner we do. That'sand try to assess what it's a picture of, it would
not to say that classic AI was a completelyisolate the focus of the picture and recognise that
flawed strategy as it turned out to be successfulit's a cat, look at what it knows about cats and
for a lot of its applications. Chess playingrecognise that it's a Persian cat. It could then
algorithms can beat grand masters, expertseparate the search results into categories
systems can diagnose diseases with greaterrelevant to Persian cats such as grooming, where
accuracy than doctors in controlled situations andto buy them, pictures etc. This is just an example
guidance systems can fly planes better than pilots.and I don't know if there is currently any
This model of AI developed in a time when theresearch being done in this direction, what I am
understanding of the brain wasn't as complete astrying to emphasise in it is that the future of AI
it is today. Early AI theorists believed that thelies in the merging existing techniques and
classic AI approach could achieve the goals setmethods of representing knowledge in order to
out in AI because computational theory supportedmake use of the strengths of each idea. The
it. Computation is largely based on symbolexample I gave would require image analysis in
manipulation, and according to the Church/Turingorder to recognise the cat, intelligent data
thesis computation can potentially simulateclassification in order to choose the right
anything symbolically. However, classic AI'scategories to sub divide the search results into
methods don't scale up well to more complexand a strong element of common sense such as
tasks. Turing also proposed a test to judge thethat which is offered by the CYC database. It
worth of an artificial intelligent system known aswould also have to deal with data from a lot of
the Turing test. In the Turing test two roomsseparate databases which different methods of
with terminals capable of communicating with eachrepresenting the knowledge they contain. By
other are set up. The person judging the test sits'representing the knowledge' I mean the data
in one room. In the second room there is eitherstructure used to map the knowledge. Each
another person or an AI system designed tomethod of representing knowledge has different
emulate a person. The judge communicates withstrengths and weaknesses for different
the person or system in the second room and ifapplications. Logical mapping is an ideal choice for
he eventually cannot distinguish between theapplications such as expert systems to assist
person and the system then the test has beendoctors or accountants where there is a clearly
passed. However, this test isn't broad enough (ordefined set of rules, but it is often too inflexible in
is too broad...) to be applied to modern AIareas such as the robotic navigation performed
systems. The philosopher Searle made theby the Mars Pathfinder probe. For this application a
Chinese room argument in 1980 stating that if aneural network might be more suitable as it could
computer system passed the Turing test forbe trained across a range of terrains before
speaking and understanding Chinese this doesn'tlanding on Mars. However for other applications
necessarily mean that it understands Chinesesuch as voice recognition or on the fly language
because Searle himself could execute the sametranslation neural networks would be too inflexible,
program thus giving the impression that heas they require all the knowledge they contain to
understand Chinese, he wouldn't actually bebe broken down into numbers and sums. Other
understanding the language, just manipulatingmethods of representing knowledge include
symbols in a system. If he could give thesemantic networks, formal logic, statistics,
impression that he understood Chinese while notqualitative reasoning or fuzzy logic to name a few.
actually understanding a single word then the trueAny one of these methods might be more
test of intelligence must go beyond what this testsuitable for a particular AI application depending on
lays out.how precise the effects of the system have to
Today artificial intelligence is already a major partbe, how much is already known about the
of our lives. For example there are severaloperating environment and the range of different
separate AI based systems just in Microsoftinputs the system is likely to have to deal with.
Word. The little paper clip that advises us on howIn recent times there has also been a marked
to use office tools is built on a Bayesian beliefincrease in investment for research in AI. This is
network and the red and green squiggles that tellbecause business is realising the time and labour
us when we've misspelled a word or poorlysaving potential of these tools. AI can make
phrased a sentence grew out of research intoexisting applications easier to use, more intuitive
natural language. However, you could argue thatto user behaviour and more aware of changes in
this hasn't made a positive difference to our lives,the environment they run in. In the early day of
such tools have just replaced good spelling andAI research the field failed to meet its goals as
grammar with a labour saving device that resultsquickly as investors believed it would, and this led
in the same outcome. For example I compulsivelyto a slump in new capital. However, it is beyond
spell the word 'successfully' and a number ofdoubt that AI has more than paid back its thirty
other word with multiple double letters wrongyears of investment in saved labour hours and
every time I type them, this doesn't matter ofmore efficient software. AI is now a top
course because the software I use automaticallyinvestment priority, with benefactors from the
corrects my work for me thus taking themilitary, commercial and government worlds. The
pressure off me to improve. The end result ispentagon has recently invested $29m in an AI
that these tools have damaged rather thanbased system to assist officers in the same way
improved my written English skills. Speechas a personal assistant normally would.
recognition is another product that has emergedSince AI's birth in the fifties it has expanded out
from natural language research that has had aof maths and physics into evolutionary biology,
much more dramatic effect on people's lives. Thepsychology and cognitive studies in the hope of
progress made in the accuracy of speechgetting a more complete understanding of what
recognition software has allowed a friend of minemakes a system, whether it be organic or
with an incredible mind who two years ago lostelectronic, an intelligent system. AI has already
her sight and limbs to septicaemia to go tomade a big difference to our lives in leisure
Cambridge University. Speech recognition had apursuits, communications, transportation, sciences
very poor start, as the success rate when usingand space exploration. It can be used as a tool to
it was too poor to be useful unless you havemake more efficient use of our time in designing
perfect and predictable spoken English, but nowcomplex things such as microprocessors or even
its progressed to the point where its possible toother AI's. In the near future it is set to become
do on the fly language translation. The system inas big a part of our lives as computer and
development now is a telephone system with realautomobiles did before it and may well begin to
time English to Japanese translation. These AIreplace people in the same way the automation
systems are successful because they don't try toof steel mills did in the 60's and 70's. Many of its
emulate the entire human mind the way aapplications sound incredible, robot toys that help
system that might undergo the Turing test does.children to learn, intelligent pill boxes that nag you
They instead emulate very specific parts of ourwhen you forget to take your medication, alarm
intelligence. Microsoft Words grammar systemsclocks that learn your sleeping habits or personal
emulate the part of our intelligence that judgesassistants that can constantly learn via the
the grammatical correctness of a sentence. Itinternet. However many of its applications sound
doesn't know the meaning of the words, as this islike they could lead to something terrible. The
not necessary to make a judgement. The voicepentagon is one of the largest investors in artificial
recognition system emulates another distinctintelligence research worldwide. There is currently
subset of our intelligence, the ability to deduce themuch progressed research into AI soldier robots
symbolic meaning of speech. And the 'on the flythat look like small tanks and assess their targets
translator' extends voice recognitions systemsautomatically without human intervention. Such a
with voice synthesis. This shows that by beingdevice could also be re-applied as cheap domestic
more accurate with the function of an artificiallypolicing. Fortunately the dark future of AI is still a
intelligent system it can be more accurate in itsHollywood fantasy and the most we need to
operation.worry about for the near future is being beaten
Artificial intelligence has reached the point nowat chess by a children's toy.
where it can provide invaluable assistance in