Artificial Intelligence began when computer scientists asked the question of whether Computers can think as intelligently as humans. Alan Turing the great computer scientist was the first to think of a test called Turing test, that a computer can pass to qualify as being intelligent. Check Artificial Intelligence BTech Course here.

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Turing test is based on the idea that if you cannot distinguish whether you are talking to a human or to a computer then the computer is deemed as being intelligent.

Artificial Intelligence is based on the concept that even dumb computing machines can be as intelligent as humans or more. One computer scientist claimed that the question of whether machines can think is the same as the question as to whether submarines can swim. 

The concept of Artificial Intelligence has been depicted in many science fiction novels and movies like Matrix Trilogy, Terminator, 13^th Floor, I Robot series by Isaac Asimov and so on.

It is interesting to not that Artificial Intelligence has created much revolution in many fields where thinking machines have started replacing thinking humans. But at the same time the field of Artificial Intelligence has not met with the hype that had been created for it.

Great expectations were made for the field of Artificial Intelligence and it is found that in many fields humans still perform better that Artificial Intelligence. For example, even though computers have defeated Garry Kasparov (the International Chess Grandmaster) in chess, even then computers have not been able to replace human computer programmers in software industry.

Roger Penrose’s Pessimism about Artificial Intelligence

Roger Penrose has written a very nice expose of the field of Artificial Intelligence in his books The Emperor’s New Mind and The Shadows of the Mind. Roger Penrose is an acclaimed theoretical physicist, who worked out the theory of Black Holes with Stephen Hawking. Black Holes are mystically scientific objects in space with escape velocity greater than the speed of light, so that even light cannot escape them.

Roger Penrose then shifted his field of expertise from Theoretical Physics to Computer Science and Artificial Intelligence and found that he was able to apply his in depth knowledge of Physics, Theory of Relativity, and Quantum Mechanics to prove that computers can never match human intelligence.

This is because Penrose believes that there is something special about human consciousness which cannot be replicated in computers. So whatever Quantum Phenomenon is going on in the human brain cannot be replicated in computers.

The best way to understand Penrose’s argument is to begin with Godel’s Theorem. Godel’s Theorem has a fascinating history. To understand Penrose’s argument we will begin with Godel’s Theorem. To understand Godel’s theorem, we will begin with a book called Logicomix.

Logicomix is a book which graphically illustrates the history of the foundations of mathematics and computer science. The quest for Truth. The quest for Mathematical Truth. The quest for Logical Truth. All subjects contain Beautiful, Eternal, and Useful Ideas. Philosophy is Ideas about Ideas.

So Philosophy of Mathematics is covered in detail in a graphic manner in the book Logicomix. Logicomix begins with the biography of Bertrand Russell, a philosopher of logic and mathematics. Bertrand Russell tried to extend the works of Frege.

Frege tried to show that all mathematics can be laid with Logic as it’s foundations. So to begin with Bertrand Russell created a Paradox which demolished the Logical and Set Theoretical foundations of Mathematics.

Frege had tried to base mathematics on set theoretic and logical foundations. But Bertrand Russell thought of the Russell’s Paradox which totally devastated Frege’s plans.

Russell’s Paradox is as given below:
Imagine R as the set of all sets that do not contain themselves. The paradox then asks does R contain itself or not? The paradox then asks if R contains itself then it does not contain itself. If it does not contain itself then it contains itself. So it can neither contain itself nor not contain itself.

This paradoxical possibility for set membership totally devastated the foundations of Frege’s attempt to lay logical and set theoretical foundations for mathematics.

After all the question being asked was as to what is a number. Can one define a number in a set theoretical manner? If we do define a number in a set theoretical manner then 2 can be defined as the set of all sets with two elements, that is the set of all sets with the property of 2-ness. Once on defines 2 as the set of all elements with property 2-ness then one finds out that it takes Bertrand Russell 40 pages to prove that 1 + 1 =2.

Though Russell’s paradox demolished Frege’s attempts to lay logical and set-theoretical foundations of Computer Science, it still provided much material for future computer scientists who worked on many fields including Artificial Intelligence.

Then Bertrand Russell set out to complete what Frege had started. It turned out that Bertrand Russell named the project as Principia Mathematica, which is the same name as given by Isaac Newton to his magnum opus.

It then transpired that this stream of thought inspired John Von Neumann, Kurt Godel, David Hilbert, Georg Cantor, Alan Turing, and Ludwig Wittgenstein.

It is fascinating as to how the abstruse abstract works of Frege could lead to such practical consequences in the fields of computer science and artificial intelligence.

The book Logicomix clearly mentions that Bertrand Russell had more dimensions to him than being a philosopher of mathematics. It is true that Bertrand Russell tried to apply his intellect and works to practical and worldly concerns such as International Politics and World Wars.

The book Logicomix also mentions that this world is full of much madness and much sadness and tries to suggest that Logic, Mathematics are no exception to this and are indeed full of their own madness and sadness. In fact the book Logicomix suggests that Logic and Mathematics are a form of madness.

There is a BBC Documentary Dangerous Knowledge which describes the Tragedies of Genius minds who laid the foundations of Computer Science and Artificial Intelligence.

One such tragic figure is Georg Cantor, who was the first westerner to suggest that one infinity can be bigger than another infinity. He created a Cantor hierarchy of infinite sets. Though Cantor may not have been aware of this but his ideas about Infinity had been anticipated by Ancient Hindus who wrote many Upanishad slokas on Infinities.

One sloka is Punidham which describes that even if one takes one infinity out of another infinity, infinity still remains infinity. Another such sloka is Sri Hari Anant. Sri Hari Katha Ananta. In which it is given that one infinity (Ananta) can be bigger than another infinity (Anant).

Thinking too hard about Infinity mad Cantor go mad and he died alone in an insane asylum. It made Cantor also many enemies. Some of his enemies believed there was no infinity.

Some of his enemies believed there was only one infinity. So Cantor’s enemies did not like the idea of a Infinite Hierarchy of Infinities. Cantor has heavily attacked for this and Cantor died alone in an insane asylum.

The proof given by Cantor of his hierarchy of infinities rested on the Diagonalization argument and the idea that the Power set of an Infinite Set has a higher cardinality that the Infinite Set itself.

David Hilbert also had a tragic life in that his son was diagnosed as a paranoid schizophrenic who always panicked that his enemies are out to get him and kill him. Despite the tragedies of David Hilbert, he laid out in 1900 International talk on mathematics at Paris  some problems that are the future of mathematics. One such problem was to show that all mathematical truths are provable. Another problem was to show that all mathematical truths can be decided by an algorithm.

The first of the Problems was solved in the negative by Kurt Godel, who also lived a Tragic life and died a Tragic Death. Kurt Godel showed that in a system of mathematics powerful enough to describe numbers there exist true statements which cannot be proved logically from the axioms.

This is the famous incompleteness theorem of Kurt Godel.  Kurt Godel gave the proof of this in a talk to an audience that contained John Von Neumann as a member. Nobody understood what Kurt Godel had to say. Only John Von Neumann understood it and even extended it to Godel’s Second Theorem which stated that if mathematic is consistent then it is not complete and if mathematics is complete then it is not consistent.

When Von Neumann explained it to Godel, Godel revealed that he had already worked out this solution but had not shared it in the talk.

The BBC Documentary Dangerous Knowledge shows that Godel became paranoid that people were trying to poison his food, and in an attempt to avoid being poisoned he starved himself to death. A very illogical end for a great founder of logic. Very Ironic indeed.

BBC documentary Dangerous Knowledge also mentions that tragedies of Alan Turing. Alan Turing solved the second question asked by David Hilbert in the Negative. Turing showed that there exist problems which cannot be solved algorithmically. This led to Turing Machine concept and the concept of Universal Computer. This caused a big revolution in mathematics and computer science.

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Alan Turing also gave the first test to verify whether a machine has become intelligent known as the Turing test. Imagine an entity who dialogs with you from behind a curtain, and you have to determine whether you are talking to a human or a computer. If you are unable to distinguish the two then it can be deemed that the machine has passed the Turing test and is intelligent. Turing had a Tragic life and Tragic death and committed suicide.

Another Tragic life was that of Wittgenstein, who was a disciple of Bertrand Russell who gave the first mystical take on Logic by publishing Tractatus Logico Philosphica.

Now we come back from the BBC documentary Dangerous Knowledge back to the book Logicomix. In this book we see the story of how Bertrand Russell kept trying to work out a logical and set theoretical foundation of computer science.

This brings us back to the book Emperor’s New Mind by Roger Penrose. In this book one of the arguments that Roger Penrose gives is based on the Godelian Argument that a system of logic cannot prove it’s own completeness and consistency. Since humans are able to do this therefor Roger Penrose believes that there is something special about human consciousness which cannot be replicated by computers.

Another argument that Roger Penrose gives in Emperor’s New Mind is that there may be some Quantum Phenomenon happening in the human brain which make human consciousness and human intelligence special thereby giving us the power to have feelings which computers cannot have. Thus, Roger Penrose is pessimistic about the future of Artificial Intelligence.

Differences between Humans and Artificial Intelligence

As per Alan Turing’s Turing test, when Turing was describing the Turing test to check when a computer qualifies as intelligent, we noticed that there are some aspects of human consciousness and intelligence that cannot be replicated easily in computers. One such example is feelings. Can computers ever be smart enough to be able to feel feelings? Or even replicate feelings? This may turn out to be a tough nut to crack. After all sentiments and feelings are what make us intelligent too.

When it comes to intelligence there are many ways to describe and quantify intelligence. One way to quantify intelligence is through Intelligence Quotient. Intelligence Quotient (IQ) is something that may be easier for a computer to capture. We already know that computers can defeat humans in chess.

Another way to capture intelligence is Emotional Quotient (EQ). Emotional Quotient deals with feelings and sentiments and our ability to deal with them. This may turn out to be more difficult for a computer to capture.

Another way to capture intelligence is Spiritual Quotient (SQ).  Spiritual Quotient deals with our intelligent ability to understand Spirituality, Soul, and God. This may turn to be even more difficult for a computer to capture.

Also, the exact Quantum Phenomenon that goes in our brain may be difficult for Computers to capture.

Science Fiction Books and Movies inspired by Artificial Intelligence

Fascination is an important aspect of knowledge and education. Most people become Scientists, Doctors, or Engineers because they have spent much time in their childhood reading fascinating science fiction books or watching fascinating science fiction movies. Artificial Intelligence is no exception. In the case of Artificial Intelligence in this section we will give a survey of some great science fiction books and movies based on the themes of Artificial Intelligence.

1. Matrix:
   This movie is a very Dystopian take on Artificial Intelligence. In this movie Artificial Intelligence has overtaken humanity and enslaved humanity in a virtual simulation. Humans spend their lives floating in liquid cells being fed simulation data to their brains. Humans believe that they are living in the real world, but their reality is a virtual simulation. This movie also mixes science fiction with religious themes from Christianity, Buddhism, Gnosticism, Pythagoreanism, etc. The basic idea is that a Savior is prophesied to be born who will liberate humanity from the slavery of Artificial Intelligence. The concept of Dreams and Computer Simulation is similar to the concept of Lord Krsna’s Maya.
2. Terminator
   This movie is also a very Dystopian take on Artificial Intelligence. Humanity is at war with Artificial Intelligence which has tried to enslave humanity. A savior is born to save humanity. This movie also mixes Science Fiction with Religious Themes
3. 13^th Floor.

Humans spend all their time sleeping and dreaming in a virtual simulation and when they die in one simulation they wake up in another simulation.

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• Isaac Asimov’s I, Robot Series:
  This movie and book series talks of humanity’s enslavement of Artificial Intelligence machines and the machine’s struggle to deal with this. The famous 3 laws of Robotics are from these series.

Scope of Artificial Intelligence in Course Syllabus for B.Tech

 There is much scope for Artificial Intelligence in the syllabus for B.Tech. The reason for this being that Artificial Intelligence is the core basis of Automation. Whatever is being Automated is being converted into Artificial Intelligence in some form or the other.

The greatest opportunities in job markets from companies like Google, Amazon, Facebook etc.. are mainly from Machine Learning and Data Mining and Artificial Intelligence.

When students study the subject of Artificial Intelligence, they prepare themselves for a great career in Information Technology industry.

Million Dollar Question and Artificial Intelligence

One of the fundamental results in Computer Science is that somethings cannot be computed by computers and algorithms. These are called Undecidable Problems. One of the fundamental results in Computer Science is that somethings cannot be computed efficiently by computers. These are called Intractable problems.  The Time Complexity and Space Complexity of a problem measures how much Time and Space resource is needed to compute the solution to that problem.

Hence, we find that there is whole computational complexity zoo where different computational problems are classified in different sets of computational complexity. For example, the set of all problems that can be solved in Polynomial Time is known as P. The set of all problems whose solution can be verified in polynomial time is known as NP. For example, if we want to find the shortest path between two cities, now to find the solution will it take polynomial time is the question of whether this problem will belong to P.

Now suppose we are given the solution as the shortest path and asked to verify that this is indeed the shortest path then this is the problem of whether this problem belongs to NP. So, Solving in Polynomial time is P. Verifying in polynomial time is NP. This P==NP? is an open million-dollar question in computer science. This may have serious implications for the status of Artificial Intelligence since some Artificial Intelligence may be in P.

Open Challenges faced in Artificial Intelligence

 The main challenges economically are that humans may lose jobs if all work gets automated through Artificial Intelligence. This would have severe impact on many humans’ lives.

Also whether Artificial Intelligence would remain benign or become malevolent is also an open question.

Some may say that they trust humans more than they trust Artificial Intelligence. Of course there may be souls who mighty speak otherwise and claim that they trust Artificial Intelligence more than they trust humans.

What is the Future of Artificial Intelligence?

 The future of Artificial Intelligence seems glorious. Imagine being treated by an Artificial Intelligence driven Doctor, or an Artificial Intelligence driven Taxi Driver. The scenario can be Utopian for some or Dystopian for some. Some even predict that as humans will start preferring Artificial Intelligence for more and more of it’s tasks than humans, the need of humans for humans will decrease.

Children will be born in test tubes and they will be take care of by Artificial Intelligence driven “parents”.  All our wars will be fought by Artificial Intelligence driven soldiers. All our food will be cooked by Artificial Intelligence driven cooks. All our music will be composed by Artificial Intelligence driven musicians.

All our trash will be disposed by Artificial Intelligence driven cleaners. We would by taught by Artificial Intelligence driven teachers. We would even marry Artificial Intelligence driven spouses. Since Artificial Intelligence can go where humans cannot go, hence we will soon have machines that can reach out and clean and explore territory where it is hazardous for humans to venture.

Weak Artificial Intelligence versus Strong Artificial Intelligence

The distinction between Weak Artificial Intelligence and Strong Artificial Intelligence is that Weak Artificial Intelligence makes machines which are response specific limited to specific tasks. On the contrary Strong Artificial Intelligence is the optimism that we can create Artificial Intelligence that can thing and respond as or better than humans.

Conclusion

 We conclude by saying that Artificial Intelligence may be a mixed blessing full of both Utopian prospects as well as Dystopian prospects.

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