The debate on artificial intelligence

While tasks, whether or not they need continuous learning, can be automated, there is one thing that a soulless machine can never do—have living consciousness

Over twenty years ago, I worked for company called The Carnegie Group, an offshoot of Carnegie Mellon University’s Artificial Intelligence (AI) Laboratories. That company is long gone. Today, a think-tank goes by the same name. While extant, the erstwhile Carnegie Group worked on some of the most cutting edge AI products of its time. It was funded by a consortium of firms such as Caterpillar and USWEST (now Qwest Corp.) and its sole aim was to look for the application of AI technologies in businesses. My boss, Arvind Sathi, now an IBM scientist, received his PhD under AI pioneer Herbert Simon, a Nobel laureate who was a professor at Carnegie Mellon.

After some years of doing cutting-edge work in fields such as multilingual billing (translating complex telecom company bills into both English and Spanish) or adding ‘intelligence’ through the use of ‘heuristics’ or rules of thumb that allowed computer programs to grow in learning as they matured in use, The Carnegie Group became a victim of that most commercial of all drivers—earnings—and had to shift to plain vanilla IT services. It then simply got acquired.

An ideal intelligent computer program can change itself to take actions that maximize its chance of success at performing a task. According to computer scientists Stuart Russell and Peter Norvig, the term “Artificial Intelligence” is applied when a machine mimics ‘cognitive’ functions that humans associate with other human minds, such as ‘learning’ and ‘problem solving’.

Contrast this with process automation—robotic or otherwise—which takes manual tasks that do not need much learning and simply mechanizes them. This could be as simple as the scanning of invoices to be processed in an accounts payable system. All the programmer has to do is define where on the invoice fields such as amount due and payment address show up, and then program the system to look in those particular spots to find this information. This step then becomes automated and removes the need for a manual keyboard operator to input such information onto the system, thereby displacing these keyboard operators. This kind of programming is not AI.

Most IT services firms selfishly blur the line between process automation and AI. Despite their best efforts at obfuscation, the line is really clear. Automation simply mechanizes routine tasks. But in AI, the computer program itself learns as it goes along, creating a database of information that it then uses rules of thumb to analyse, and in a vital twist that has occurred in machine learning in the last 36 months, these databases themselves generate additional computer programming code as they learn more, without the need for an army of computer programmers. In AI speak, this is now often referred to as ‘deep learning’.

As AI becomes more capable, it simply is no longer considered ‘intelligent’. For example, the multilingual work I used to do over two decades ago is no longer called AI since it is now routine. So will it be with many of the programs now considered to be on the cutting edge of AI.

What is not in doubt, however, is that automation—whether routine or ‘intelligent’—will lead to seismic shifts in employment, especially in India with its armies of programmers, and much like the industrial revolution caused in the 1800s in the West. People spinning or weaving fabrics lost their jobs after Eli Whitney invented the cotton gin in 1794, many a buggy-whip maker after Karl Benz invented the automobile as we know it in 1885, and several bank cashiers after the ATM was invented. History—and classical economics—has proven time and again that a revolution such as this simply changes the nature of human work in the long term (after the excruciatingly painful short-term effects of job displacement have worked themselves out). Stop suggesting computer programming as a future profession to your children, unless you’re sure they will be genius scientists.

Simon, Tom McCarthy and others founded the AI field on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. This raises questions about the ethics of creating artificial beings endowed with human-like intelligence. The Economist, in a recent article says that it is not just programmers who will lose jobs to AI, but also pilots, machinists and others. It quotes Elon Musk, himself a heavy investor in AI, who says “with artificial intelligence, we are summoning the demon”.

This requires a quick foray into metaphysics to debunk. While tasks, whether or not they need continuous learning, can be automated, there is one thing that a soulless machine can never do, and that is to have living consciousness.

Computer programs can be taught tricks that involve the application of learning, just as apes, dogs and humans can, but learning is not intelligence. Living consciousness is the key to all true cognition.

If you doubt me, then simply ask yourself who is listening to these words as you read them to yourself. Is it your learning neurons—or some other, larger field of consciousness into which words and thoughts like these come and go and are understood? Next, go ahead and ask yourself whether you will lose your job to AI—and watch your mind (your learning repository database) respond. Both the question, and your answer to it, whether driven by the limbic response of fear or by the intelligent reasoning of your database, are perceived by the real living consciousness in you. And unlike learning, it is this consciousness that is the root of true cognition. Only sentient beings have it. Even apes and dogs have it, though to a lesser degree than us; a computer program automatically generating lines of code so that it can make itself more efficient does not.

But it can put you out of a job, so learn new skills to shift into the AI-enabled economy, just as artisans did two centuries ago to shift into the industrial age.

Source | Mint | 5 July 2016

Regards

Pralhad Jadhav

Senior Manager @ Library

Khaitan & Co

Blog | http://pralhad-fyilibrarian.blogspot.in/

Best Paper Award | Received the Best Paper Award at TIFR-BOSLA National Conference on Future Librarianship: Innovation for Excellence (NCFL 2016) on April 23, 2016.  The title of the paper is “Removing Barriers to Literacy: Marrakesh VIP Treaty”

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