In the year 1986, when I was pursuing my master’s degree from IIT Mumbai, we had a full course in AI. It had a very interesting computer game called “Predict the Animal”. The game allowed you to think of an animal and after asking you some questions, to which you only had to reply in ‘Yes’ or ‘No’, the machine accurately predicted the animal you had thought of. The game started by asking a simple question like, is it herbivorous or carnivorous? So, if say, you had thought of a ‘cow’, and replied herbivorous, the game may respond that it is a goat. Because at that stage of the game the only animal listed as herbivore in its animal database was a goat. When the game realized that it has made a wrong prediction, it would give up and ask you, what question could it ask to distinguish between a cow and a goat? You will probably say, “Is it huge and bulky”? to which the answer for goat will be ‘No’ and for cow will ‘Yes’. The game shall start all over again and the computer, while playing the game shall also learn to distinguish between different animals and ask right questions for the purpose. After playing the game for a few rounds, the computer always predicted the right animal after asking a few questions. The earliest versions of Artificial Intelligence algorithms were taking shape at that time.
Since then AI has come a long way over the last 33 years. Today Artificial Intelligence is making its presence felt across all domains of businesses. Whether it is Retail or health or education or finance sectors, AI based applications are making a ubiquitous presence across all sectors. So, what is AI? How does it differ from Human Intelligence? Earliest computer programs were linear in nature and had a fixed logical flow. The computer executed this algorithm on the available data and produced the same result every time it executed the program. However, humans realized that the natural intelligence did not behave in such a static manner always. It applied the contextual information to processing of the data and came out with different results depending upon the context in which it operated. Thus, for example, a given number was big or small in context with which it was referred to. Thus 35 degrees Celsius was high for humans to bear but low for water to boil. This ability of the humans to learn from their environment and adapt to the changing conditions needed to be replicated in the computers. This meant writing computer algorithms that adapted and changed every time it encountered contextual data. More data it crunched, more the algorithm learnt and more it adapted itself to the changing conditions. These adaptive computing algorithms lead to many different sub fields with in Artificial Intelligence. These fields included Natural Language Understanding, Machine Learning, Robotics, Deep Learning &, Neural Networks.
Today AI based applications are driving several sectors of the economy. Industrial Robots have automated the production of several industries. Auto Manufacturing is one major example. Robotics based production is much faster and is also more accurate leading to much lesser wastage in terms of material and faulty manufacturing. Retail sector is now able to accurately predict the buying behaviour of its customers on the basis of the deep learning algorithms crunching the customer data on a real time basis. This enables the retail stores to adjust their inventory just in time to satiate the customer demand.
A prominent home application of AI is Voice activated intelligent bots like Alexa. These devices are making it much easier to operate general home appliances and demand music and entertainment and news on demand through voice actuated AI applications run on a small device plugged in to a home socket.
Machine learning algorithms are helping major social media giants like Facebook to fine tune their advertisements to specific log ins on the basis of their browsing history. Data pertaining to billions of searches on Google is helping to provide the browsing history and buying behaviour of people and helping the retails industry to finetune its products and Advertisement spend.
AI is also finding major use in the field of medicine. IBMs ‘Watson” is an early example of an online doctor capable of diagnosing a given disease on the basis of the symptoms and providing medication for the same. The field of surgery is replete with many surgical instruments with AI and robotics capability helping human surgeons undertake complicated surgeries. Recently an operation done in Indiana Police in USA, a surgeon using a Google Glass was automatically supplied with imaging and diagnostic data pertaining to the organ S/he was operating on seamlessly. This meant that the surgeon did not need to take his/her eyes off the organ to refer to the imaging or diagnostic data while performing the surgery.
Driverless cars are fast becoming a reality. The driverless car developed by Google has already clocked a million mile. The city of Singapore has already launched the first driverless Taxi service in the city. It is expected that in a decade or so, driving as a profession shall vanish and most of the cars on the streets will be driverless cars.
The speed at which Artificial Intelligence based applications are proliferating across all domains of the economy, it is very difficult to predict its complete impact over the coming decade. Almost all sectors of the economy shall be impacted by AI based applications and devices.
Driverless cars shall certainly become a reality. That shall mean many less cars on the road and nearly zero accident rates. (Since automated driverless cars shall always avoid collision using AI and proximity devices.)
The communication as we know shall undergo a complete change. Holograms (Virtual and Mixed reality devices) shall change the communication experience across the entire spectrum. Someone sitting in India shall be able to deliver a lecture in the USA as if the person was present there. Online real time translation shall also mean that the lecture given in one language will be translated online and delivered in any other language of choice using Natural Language algorithms.
Enormous proliferation of IOT (Internet of Things) devices across all sectors of an economy shall mean that these devices shall generate voluminous data. Such data (in Tera and Peta Bytes) will only be possible to be crunched and made sense of using AI and machine learning techniques. Thus, IoT controlled Devices driven by AI based applications, continuously fine tuning their actions on the basis of analysing big data produced by IOT devices shall govern our life in the year 2030. We will not drive to office, we will interact with virtual people using holograms rather than real people, machines shall do most of the mundane routine work, social media is likely to impact the way people shall interact with each other and socializing as we understand today may undergo a complete change.
Will such an influx of AI in our lives impact the jobs. Will it mean that a number of jobs in the economy shall be lost to smart Robots, who shall do the same job better, at a lesser cost and more accurately? The verdict on job losses is mixed. If we go by the history of automation, we find that automation has always created more jobs rather than taken away jobs. Advent of computers and automation has always helped expand the economic activities faster and has helped grow the economies across the globe. However, there is a possibility that the types of jobs may undergo a change. People may have to re-skill themselves in to using newer technologies and some professions may be lost for good. Blue collar jobs are likely to give way to white collar jobs. People at the bottom of the pyramid may find it very difficult to find jobs because of robots and IoTbased devices undertaking all mundane repetitive jobs done by humans. This may turn out to be a blessing in disguise and the quality of human effort will undergo a change for the better.
About the Author
Wg. Cdr. Pradeep Valsangkar is a postgraduate Engineer from the IAF. He completed his M.tech in Computer Science from IIT Powai and MBA from FMS Delhi. He is also a graduate of Defence Services Staff College of India. After leaving service he has worked in various capacities across different ITservices companies. He has been working as a senior consultant of the world bank for last 15 years, a visiting faculty at Institute of Management technology and runs his consulting firm Global Consulting Solutions.
