The description for how to replace the human
Human endeavour has always been to make life easier, faster and convenient with improved productivity, efficiency, and effectiveness towards the broader goal of solving our problems and fulfilling our needs or objectives. In the last two centuries, this endeavour has reached new peaks at exponential speeds. Take for example the case of automobiles. Until the beginning of the nineteenth century, our ancestors heavily relied on animal-drawn carriages for land-based conveyance and transportation. These conditions underwent a dramatic change when the early forms of engine-based vehicles started to appear and became increasingly popular. Why these became so popular? Because these engine-based vehicles were faster, could carry more load, travel longer distances and its controls were easier and predictable.And after two hundred years since cars and trains first appeared on the face of this world, here we are today, bracing to enter into the age of self-driving cars.
Automation is not a new phenomenon. We humans have always had this tendency to get more and more things done by the machines and specifically those things which the machines could do better than us.This is what drives the cause of automation. We could see this in the example cited above. In this article, we’ll discuss the evolution and growing dominance of Robotic Process Automation and Artificial Intelligence.
Robotic Process Automation (RPA)
By the first quarter of the 20th century, workflow automation had begun to find its place in various industrial and manufacturing units. Workflow automation refers to replacement or reduction or simplification of manual and paper-based processes with digital and automated solutions.It had a significant impact on productivity, efficiency and effectiveness of the manufacturing units and its applications eventually spread to other business processes which were about to get increasingly relied on computers in the decades to be followed.
Towards the fall of the 20th century, businesses began to face the issue of incompatibility between the conventional legacy systems and the evolving software tools and applications. This gave rise to the use of screen scraping software to bridge the gap between the old and the new.However, it still suffered from many existing and evolving limitations.
The evolution of RPA has its roots in artificial intelligence as well. Although the idea of Artificial Intelligence (AI) has been in existence for more than 60 years now, it is only in the last decade or so that it has started to gain a lot of attention and momentum. AI is the idea to empower machines and computer systems to exhibit human-like intelligence and judgmental abilities with the ultimate motive of automation.
With the cumulative effect of all these developments which has contributed to the scope and scale of the contemporary automation technology, what we have today are the software robots that are capable of mimicking human actions in the execution of various routine and repetitive operational activities by working on various computer-based business information and communication systems. Automating business processes through the use of software robots is the core idea behind Robotic Process Automation (RPA). Various industries and business processes where RPA is used include banking, insurance, customer service, data entry, communication management, report management etc.
To read more about Robotic Process Automation, click here — What is Robotic Process Automation (RPA)?
The idea of machine intelligence can be traced back to mythologies. And since then this figment of human imagination has kept on surfacing again and again at different ages in one form or the other.
However, in the year 1950, it was Alan Turing who pioneered to figure out if machines could exhibit human-like or equivalent intelligence. Alan Mathison Turing was a British scientist, mathematician, crypt analyst and a pioneer of computer science who is also reckoned for his feat of breaking into ‘The Enigma Code’ during the Second World War.
The term ‘artificial intelligence’ was first coined by Dr. John McCarthy at the Dartmouth Conference of 1956. Since then some of the most significant introductions and developments made in the field of AI include natural language processing, robotics, neural network, logic and symbolic reasoning, expert systems, use of algorithms, brute-force computing, intelligent agents, data mining, search engines, speech recognition, machine learning, deep learning, cognition, Big Data and artificial general intelligence.Reaching here took us five to six decades. However, in the last 10 years or so,AI has again started to make a buzz in today’s closely intertwined worlds of business and technology.
Input Sources: (1), (2), (3), (4)
The business case: Robotic Process Automation and Artificial Intelligence
The fundamental difference between RPA and AI is that the former is only a software tool or a software program for automating a certain category of routine and repetitive operational activities which are otherwise executed by human employees in a business enterprise while AI is a broader concept of designing and developing machines and software programs for automation(systems approach), self-learning and most importantly, with the ability to deal with input and output of diverse nature from varied sources. Both RPA and AI can exist independent of one another. However, AI can be applied on RPA. Combined together,these two can form a powerful tool for automation for business enterprises. Some of the advanced applications of Robotic Process Automation (RPA) and AI in different business processes and verticals are depicted in the following diagram.
Diagram 1 — Few applications of RPA and AI
With the exponential speed at which Artificial Intelligence is developing,backed up with the keenness shown by the big players like Google, Facebook, Amazon, Tesla and even lesser known but high-potential entities like ADDO-AI (farming), ELSA (linguistics), Scry (prediction engine) and Sig Tuple (healthcare)for research& developmental activities in the field of AI applications, it may not be very hard to fathom that AI is on its way to redefining how we make use of machines by making them more and more intelligent.
Input Sources: (5)
Disclaimer: The above content/publication is intended only to provide a general overview and is not to be used as a basis for the exercise of any business or professional judgment.
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Consequences of these technologies to human mankind
=humans being replaced by machine
AI will cause a global unemployment rate up to 50% with the next 30 years or faster
If it is more cost efficient to automate a job, rather than hire a person, it is simply a matter of time before humans are replaced as companies compete for lower prices and more market share.
This is called “Ephemeralisation” – more with less.
Only because we might be capable to develop this type of technology, while thinking about the difficulties and the probability of the drastic consequences on all levels of humanity, it would be more wise not to continue this path and look at the real sources of the problems we are causing globally, such as overpopulation and our localised perception.
Localised perception vs. system perception
We tend to perceive in very linear and superficial ways, as opposed to broader, more thorough ways. This contrast could be termed localised perception vs. system perception.
Localised perception is what you see directly around you, drawing conclusions and building associations from the incomplete sensory data coming through your five-sense reality.
System perception or system thinking is about understanding intersecting processes and chain reactions. Unfortunately, such thinking does not come naturally to us. We tend to see the world as a facade, perpetuating illusions of reality.
Hence, system thinking puts into doubt the major foundations of any belief, eliminating the idea that human beings have a privileged position in the universe. We don’t have! This is the first truth we have to face and to commit to.