Artificial Intelligence: How far or how close? | Sherpas in Blue Shirts

Progression of technology

Technology has advanced to the extent that the sci-fi stories have come close to becoming reality. Whether it is the humanoid AI from “Ex-Machina,” Skynet from “Terminator,” or JARVIS from “Iron Man,” most people might likely agree that nothing seems impossible to achieve. The debate lies on how far are we from getting there. And here’s why we are probably much closer than most of us might actually think.

Ray Kurzweil – the American author, inventor, futurist well known for his predictions about artificial intelligence and the human race – suggests in what he calls “the law of accelerating returns” that the rate of change in a wide variety of evolutionary systems tends to increase exponentially. This includes the evolution of technology as well. Kurzweil suggests that this exponential technological growth is counter-intuitive to the way our brains perceive the world, as our brains were biologically inherited from humans living in a world that was linear and local. Due this exponential nature of growth, all predictions made based on past and present growth rates would lead to massive underestimations of the future, which in turn would lead to great skepticism in our future projections. If Kurzweil is correct, the level of advancements we would experience by jumping to 2035 would be equivalent to what a person from 1750 would experience in 2016.

So, advances are getting bigger and happening more quickly than before. This suggests some pretty dramatic things about our future, right?

This theory is well demonstrated in the case of business services (business process and IT services) in terms of the adoption of Robotic Process Automation (RPA) – or rather, the lack of it. The role of technology (RPA in this case) in delivering services has evolved at a very fast rate, faster than what one would have naturally perceived, and the skepticism in future projections resulted in most enterprises’ seeming unpreparedness for robotic automation. The economic downturn that started toward the end of the last decade should have been the perfect trigger for RPA uptake in business services. RPA adoption seemed like a natural corollary as enterprises concentrated feverishly on cost savings, and trimmed their support functions in the wake of the recession … but that didn’t happen. A very important technological development has been presenting itself in the form of RPA, and most enterprises were clueless about the impending disruptions. It was not until recently that enterprises started to take a serious look at RPA. Even now, action is lagging the hype, though the upward trajectory for RPA adoption from here onward should be exponential.

Era of Cognitive Disruption – the road to Artificial Intelligence

Cognitive disruption and its usage in business services is an extension of RPA’s story. Many people are confused about the term Artificial Intelligence, mainly because it’s a very broad subject with diverse set of applications ranging from smart phone apps to self-driving cars to something much more dramatic in the future, and because of the way it’s portrayed in popular media.

Almost all the AI and cognitive platforms that have been developed to date, ranging from iPhone’s Siri to Google’s self-driving cars to more sophisticated systems such as IBM Watson and IPSoft Amelia, are examples of what are called Artificial Narrow Intelligence (ANI) systems – AI that equals or exceeds human intelligence in specific areas. The next generation of AI, Artificial General Intelligence (AGI) – AI that is as smart as a human and can perform any intellectual task that a human being can – may still sound like science fiction; but it could suddenly become very real due to rapid advancements in technology. We keep coming across claims made by various AI developers about how close they are to achieving the next level of cognitive intelligence. For example, IPSoft claims that its artificial intelligence platform, Amelia, is close to achieving “near human cognitive capabilities” and we are going to hear more and more about AI in the coming months and years. However, many such claims are still met with great skepticism, and understandably so.

AI-enabled automation of knowledge work could cut employment costs by $9 trillion by 2020, according to estimates by Bank of America. This depicts the huge potential for near-complete automation of core and repetitive businesses functions in the future. Many enterprises missed the early adopter bus for RPA, in a perfect example of the law of accelerated returns. The question is, “Will they repeat the same mistake for AI?” Or, more correctly, “Are they ALREADY REPEATING the same mistake for AI”?

Future-ready enterprises

Being reactive is certainly not the best way to realize full benefits of important technological advancements, especially in highly competitive markets. In order to be future ready, enterprises need to cut through the web of skepticism, and proactively take necessary steps to align themselves to what is about to come. Due to the counter-intuitive nature of the progression, this is probably even more challenging than it actually sounds.

Business services is inherently an area which is seemingly laggard in any types of innovation. Most enterprises are reluctant to doing untested innovation in back-office processes. The primary challenge is the chicken-and-egg problem… getting budget allocation without demonstrable benefits out of using AI, and vice-versa. Enterprises can move past this problem by starting small with a small seed budget, creating liquidity in a small segment of the market, getting the virtuous circle to work for them, demonstrating some benefits, getting stronger buy-in, obtaining a bigger budget for bigger AI projects, and extending to adjacent areas.

Several companies, such as Baidu, Black Knight, Facebook, Google, IBM, Hitachi, and Microsoft are investing heavily in AI. And they are not only at the forefront of the latest technological developments, but are also laying the groundwork for the future developments.

Technological advancement is progressive, and organizations need to prepare for this journey, rather than seeing it as a destination. Enterprises are already in the midst of robotic revolution, and with Kurzweil’s law of accelerating returns in mind, it is time they start embracing the cognitive era.

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