Artificial Intelligence, Disruption and V.U.C.A “Volatility, Uncertainty, Complexity, Ambiguity”

VUCA is a term whose initials respond to the acronym of volatility (volatility), uncertainty (uncertainty), complexity (complexity) and ambiguity (ambiguity) of the world that emerged after the end of the Cold War.

This acronym emerged in the 1990s to describe the ability to address situations marked by change and challenges. For leaders in the military and beyond, the doctrine emphasizes the importance of strategic decision-making, preparedness planning, risk management and the resolution of situational problems. Emerging from an intensive analysis by the military of their leadership thinking, partly conducted with business management researchers, the Army Leadership Manual was revised after the end of the Cold War. 1

The term began to be widely used in the 90s. Since then, this concept has been adopted throughout the world of leadership and management to describe the challenging conditions that companies go through.

We live in a VUCA world. Our existence is characterized by volatility, uncertainty, complexity and ambiguity, the four components of VUCA.

V = Volatility. The nature and dynamics of the change, and the nature and speed of the forces and catalysts of the modification.

U = Uncertainty (Uncertainty in English). Lack of predictability, perspectives of surprise and sense of conscience and compression of events.

C = Complexity Multiplicity of forces, mixture of issues, rupture of cause and effect and confusion that surround the organization.

A = Ambiguity. The distortion of reality, potential for misunderstandings and the different meanings of the conditions: confusion of cause and effect.

After the 1st Industrial Revolution the rhythm of the progress of our civilization began to accelerate. Currently in the 4th industrial revolution driven by Artificial Intelligence and Robotics the rapid and large-scale changes in technology have induced an exponential acceleration to our modern societies that make necessary new adaptation and survival capabilities.

While you read this article, millions of industrial revolutions per minute are being produced within the fourth industrial revolution inducing turbulence of the first order. Under this highly disruptive current scenario, new forms of work emerge that challenge the status quo of the companies that operated with the solid iceberg mentality of the 1st industrial revolution and with the computers of the 3rd revolution, «The era of the polar business and academic meltdown» In metaphorical sense of the 3rd industrial revolution gives way to a new scenario in the 4th industrial revolution or Industry 4.0 where those with more adaptive capacities will be able to survive this deglaciation.

«The strongest species is not the one that survives, but the one that best adapts»

The collaborative economy in a broad sense or on demand (gig – platform – shared – on demand economy), with a business structure of on – demand and projectized works and clusters in crowdworking mode, with global production per unit (micro – labor) and big data (big data) generated by the so-called «internet of things» (internet of things IoT), along with artificial intelligence (AI) and automation will represent a new paradigm in the way in which company and employees will relate in the future . The knowmads will lead this highly turbulent, changing and constant deglacating scenario of the structures that were supposed to be solid and stable but which in this industrial revolution are no longer so.

The nomadic term of knowledge comes from the English neologism knowmad, which combines the words know (know, know) and nomad (nomadic), and which accounts for the profile of the subject capable of being a nomad of knowledge. It was created by John Moravec to refer to the nomadic workers of knowledge and innovation. It is characterized by being innovative, imaginative, creative, able to work in collaboration with almost anyone, anytime, anywhere. A knowmad is valued for his personal knowledge, which gives him a competitive advantage over other workers. 2

Economist Frank Knight noted the distinction between risk and uncertainty. It is possible to measure risk but uncertainty can not be measured in a similar way. When risks are known, it is possible to make robust predictions. Uncertainty, on the other hand, poses unknown risks, which make forecasts difficult to make and precipitate unreasonable decisions. 3

The intelligent machines of today are driven by expert systems. These systems include software that allows decisions to be made, for example, to support a medical diagnosis or the operation of an intelligent network. The engine of that software is based on rules of type if-then that learn and emulate the expertise of the human expert. Autonomous AI-enabled robots will proliferate for a simple reason. These robots will be inexpensive. As the number of robotic devices continues to increase, the cost of the sensors decreases. The global sensors for the robotics market already exceed $ 16 billion.

Open source tools, such as Amazon’s DSSTNE, Microsoft’s DMLT, and Google’s TensorFlow, contain software libraries that enable machine learning. Google launched an open-source artificial intelligence tool, DeepVariant, that can provide a more accurate representation of a person’s genome from gene sequencing data than other methods.

Alexa and Siri from Apple use natural language processing to make decisions, oncologists train IBM Watson to help them diagnose and treat lung cancer, Tesla and Google compete to bring autonomous cars to consumers, the Israeli company Zebra Medical Systems is developing tools for radiology that has a greater precision than the human.

«As the philosopher Immanuel Kant said, one of the most influential thinkers in modern Europe and universal philosophy, the intelligence of an individual is measured by the amount of uncertainty that is capable of supporting»

References:

1. Six Creative Leadership Lessons From The Military In An Era of VUCA And COIN. Forbes
2. VUCA. Wikipedia
3. AI and the Future: Volatility Uncertainty Complexity Ambiguity. Dr. Ishwar K.Puri, Dean of Engineering Faculty. Mc Master University in Hamilton. Ontario. Canada

Fernando Jiménez Motte Ph.D (c) EE, MSEE, BSEE

CEO of NEUROMORPHIC TECHNOLOGIES NT Robotics, Control Systems, Artificial Intelligence AI

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