'Technological Intuition' -- The Must-have Skill of the Digital Era

In my view what will make or break a disruption using AI technologies is not the hardware but the software, which is us and our technological intuition to challenge common perceptions of what defines good performance.
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By Märtha Rehnberg, Master student at Copenhagen Business School, Denmark, and member of the Leaders of Tomorrow community

When a technology pops up, a window of opportunity opens to transform our world, to address the truly big issues of our time be it environmental degradation, social inequality or global health. This is a brief yet defining moment that terms how a technology is applied in our homes and organizations, which market players will dominate its development and control its distribution. An attempt to disrupt our world with technology is defined right here, by those present and their abilities. Up until now, this space has naturally and in large been taken up by providers of technology and early adopters. It is them who have defined originality in technology and its disruptive potential, and it is them who finally have moved quickly to build the institutions suitable to promote its widespread application in society. But, as technology is increasingly embedded in society so should the discussions be regarding its purposeful application.

The next small BIG thing I argue is technological intuition - our ability to derive from a functional view where technology is a mere instrument, towards one in which technology serves as platform for an open dialogue about societal needs and goals. Technological intuition should thence be extended beyond the base of technology providers and early adopters, beyond the walls of the engineering classroom or the physics laboratory, to society at large. Technological intuition I argue, is the ubiquitous must-have skill of leaders of 'today' and certainly of those of 'tomorrow'.

Fascinated by the notion of disruption and the role technology plays in solving the 'big issues', I am relentlessly scouting the 'defining moments' of emerging technologies. The last couple of months this exercise has led me to hyper intelligent or artificially intelligent (AI) technologies. Technologies that prosper with the exponential growth in computational power we see today, and technologies that gain intelligence from the exponential growth in data. Affective computing, prescriptive analytics and quantum computing are potential candidates of AI technologies that one day, not long from now, may generate solutions to environmental degradation, social inequality, global health or even to issues yet uncovered by with human non-artificial intelligence. As these technologies advance, we need to be ready to ask the right questions and create the right context for them to operate in. We need technological intuition.

Big data and AI are no news to us. As an executive, big data is pitched to run current operations more efficiently; as a policy maker make policies more legitimate; as a researcher research more credible; and as an entrepreneur market exploration less costly. But big data is also hyped, and that is because now more than ever, we are faced with information overload which is also why artificial intelligence, a once provocative idea, is gaining relevance. Coined by Herbert Simon in the 60s as "the science of mimicking human beings" AI mimics dominant perceptions of good performance from the data at hand. Unless we explicitly ask it to, or temper with its data input, AI filters away what does not fall under this dominant perception, and so eliminates information overload. In this method lays the technology promise and its peril.

On a smaller scale there are obvious benefits with AI technologies. Siri or Google search apps installed on our smartphones show how AI works to categorize, filter and select data to indeed become a reliable and credible source of information. However, on a grander scale, what solutions will see from using quantum computing to address environmental degradation, social inequality or global health? Do we then really want dominant perceptions of good performance? Or do we in fact want the outlier data? Even better... do we want data at all?

In my view what will make or break a disruption using AI technologies is not the hardware but the software, which is us and our technological intuition to challenge common perceptions of what defines good performance. In this sense, knowing when to use AI, and when not to use it will be key, as in its current shape it does not operate with, nor value, data which does not fall under this dominant perception of 'good performance'. Educating ourselves with ethical, critical and analytical minds apt to actively select data inputs and make new, yet relevant combinations of data should nurture transformation and hold back reproduction. As should, the organizational and institutional mechanisms developed to support conducive social networks and organizational values, which encourage intuition and human non-artificial experience.

I am not an engineer or a quantum physicist, but in writing this piece I assume the stake I have in technology and so the role I have the dialogues about its purpose and goal. A new mindset towards the use of technology is the seemingly 'small' change needed to create the next BIG thing. In this case - technological intuition.

This post was written in the light of the topic "Proudly Small" debated at the 45th St. Gallen Symposium held on May 6-8, 2015.

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