Economic AI Literacy: A Source of Competitive Advantage

Introduction

It is backstage where the new key actor in business prepares for its role. And this is where it will remain while the play changes. It changes with the introduction of Artificial Intelligence (AI) as the new actor who represents a general-purpose technology (Trajtenberg, 2019). Based on a cluster of technologies that includes Machine Learning, Deep Neural Networks, Big Data, Internet of Things and Cloud Computing AI has finally left the research laboratories and begins to rapidly establish itself in business practice, to cross borders between industries, and to create a constant flow of new possibilities on the fly. The play changes because there is a pattern change (Kruse, 2015) in how organizations work with machines. In short, AI assists by providing predictive analytics, it augments by providing prescriptive analytics, and it substitutes human work by fully automating business activity (Lepenioti et al., 2019). It does take over knowledge work but it does so in unprecedented ways. Typical for software, AI operates “behind the scenes” (Jennings et al., 2014, p.85). Not only does its reasoning largely remain a black-box for its users. More often than not, users do not even notice their interactions with an AI, which is for example illustrated by the fact that an ordinary smartphone user is likely to have hundreds of thousands of server contacts per week (Hill, 2019). Protected from foreign eyes, AI uses its place in the cloud to learn. This is a new property for a machine. The learning takes place centrally but with the help of and in the presence of decentralized and massively parallel action. This is highly economical. AI is designed to be highly results-oriented.

A new type of actor who represents a general-purpose technology, who acts behind the scenes and who rapidly learns centrally based on decentralized activity: these are the ingredients for an economic pattern change that poses a substantial challenge to business leaders and to their organizations: How to adopt, co-operate but also compete against a technology that

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  interacts with business through an exponentially growing number of sensors and user interfaces, making it omnipresent,

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  pulls the strings together centrally in the cloud and without further eye-contact,

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  on each encounter puts more knowledge to use, and

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  operates more and more autonomously without taking breaks in a highly economical fashion?

Leading tech firms who are at the forefront of AI development for business purposes early on realized that with AI on board machines are no longer ‘handled’ but need to be ‘organized’ and ‘managed’. They identified the discipline of economics as a puzzle piece to fit in between computer algorithms and business processes and they started to hire economists (Athey & Luca, 2018). This serves to explain the effects of the deployment of AI and to develop constraints as well as incentives for machines to act, coordinate, and collaborate in desired ways. The Economics of Artificial Intelligence (Agrawal et al., 2019) have rapidly gained importance.