Deep Learning and the Innovator's Dilemma
This article was originally published on deeplearningweekly.com
Mostly everyone seems to agree that AI, carried by a wave of deep learning breakthroughs, will 'disrupt' industries left and right. Of course, the term disruption is often somewhat carelessly and imprecisely bandied about to refer to technological or business model innovations that threaten industry incumbents. But what exactly enables an innovation to be disruptive given the fact that incumbents, generally, have both the know-how (in fact they are often the source of the innovation) and the resources to get a head start on any entrant is often glossed over.
Before we turn to the case of disruption through deep learning innovations, let us briefly explore an answer to this question presented by Clay Christensen and his seminal thesis on the Innovator's Dilemma. The central thesis is that incumbent firms operate in a certain context of customer needs, suppliers, target markets and competitors that form a value network which sets the standard of value for any strategy or business decision including where to allocate resources and which innovations to pursue. In practice this means that firms will often pursue sustaining innovations, that is innovations which improve and sustain the firm's position within the established value network.
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