Book Review: “Power and Prediction”

Book Review: “Power and Prediction”

Book Review: “Power and Prediction”

How agile new businesses can benefit from their ability to harness the disruptive economics of artificial intelligence.

Not many authors start their new book with the honest admission that their previous book was fundamentally wrong. “We were wrong,” say Ajay Agrawal, Joshua Gans, and Avi Goldfarb in their foreword to “Power and Prediction” (Harvard Business Review Press, £22, ISBN 9781647824198), a compelling essay on the disruptive economics of artificial intelligence. But you can’t blame them for missing the mark in 2017’s ‘Prediction Machines’ – some might say they’re being too hard on themselves here – because their starting position was pretty strong: technologies they will always evolve, while being stable and reliable. the economy will obey the same rules it always has.

Again, to be fair, ‘Prediction Machines’ came out five years ago and a lot has happened in the AI ​​world since then. While the economic model the authors described ‘remains useful’, half a decade later AI has moved on. There is an emerging and critical new chapter in the history of technology to tell, say the authors, particularly related to fintech, pharmaceutical, automotive and retail businesses.

Because AI is a transformative technology, there is inevitably a phase between first realizing its potential and witnessing its widespread adoption. Here we are today, say the authors, who reveal an uneven timeline in which some industries integrate larger AI systems faster than others. These are the winners who gain the ‘power’ of the book title in their markets. The downside of this power is the ‘AI bug’ that can create resonant effects in supply chains from seemingly small movements upstream. The ‘anticipation’ part has more to do with the concept of ‘climbing’ an entrenched corporate culture from its pre-AI rule systems. We need to understand that there is uncertainty in the ecosystem as we create space for AI to do its job – which is essentially making predictions based on multiple combined decisions.

The authors claim that by quickly gaining an understanding of how and when to apply AI, younger organizations find themselves better able to gain a competitive advantage over older corporations that cannot shake themselves out of self-imposed inertia.

Where the economy kicks in is when replacing old systems rewards technological innovation. It’s a ‘fortune favors the bold moment’ because AI creates an advantage for early adopters as venture capitalists line up to invest in nimble start-ups that have bought into the AI ​​cred. Onlookers, weighed down by the fear that we are handing over power to the machine, miss the argument that a well-integrated AI leads to better decision-making while humans remain in control.

When it comes to the pervasive fear of AI bias, there was a lot of it before we came up with algorithms to help us detect and reduce it. Overall, Power and Prediction is a timely and detailed follow-up to Prediction Machines.

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