Artificial Intelligence can do so much more. Why are we not letting it?

There was plenty of hype around electricity in the early years but not much to show for it.

Electricity revolutionised factory design. As the authors note: “Henry Ford could not have invented the production line for the Model T car with steam power. Only electricity, decades after its commercial promise was shown, could achieve that. Yes, Ford was a care entrepreneur, but he was largely a system solution entrepreneur. These system changes altered the industrial landscape. Only then did electrification show up in the productivity statistics.

Consider insurance. The business model here concentrates on calculating likely losses across the portfolio insured and then building in a margin to create profit. Premiums spread risk among the pool but in a relatively crude way. AI could in theory upend this model by incentivising risk reduction behaviours in a way not done now.

One solution is to borrow from the toolkit of the lean movement and introduce a blank canvas approach to business modelling, posing a lot of “what if?” type questions. Simulation can help here. It is possible to use digital assets, including digital twins of physical environments, to simulate different options and use AI to predict the outcome of each.

Take Google, for example. Because of the massive investment it has made in talent as well as data, it makes very accurate predictions about who wants what and when, which makes it an excellent targeted advertising platform. It has built-in feedback loops enabling it to see whether its predictions are accurate or not. If it finds it has made an error, it corrects the model for next time, which makes it difficult for competitors to compete.Fast feedback loops lead to races to market.

Gans and his co-authors write thoughtfully as well as insightfully about the possibilities of AI, but also see the challenges and maintain a healthy scepticism throughout the book.

Source: Tech Daily Report (techdailyreport.net)

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