What happens when AI reach the tipping point?

In the last few years we have seen that social change and consumption behaviour are often characterised by an extraordinary speed in spreading and are able to turn into global phenomena.
From a behavioural point of view, some trends, supported by powerful marketing strategies, have became viral and this feature is very timely and not casual.

The spread of a trend, whether it is fashion, entertainment or lifestyle, leads to intensify the activity of people in some specific areas, physical or virtual, concurrently increases the demand for products and services  connected  to that trend and also the spreading factor of the trend itself.
As Malcolm Gladwell explains in the book The tipping point, once reached the tipping point, you reach that threshold beyond which you can get an avalanche effect.

This phenomenon is evident in the biological processes of virus spread, but it is quite surprising that the phenomenon can be replicated, in almost identical ways, even in the real world especially if assisted by powerful marketing strategies.
When the demand for a service or product emerges massively, the efficiency of the process to access to those resources and services determines the tipping point of spreading and also determines the perceived quality of the service or product.

The gap between supply and demand is no longer an eligible cost as we are now in a time when it is possible to predict how demand will change over time and implement adaptive supply strategies. Predictive business strategies combined with a knowledge of the audience and its behavior are conditions that are determining the success of some realities and the disappearance of others from the market.
Knowing how to grasp, control and respond in a timely and automated way, to emerging questions or to the change in demand behaviour is one of the most important challenges for retail.

The automation of retail processes affects many aspects ranging from the retail and product experience to post-purchase phase and customer care.

Real-time audience analytics, digital shelf strips, interactive surfaces and touch-less interfaces: that’s the way is changing the approach to shape the retail experience.

Automated experiences and retail automation

Automated experiences and retail automation seems to be more and more applied to a wide range of products and services.
Radars, cameras, voice recognition and weight sensors are only some of the solutions adopted to acquire a deep knowledge about context and audiences. This means that control, categorise and analyse is a pattern to generate a chain of events predictable and measurable to perform the retail automation.

This may suggest that, in a daily regime of automated actions and responses,  in order to make the services efficient, there is a risk of making the human experience entangled or filtered though safe and performing.

Artificial intelligence and implications on behaviour and society

We might think that coding  experience in patterns recognisable also for artificial intelligence is leading us to adapt our language to facilitate and support this dialogue with machines. In order to make machine able to recognize and respond to simple or quite complex commands we must somehow transform verbal, gestural and vocal language into metalanguages able to be associated with information and translatable therefore in answers and results.

The integration between the digital and the real world is now fully in place and it is constantly evolving, moreover the training accelerated by the pandemic has produced a vast evangelization of the benefits brought by digitalisation and virtual transposition of some experiences.
It is beyond any doubt that, in emergency situations, digital and virtual are the preferred as well as reasonable way, but before handing over the experience to an automation lived in everyday life it is sensible to make some more reflection.

Pros and cons in experience automation

When the experience is automated by an efficient relationship of dialogue between machine and man the result can be certainly a benefit. These are situations where real-time information is required for efficient management of passenger traffic, situations where it is necessary to preserve specific environmental qualities or situations where it is necessary to reduce the presence of man or his impact on the environment.
Sharing information, acting in a procedural and collaborative way is something that can be reproduced or replicated by a machine and can bring obvious benefits.
Behaving with empathy is a precious attitude that can hardly be attributed to a machine.

When the experience becomes automated without a real pro-social aim presumably we are faced with a controlled and simplified experience moved by disparate purposes ranging from entertainment to pure distraction not properly useful for those who are experiencing it.

Wanting to add a provocative touch but not far from pure reality, we can say that automated experience can also have the purpose of generating data through people.
Such data, as a trace of people involvement become monetizable because these data have the intrinsic power to multiply exponentially on the basis of emotional factors.

And here we are at what may be considered, with discrete and desirable limits, not fully automatizable and that will always have a slight form of resistance to the most efficient prediction strategy: emotions, events, events, real life.



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