Artificial Intelligence: When Machines Are Kinder Than Us

This column is for all those who prefer being human when it comes to negotiating a price or service. This group considers humans to be more resilient, more empathetic, and more willing to improvise in order to arrive at a just and balanced solution. This positive view of human judgment, in contrast to the brutal coldness of artificial intelligence, is being shattered as online services expand. Preferred by a generation whose approach is more transactional – I pay, so I have an expectation – which gives a reward for efficiency, preferably measurable.

The idea of ​​maximizing the “return on relationship” is crucial. In a highly competitive environment such as technology, it is rare for people to meet without an anticipation of transactions: a novice will look for more experience than to speed up their learning curve at a given point; He will accept senior on the basis of evaluating the return on time spent (this little kid can do something interesting, he’s worth an hour of my time). An astonishing study by Aaron Garvey (University of Kentucky), Taiwo Kim (Sydney University of Technology) and Adam Duhacek (University of Sydney) shed new light on this issue.

The researchers presented the groups with different scenarios based on the purchase of a concert ticket and an Uber ride. The same principle in both cases; Three prices are offered to guinea pig customers: one is cheaper than expected, the second is in line with their expectations, and the final offer is more expensive than expected. The central element of the study: Presentations are given in turns by a human called Alex, and through a robotic interface, a chatbot, responding to the metallic name “XT-1000”. Then they are asked about their opinion of the quality of interaction according to three criteria: Is the system good, selfish, and fair?

“For bad news, send an AI”

Conclusion: When faced with a disappointing price tag, it is the robot that is nonetheless seen as “more benevolent”, “less selfish” and “more fair”. Conversely, if the offered price of a concert ticket or Uber ride is, in the end, more exciting than expected, the opposite is true: a human being is seen as more altruistic and fairer in his offer. Hence the result (and title) of the study: “For bad news, send an AI, for good news, put a human.” It is clear that cognitive bias is favorable to machines, which are considered more impartial, and more prone to objective appreciation of issues, as opposed to biased, greedy and cunning human beings.

However, the conclusions of this study are unlikely to accelerate the deployment of robotic interfaces in interactions with the audience due to an element very poorly managed by digital interfaces: the exception. Admittedly, in the case of Uber for example, when it comes to integrating numerous and heterogeneous elements in a few milliseconds such as car availability in the area, traffic and weather and their changes in the next minutes or hours, AI is unbeatable. She knows how to take into account many factors and return them in the form of clear and unambiguous information (the price of a flight in VTC or a plane ticket).

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The exception is a nightmare for automated systems

But once one leaves a specific and known environment, everything becomes complicated; It is, for example, a banking bot, unable to understand a customer’s statement of a problem beyond his narrow field of knowledge. Getting out of a standardized environment and encountering exceptions is a nightmare for automated systems. This is the case with self-driving cars, for example: many computer science professionals believe that we may not, at least for the foreseeable future, see fully self-driving cars (so-called Level 5) on the roads or in cities. According to them, leadership is just a series of exceptions, which are not poorly managed by humans, through experience, adaptation, and infrastructure limitations, but which are impossible to design. In obscurity, the advantage remains, and for a long time, for the human being.



Nicolas Pozzo


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