• Automated World
• Capital-Labor Collaboration
• Human Behaviour
• AI
• Robots
• Algorithm adversion

Given the great development of new technologies in the last decade, it is important to analyse how industries today have organized themselves. This thesis proposes in the first chapter an explanation of how industry today should be analysed by explaining that the old utility function of classical economics is no longer correct, as it imposes a static a view of technology in relation to human labor. Today, in fact, more than ever the synergy between labor and capital, that is, the work done by human beings and the work done by machines, should be at the centre of every industry. Labor and capital should be left free to exchange tasks and not having a rigid imposition on the tasks to be done. Here this thesis in fact questions how these exchanges should take place and when.
An important look, to justify the changes that should be taken into account when evaluating businesses today, is the trend of reliance of different tasks divided between Labor and Capital. Observations on real data are considered between the late 1900s and the first decade of the 2000s. Researching for some trend of association between the different types of tasks, to try to predict what will happen in the future.
To talk about our days the following thesis tries to show, through statistical data, from IFR (International Federation of Robotics) which countries in the world are applying robotic enterprise and which market sectors are leveraging these new technologies the most.
Thanks to this data base we can understand the historical evolution that industrial automation has undergone.
Particular attention will then be paid to artificial intelligence, one of the greatest information technology innovations we have today.
Artificial intelligence is an automatic algorithmic process that allows decisions to be processed without the need for human intervention. AI uses data, statistics, or computing resources to make these decisions. Artificial intelligence is often applied to machinery in industries because it allows organizations to rely on algorithmic decisions. AI-equipped robots can be brought into the production cycle without prior programming; in fact, they learn in the field by taking advantage of a variety of sensors and computing and analytical units.
Whereas in a machine without AI human decides the factors that must be considered or not to undertake a production process, in a machine with AI it is the algorithm that makes the decisions, decides the input factors and processes the outputs, based on the patterns discovered by itself.
The application of artificial intelligence to machinery enables many organizations to optimize their business, optimization both from a production standpoint, such as speed or accuracy of production, but also from a cost standpoint.
We are going also to investigates what happens in the financial sector, a sector that has always been a pioneer in the application of new technologies.
Again, this could lead to benefits as algorithms are able to process and analyse data on a scale far beyond human capabilities.
Machine learning algorithms and neural networks are able to extract hidden patterns and relationships within large datasets, revealing valuable insights that might otherwise be missed.
One important example the paper reports is that of AI consultants in banks.
At the basis of economic theories there is always as a human subject the "Homo economicus," that is, the one who is able to make rational decisions under uncertainty, maximize the return for a given risk, try to minimize risk, etc... in reality, as noted in the paper with the study by Amos Tversky and Daniel Kahneman, people do not make decisions based on reasoning but often get carried away by emotions and various cognitive biases, which cause their investment decisions to be irrational choices. The solution to this proposed by the thesis could be the Artificial Intelligence Consultant.
In the end, we will go on to answer why, despite all the benefits that artificial intelligence could bring to industries, it is not being fully applied. We will try to understand what factors influence people's aversion to artificial intelligence.