Università Roma Tre

The course is dedicated to the birth of Artificial intelligence which happened more or less together witht the birth of the first electronic computers. The term was invented in 1956, but the discussion around the possibilities and consequences of what was called mechanical or machine intelligence started during the early Fifties and even earlier.
The Famous Turing Test created a huge interest since it was invented and proposed in 1950 by Alan Turing. Many years and many different methods were considered since AI origins, now many perspectives and technologies changed since then, in order to solve problems that required intelligence and problem solving capabilities to be solved.
At present there are many soft bots, many robot and many artificial devices that with the help of algorithms seem to espress intelligence and oblige us to change the concept of intelligence itself, both if applied to humans or to machines.
the most interesting phenomenon is the tendence to attribute to machine intelligent capabilities, mainly when we don't know precisely how the machine works.
This social dimention in attributing intelligence to machines was underlined by Turing too at the very beginning of machine intelligence reflection.
However this characteristic risks to produce unintendend and undesired consequences for human beings. we know that not many ara capable of understanding how to program a deep learning algorithm, and that more and more even programmers ignore how the machine produced the output results, because the layers of calculations are too difficult to follow in details also by those who programmed them. We know that only a small group of programmers and experts know the details. they tend to be trained by the same universities and to be hired by the same few multinational companies.
the technics that are more successful in AI are the machine learning programs, that build theri previsions on the manipulation of past series of data. Between the machine learning solutions the most relevant at present are the deep learning techniques. Deep learning solutions are based on multilevel layers of learning networks, in which the nobody knows what is happening inside the hidden layers. the programmers don't know precisely the reasons behind the output of the neural network to a specific problem. In some context particularly sensitive such as predictive policing, face recognition, image recognition, clusterization, risk assessment in recidivism, personnel selection, insurance premiums, welfare services ect. it is difficult to make previsions, because the structural incertitude of the future events. In these situations the strength of rhetoric about the trustworthy of algorithmic devices risk to create self-fulfilling expectations that transform the world according to previsions that are not right or wrong. the future in created by anticipating it.
The introduction of generative AI creates additional problems in terms of the controllability of the veracity of the responses obtained from the various CHATGPT and other similar intelligent chats. The risk is to have a proliferation of content without control that could make it impossible to use textuality to validate knowledge and transmit it. We are facing a momentous change that requires extreme attention to the protection of the rules of peaceful coexistence based on justice, fairness and freedom that we have shared in the countries of advanced democracies.
This framework shows that there are political and social problems that need solutions when we introduce a new AI tool. Innovation is not enough we need to build tools that are fair and useful to promote the development and wellbeing of all humans and not only of a small minority.
the course proposes some histories and methods to understand the political and social dimensions of the technological choices around us, with special regard to AI.

Mitchell M. (2019) Artificial Intelligence, Pelican Press, London.
Copeland J. (2004) The essential turing, Clarendon Press, London (a selection of pages)
Natale S. Deceitful media, Oxford university Press, Oxford.