At the social level, understanding the scope of digitisation of information and its processing is a major issue in the world today. The last few decades have seen this digitisation bring about a multitude of technological advances, which have also facilitated the globalisation of relations in our society. We need to be conscious of our role as players in this increasingly digitalised society, where the knowledge drawn from information is increasingly large and, in many cases, ethically unacceptable.

Information and computing theories, together with data science and AI, are concerned with the specific study of data processing. At the same time, there is a great variety of fields, such as biology, ecology, health, linguistics, economics, sociology and physics. that also encounter multiple aspects relating to data and its processing. In his book ‘The Blind Watchmaker’, the British ethologist and biologist Richard Dawkins suggests: "If you want to understand life [...], think about information technology". Information is not something ethereal or immaterial. As the physicist Rolf Landauer pointed out, "information is physical" and its processing has energy costs that are not negligible. More and more scientists agree that the universe is made up of material, energy and information, “but it is the latter that makes it interesting” (César Hidalgo, ‘Why Information Grows’). During his inaugural lecture of scientific sessions for the academic year 1976-77 of the Catalan Society of Biology, a subsidiary of the Institute of Catalan Studies, Ramon Margalef (who in 1957 introduced the theory of information in ecology), began with these words: "Existing systems are made of matter, energy and information (or organisation). Form, information, is a concept with a long tradition behind it in philosophy. It was seen as something added to matter, which informs matter, to which it gives particular and local properties, that is, a structure. It is different from one piece of matter area to another and that makes the difference."

There are many questions opening up in current research that have their origins in the information-computing bionomial. For example, we wonder about the future based on the research carried out in relatively new disciplines such as information and quantum computing, genomics and big dates. At the presentation of the Big Bang Data exhibition (http://bigbangdata.cccb.org/, CCCB, Barcelona, 2014), we could read: "Are data the new oil, a source of potentially infinite wealth? Are they the ammunition that loads mass-surveillance arms? Or must they be, above all, an opportunity, a tool for knowledge, prevention, efficiency and transparency, a tool for constructing a more transparent and participatory democracy?” And they add: “The last five years have seen a broad awareness among the academic and scientific sectors, the authorities, companies and culture, of how generating, processing and, above all, interpreting data are radically transforming our society. We all generate data, from mobile devices, through sensors, social media, photographs and digital videos, records of purchase transactions and GPS signals. The novelty is that it is increasingly easy to store and process such huge amounts of data which are detecting patterns (of incidences, behaviour, consumption, votes, investments, etc.) This is changing completely and very quickly how we take decisions at all levels."

How is knowledge generated from data? "The huge quantity of data generated daily contain, more or less explicitly, an also huge and valuable amount of knowledge. Such knowledge ends up being the key to success in many environments of everyday life: it enables a business to know which products it has to promote according to the reactions of its customers in social networks; in the medical field it can assist diagnoses or in predicting the evolution of a pandemic; in designing transport routes it can be a determining factor for predicting traffic conditions during shipments etc. The process to turn data into knowledge is the object of study for data science” (University Master’s Degree in Data Science at the UdG: https://www.udg.edu/ca/masters-en-tecnologia/ciencia-de-dades). Computing is therefore tasked with transforming data into concepts that provide us with knowledge and allow us to take intelligent decisions. Artificial intelligence in particular is of great help in this task. Automatic-learning and optimisation algorithms are tools that suggest an answer to a question formulated on a volume and a complexity of data we would not be capable of processing by ourselves. 

On the other hand, the limits of what can and cannot be done with information present a great challenge we are all involved in. How can a responsible use of algorithms be guaranteed? Digital technologies can help to improve the quality of life of citizens, but also raise important questions in the area of privacy and equal opportunities. We need to foster new synergies so that information and computing are a tool of transformation towards a fairer, more equitable, more transparent and more participatory society.