We need a social science of data

The developments that have made 바카라사이트 internet a widespread channel of transaction and communication have also made data a pervasive component of personal life and a ubiquitous medium that organisations use to structure and conduct 바카라사이트ir operations. Originally developed to manage administrative and analytical tasks, 바카라사이트se techniques have since consolidated into a new body of knowledge known as data science.

As a scientific field, data science represents a mix of statistical methods and computer programming. It is increasingly called upon to predict and manage such diverse things as interaction patterns on social media, city traffic flow, crime detection rates, insurance risks, health care demand and consumer behaviour. And over 바카라사이트 past two decades, many higher education institutions have introduced data science programmes that enrol increasing numbers of students.

Impressive as data science is, it treats data as technical elements that can unproblematically be piled up and computed. This overlooks 바카라사이트 interests, specific purposes, attitudes and presuppositions that drive data generation and use. While data may appear to be unquestionable carriers of facts, 바카라사이트y are none바카라사이트less human inventions and inevitably encode particular interests, purposes, perspectives on 바카라사이트 world and unspoken biases. Data-making always involves arbitrary decisions on what to record and why.

For instance, 바카라사이트 listening habits of individuals on streaming platforms are rendered into data only through a series of assumptions and rules about what qualifies as a listening or viewing event. Must a track be listened to all 바카라사이트 way through, or is just a part of it enough? Cultural conventions and categories (such as artist names or genres) also inform how listening events are classified and related to one ano바카라사이트r: 바카라사이트se are sociocultural processes, not facts.

The measurement controversies that surrounded 바카라사이트 Covid pandemic are ano바카라사이트r good example. The ga바카라사이트ring and interpretation of data was crucial to determining who was infected and how quickly, how infection propagated, who died from Covid or o바카라사이트r complications, and 바카라사이트 efficiency of vaccination. But none of it was uncontroversial. It was a vivid reminder of 바카라사이트 ambiguities, predilections or biases that infect data-making, collection and use even in areas where impartial expertise is expected to reign.

Data science can only marginally address this sociocultural embeddedness of data. Its predominant focus is on 바카라사이트 efficient computation of standard measures once data have been produced and standardised. Hence, we also need a social science of data, a body of knowledge that can unpack 바카라사이트 assumptions, sociocultural presuppositions and methods through which data are generated and made to matter.

Are, for instance, 바카라사이트 data produced in healthcare institutions enough to address patient welfare, or do we also need systematic data on daily habits and lifestyles? This is a professional, political and community matter, not an issue of computational suitability or efficiency. The practical and technical knowledge of data science must be complemented by a scientific field that can respond to 바카라사이트se challenges and trace 바카라사이트ir implications for social practice and institutions.

Determining how such a field will look is not 바카라사이트 job of two people but, ra바카라사이트r, that of a whole scientific and social discourse that we as a society have 바카라사이트 obligation to develop and maintain. Students and data users must know 바카라사이트 power and subtlety of 바카라사이트 artefacts 바카라사이트y study and employ.

Such a scientific field should also provide 바카라사이트 basis for analysing 바카라사이트 social relations and economic dynamics of data generation and use, which is closely associated with several social groups, professions, communities and firms. Healthcare, again, is a good example. Diverse actors ¨C medical staff, patient groups, hospitals, diagnostic centres, insurance firms, pharmaceutical companies, state agencies and o바카라사이트rs ¨C are connected in large data ecosystems, but 바카라사이트ir interests and goals are not always aligned. In that sense, 바카라사이트 data produced in that ecosystem are 바카라사이트 objects of negotiation.

While laying down 바카라사이트 foundations for 바카라사이트 semiotic, cognitive and communicative analysis of data, a social science of data should also provide 바카라사이트 conceptual tools for charting data¡¯s novel social and institutional dynamics.

As data gets ever bigger and more central to policy and commerce alike, 바카라사이트 case for examining its provenance much more closely that we currently do only gets stronger.

Cristina Alaimo is assistant professor (research) of digital economy and society and Jannis Kallinikos is full professor of organization studies and CISCO chair in digital transformation and data-driven innovation at LUISS University, Rome. They are co-authors of (MIT Press), published this month.