Walking Finelines between Law and Computational Social Science

• Autore: Sebastiano Faro, Nicola Lettieri
• Pagine: 9-24

Walking Finelines between Law

and Computational Social Science

SEBA STI ANO FARO , NIC OLA LE TT IER I∗

“Computational social science” entries in Google N-gram Viewer from 1985 to2008

1. Four years ago, “Science” published a position paper on the emergence

of a new research paradigm – computational social science – destined to have

a profound impact on social sciences1.

The authors, 15 leading scientists coming from strongly diversif‌ied disci-

plinary spheres, from physics to economics, begin with the observation of a

phenomenon that is a fundamental characteristic of the information society:

“we live life in the network”, each transaction that occurs in the network

“leaves digital traces that can be compiled into comprehensive pictures of

both individual and group behaviour, with the potential to transform our

understanding of our lives, organizations, and societies”2.

∗S. Faro is senior researcherat the Institute of Legal Information Theory and Techniques,

National Research Council of Italy (ITTIG-CNR), Florence; N. Lettieri, researcher at

ISFOL, Rome, is adjunct professor of Legal informatics at the University of Sannio, Be-

nevento (Italy) and of Computational social sciences at theDepar tment of Computerscience

of the University of Salerno (Italy).

1D. LAZE R, A. PEN TLA ND, L. ADA MIC , S. ARAL , A.-L. BARA BÁSI , D. BREWER, N.

CHRI STAK IS, N. CO NTRAC TOR, J. FOWLE R, M. GUT MAN N, T. JEBAR A, G. KIN G, M.

MACY, D. ROY, M. VAN ALSTYN E,Computational Social Science, in “Science,” Vol. 323,

2009, n. 5915, pp. 721-723.

2Ivi, p. 721.

“Informatica e diritto”, Vol. XXII, 2013, n. 1

XXXIX annata - Seconda Serie - Fasc. monografico - S. Faro, N. Lettieri (a cura di), "Law and Computational Social Science", ESI, Napoli, 2013, 352 p.

10 Informatica e diritto /Law and Computational Social Science

In their view, the capacity of new technologies to collect and analyse

massive amounts of data is bound to play a fundamental role in the future of

science.

The position of the authors demonstrates that social sciences are going

through a phase of profound change due to two main factors. Firstly, there

is resort to computational tools and approaches: understanding social phe-

nomena means increasingly using statistical and analytical tools, exploiting

data mining techniques, running simulation models or, in other words, ex-

ploiting the power of computation3. Secondly, there is integration, enabled

by computational tools, among different disciplines and sciences, a process

that is involving differentareas of social sciences from economics to political

science, from sociology to anthropology.

The scenario in which the article in “Science” is inserted is that of the ever

increasing availablity of information in electronic formatregarding the most

varied aspects of reality4. The so-called “Data Deluge”5is at the basis of inno-

vative scientif‌ic research practices rich in implications of an epistemological

nature6in which scientif‌ic progress is mainly the fruit of the application of

3See I. AYRES,Super Cr unchers: Why Thinking-By-Numbers Is the New Way ToBe Smart,

New York,Bantam Dell., 2007, and the review by E.K. CHE NG,Will Quants Rule the (Legal)

World?, in “Michigan Law Review”,Vol. 107, 2009, pp. 967-978.

4According to a recent estimate, in 2011 only, humanity has overall produced morethan

1,200 billion gigabytes of information compared to 125 billion producedin 2005.

5The data deluge is central to a consideration, originating in the scientif‌ic domain, that

(see, among others, T. HEY, A. TREF ETHE N,The Data Deluge: An e-Science Perspective, in

Berman F., Fox G., Hey A. (eds.), “Grid Computing - Making the Global Infrastructure a

Reality”, Chichester, Wiley and Sons, 2003, pp. 809-824 and Nature of 4 September 2008,

which dedicated its cover to so-called “Big data”, Big Data, Science in the petabyte era) has

come to the attention of the non specialised public, as the cover and thear ticles dedicated to

it in the Economist of 27 February 2010 show.

6In a provocativear ticle of 2008, American physicist and essayistChr is Anderson argues

the science that is the descendant of Data Deluge, so-called “Big Data Science”, is making

scientif‌ic method obsolete: “Sensors everywhere. Inf‌inite storage. Clouds of processors.

Our ability to capture, warehouse, and understand massive amounts of data is changing sci-

ence [...]faced with massive data, this approach to science – hypothesize, model, test – is

becoming obsolete [...]There is now a better way. Petabytes allow us to say: ‘Correlation

is enough.’ We can stop looking for models. We can analyze the data without hypotheses

about what it might show. We can throw the numbers into the biggest computing clusters

the world has ever seen and let statistical algorithms f‌ind patterns where science cannot” (C.

ANDE RSO N,The End of Theory: The Data Deluge Makes the Scientif‌ic Method Obsolete, in

“Wired Magazine”, 2008, http://www.wired.com/science/discoveries/magazine/16-07/pb_

theory). Particularly interesting, on this matter, see also T. HEY, S. TANSL EY, K. TOLL E,