Modeling the Information Society as a Complex System

1. Modeling the Information Society as a Complex System Noemi L. Olivera GECSI-FCJyS-UNLP, Arg. Araceli N. Proto CIC, LSC-FI-UBA, Arg. Marcel Ausloos GRAPES-SUPRATECS, ULG, Belg. Scientific Cooperation Agreement CONICET-FNRS

2. WSIS Statement: • “We, the representatives of the peoples of the world, assembled in Geneva from 10-12 December 2003 for the first phase of the World Summit on the Information Society, declare our common desire and commitment to build a people-centred, inclusive and development-oriented Information Society, where everyone can create, access, utilize and share information and knowledge, enabling individuals, communities and peoples to achieve their full potential in promoting their sustainable development and improving their quality of life, premised on the purposes and principles of the Charter of the United Nations and respecting fully and upholding the Universal Declaration of Human Rights” • WSIS-03/GENEVA/DOC/4-E, 12 December 2003

3. Goals: • Intensive usage of ICT in daily life => • Information Society -IS- • as well as different problems => demand stable solutions • Therefore, certain policies are required • POLICY: a course of action or inaction chosen by public authorities to solve, in most cases, an interrelated set of problems • BUT

4. Issues: • Due to ICT, information is globally transmitted almost instantaneously. • Yet, different societies and cultures have different reactions to the information received and differenttimes to absorb it and implement its “value”. • So,policies to be applied should be carefully analyzed as they need to fill up at least two different issues: • (a) to be acceptable for any national society • (b) to be coherent with external conditions

5. Content: • This contribution is devoted to show how social, legal and ethical aspects of the IS can and should be analyzed using the concept of complex systems, as the IS has most of those systems properties, in the sense that societies and economies are interrelated in a nonlinear way and often self-organizing within some general constraints

6. Problems: • Two relevant problems regarding the IS are treated in this contribution: • (a) the Digital Divide -DD- and • (b) the Internet Governance -IG-

7. Data? • Both expressed through the perception of policy makers and social scientists • There is little data to be analyzed • In this context, data analysis followed by the construction of adequate physical models which are able to describe different future scenarios that can be further discussed, appear to be if not extremely relevant, very much rewarding

8. Part I The ‘Digital Divide’

9. The ‘Digital Divide’ • the world is divided between people who do and people who do not have access to ICT • the DD involves the gap between the educated and uneducated, between economic classes, and the more and less industrially developed nations • To sum up: A DUAL SOCIETY

10. Ising model approach to Digital Divide • Briefly, it is a lattice of sites (interpreted here as agents), each site can have two values (blue/cyan, +1/-1). • Neighboring sites have an energetic preference to have the same value. • The temperature is associated to the degree of interest or relevance concerning a given situation: • to be ‘in’ or ‘out’ of the IS. • The external field represents the applied policies. • Simulation method:C. Caiafa and A. Proto, International Journal of Modern PhysicsC17 (2006) 29-38

11. The initial situation Fig.2 Bidimensional plot showing initial situation/state of each agent. Blue dots are the ‘in’ agents (+1) and cyan the ‘out’ (-1) ones, as in the following draws. Fig. 1 Neighbor structure, each agent has eight neighbors with whom to interact.

12. Time evolution; no external field • Fig.3 Bidimensional plot showing the “stable” situation of each agent when there is no external field ( = without policies) • Fig.4 The number of ‘in’ and ‘out’ agents, plotted versus time/iteration

13. Applying an external field (H = 1, arbitrary units), that represents a certain policy • Fig.5 Bidimensional plot showing • the ‘’stable’’ situation of each agent • Fig.6 The number of ‘in’ and ‘out’ agents, plotted versus time/iteration

14. Finally, we apply a more adequate policy (external field H = 2 arbitrary units) • Fig.7 Bi-dimensional plot showing the ‘’stable’’ situation of each agent after a “long time” • Fig.8 The number of ‘in’ and ‘out’ agents, plotted versus time/iteration

15. Conclusions on DD • Numerical simulations of the Ising model shows that adequate policies drastically reduce the time required for the society to arrive at, almost all, ‘in’ agents. • In zero external field, a low number of agents shall be ‘in’; it takes a long time to reach a steady state • Thus in many situations (countries, regions, social groups), defined policies should be implemented in order to encourage people to move ‘in’ the Information Society.

16. Part II The ‘Internet Governance’

17. The regulation of the Internet • Internet, being a global network, should not be submitted to the national state regulation of each connected country • Neither should it be submitted to the national state regulation of one given country  • In fact, Internet would be an ideal example of an institution that can only be ruled by international law; … actually, it is not

18. Internet Governance : Government, Management? • The WSIS is committed to governance, a term that corresponds to the so-called post-modern form of economic and political organizations • Some authors maintain that the cyberspace shows a somehow feudal character that emerges from the hierarchical privatization of its government associated with the granting of Internet domains • ICANN, the gatekeeper of the Internet,leads the ‘de facto’ management of the net

19. Internet Governance Forum (IGF) • In the Tunis phase of the WSIS (Nov. 2005), governments asked the UN Secretary-General to convene a Forum, • with the mandate to discuss the main public policy issues related to Internet Governance in order to foster the Internet's sustainability, robustness, security, stability and development. • WSIS-05/TUNIS/DOC/6(Rev.1)-E • Inaugural Meeting, Athens, Nov. 2006 • Second Meeting, Rio de Janeiro, Nov. 2007

20. The regulation of the Internet • “The international management of the Internet should be multilateral, transparent and democratic” Therefore, it demands • “the full involvement of governments, the private sector, civil society and international organizations” (WSIS, Tunis Agenda, 2005, 29) • BUT

21. IGF Participants • Government Delegations • Private sector (‘Civil Society’?) • companies, • trade associations, • non profit organizations, fully committed to the Internet • Individuals • International Organizations • ENTITIES • ISOC Italy, SOTEL CHAD, NetTel@Africa, Telecom, … • GOVERNMENT ORGANIZATIONS • Norwegian Media Authority, IBGE (Instituto Brasileiro de Geografia e Estatística), …

22. IGF Participants: agents in the model • well-established in the Information Society agents: Old (O) STAKEHOLDERS • ICANN, software companies, Internet providers and NGO involved in the development of communications and the Internet. • These agents presently lead the ‘de facto’ management of the net • agents that are trying to find a seat in the IS Governance: New (N) PARTICIPANTS • ‘civil society agents’, like NGO, individuals, SME • can also include several governments

23. The IGF outcomes • Chairman’s Summary: • among several appeals to self-regulation and soft law instruments, a consistent demand of state regulations appears: • “There was a clear convergence of views that governments had an important role to play in creating a solid regulatory framework and making sure that the rule of law was well established and respected”. • Whose views? • In whose benefit has such a demand been posed?

24. Lotka-Volterra model I Modified version of the Lotka (Lotka, 1925) - Volterra (Volterra 1932) model applied to web site competition (Maurer and Huberman, 2000) and in hung scenarios in sociology (Caiafa and Proto, 2006). N differential evolution equations (Maurer and Huberman, 2000) : the time derivative of fi ;fi is the weight of the i-th agent opinion, at each time t, with summatoria the fi equal 1 (i, j = 0, 1, . . . , N).

25. Lotka-Volterra model II The parameters of the model: ai , the growth rate ofthe agenti, bi, the saturation value of the i-th agent. In order to introduce the ‘size’ of the agents, the growth rate parameter ai is taken as (Economo et al, 2005) : a : is the selection pressure constant and equal for all agents living in the same environment (here the IS) bi : reflects the inverse of agent competitiveness associated to the “cost to do something”(Porter, 1980).

26. Lotka-Volterra modelIII Competitiveness should be understood as the cost imposed to the agent’s ideas/interests to be accepted in the regulation of the Information Society. This simple modification of the growth makes it possible to take the agent’s ‘size’ into account in a simple way. We consider ten agents as an example; a = 1equal for all agents (ideally, all the agents have the same rights as regards the policies for the sustainability of the IS). Also for simplicity we keep bi = b = 1.

27. Lotka-Volterra modelIV We look at the evolution of and determine the long term weight fi(importance of its opinion) of the i-th agent. Simulations have been done for a situation where there are 40% of Old big-size agents (O) (bi= 0.10 to 0.13) 60% of Newsmall-size agents (N) (bi = 0.41 to 0.46). Initial conditions for both, the O- and N- agents : fi = 0.1. ij values are fixed = +/- 1. The O agents are in competition among themselves : ij sign is the same (positive = +1). The N agents cooperate (-1) or compete (+1); scenarios are determined through the numbers of identical ij signs: 0%, 40%, 66%, 100%.

28. Simulation Results 50% Coop 0 Coop 66% Coop 100% Coop

29. Governance problem Summary • Convergence of whose views? • for whose benefit? • As the simulation results show, there is a chance to achieve a scenario where, by means of cooperation between the Nagents, their demands are attended N.B.There are many weak agents among the N, but there is also China, Brazil and some relevant independent NGO.

30. Conclusion on IG • Through the L-V multiagent model, we arrive at the conclusion that to attain an active role in the Information Society, and therefore participate in policy decisions, Nagents should cooperate among themselves • There is even some indication of the order of magnitude of the number of necessarily cooperating N agents in order to overthrow the O opinion/attitude and how long it takes

31. CONCLUSIONS • We are handling with problems where there is little data to be analyzed • In both DD and IG cases simulation results lead to predictions which are clearly equivalent to the consequences that some social scientists have forecasted, in terms of theoretical explanations of phenomena that are actually comparable to those that are taking place within the Information Society. • The modelization of the Information Society as a complex system provides insights about how the Digital Divide can be reduced and how the huge majority of ‘weak’ members of the IS would influence the outcomes of the IG and, in so doing, allow the Internet Governance to “be multilateral, transparent and democratic”. • In fine, physics-like models appear to be if not extremely relevant, very much rewarding