Artificial Intelligence and Law

, Volume 14, Issue 4, pp 251–260 | Cite as

Suitable Properties for Any Electronic Voting System

  • Jean-Luc Koning
  • Didier DuboisEmail author


Numerous countries are heading toward digital infrastructures. In particular this new technology promises to help support methods for elections. However, one should be careful that such an infrastructure does not hinder the voting and representation issues. On the contrary, it should support those issues and help citizens have a clearer picture of the underlying mechanisms. This paper deals with the limits of voting procedures as they are described in classical collective choice theory and reflects on ways to aggregate electronic votes stemming from various individuals that would be at the same time democratic, decisive and rational which is not feasible when candidate rankings alone are taken into account. This paper shows how electronic voting procedures could improve the situation by introducing preference-based votes.

Key words

Arrow’s theorem electronic voting social choice theory 


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  1. Arrow, K. J. (1963) Social Choice and Individual Values. 2nd edn. Wiley, New YorkGoogle Scholar
  2. Blair D. H., Pollak R. A. (1982) Acyclic Collective Choice Rules. Econometrica 50: 931–943zbMATHCrossRefMathSciNetGoogle Scholar
  3. Blau, J. H. (1972) A Direct Proof of Arrow’s Theorem. Econometrica 40: 61–67zbMATHCrossRefMathSciNetGoogle Scholar
  4. Dubois D., Prade H. (1988) Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New YorkzbMATHGoogle Scholar
  5. Dubois, D. and Koning, J.-L. (1991) Social choice axioms for fuzzy set aggregation. Fuzzy sets and systems 43(3), 257–274Google Scholar
  6. Fung L. W., Fu K. S. (1975) An Axiomatic Approach to Rational Decision Making in a Fuzzy Environment. In Zadeh L. A., Fu, K. S., Tanaka, K. and Shimura, M. (eds), Fuzzy Sets and Their Applications to Cognitive and Decision Processes. Academic Press, New York 227–256Google Scholar
  7. Hansson B. (1969) Group Preferences. Econometrica 37: 50–54CrossRefGoogle Scholar
  8. Moulin, H. (1988) Axioms of Cooperative Decision-Making. Cambridge University Press, UKzbMATHGoogle Scholar
  9. Plaza, E. (2004). Technologies for Political Representation and Accountability. EU-LAT Workshop on e-Government and e-Democracy. Santiago, Chili, 99–107Google Scholar
  10. Silvert W. (1979) Symmetric Summation: A Class of Operations on Fuzzy Sets. IEEE Transactions on Systems, Man and Cybernetics 9: 657–669zbMATHMathSciNetCrossRefGoogle Scholar
  11. Yager, R. R. (1989). On the Logical Representation of Social Choice (Multi-agent Aggregation). Technical Report MII-811, Machine Intelligence Institute, Iona College, New Rochelle, NYGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Grenoble National Institute of TechnologyGrenobleFrance
  2. 2.Université Paul SabatierToulouseFrance

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