Abstract
Classically, risk is characterised by a point value probability indicating the likelihood of occurrence of an adverse effect. However, there are domains where the attainability of objective numerical risk characterisations is increasingly being questioned. This paper reviews the arguments in favour of extending classical techniques of risk assessment to incorporate meaningful qualitative and weak quantitative risk characterisations. A technique in which linguistic uncertainty terms are defined in terms of patterns of argument is then proposed. The technique is demonstrated using a prototype computer-based system for predicting the carcinogenic risk due to novel chemical compounds.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
10 References
J. Adams. Risk. UCL Press, London, 1995.
J. Ashby. Benzyl acetate: from mutagenic carcinogen to non-mutagenic non-carcinogen in 7 years?. Mutation Res., 306:107–109, 1994.
J. Ashby and R.W. Tennant. Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP. Mutation Res., 257:229–306, 1991.
S. Benferhat, C. Cayrol, D. Dubois, J. Lang and H. Prade. Inconsistency management and prioritized syntax-based entailment. Proc. International Joint Conference on Artificial Intelligence’ 93, Chambery, France, 1993.
P. Brown. Quoted in Local Transport Today (30 October), 1991.
D.V. Budescu and T.S. Wallsten. A Review of Human Linguistic Probability Processing. Knowledge Engineering Review, 10:43–62, 1995.
R.L. Carter. Guidelines for the Evaluation of Chemicals for Carcinogenicity. London: HMSO, 1991.
D. Dubois and H. Prade. Non-standard theories of uncertainty in knowledge representation and reasoning. Knowledge Engineering Review, 9:399–416, 1994.
M. Elvang-Gøransson, P.J. Krause and J. Fox. Dialectic reasoning with inconsistent information. In: Heckerman, D. and Mamdani, A. (eds.), Uncertainty in Artificial Intelligence. Proceedings of the Ninth Conference, San Mateo Ca: Morgan Kaufmann, 1993.
J. Fox. Language, Logic and Uncertainty. Technical Report, Imperial Cancer Research Fund, London, 1984.
J. Fox. Three arguments for extending the framework of probability. In: Kanal L.H. and Lemmer J.F. (eds), Uncertainty in Artificial Intelligence, Elsevier Science Publishers B.V. (North-Holland), 1986.
J. Fox and P.J. Krause. Symbolic decision theory and autonomous agents. In: D’Ambrosio B.D., Smets P. and Bonissone P.P., Uncertainty in Artificial Intelligence, Proceedings of the Seventh Conference, San Mateo Ca: Morgan Kaufmann, 1991.
J. Fox, P.J. Krause and S.J. Ambler. Arguments, contradictions and practical reasoning. Proceedings of ECAI’ 92, John Wiley and Sons, 623–627, 1992.
J. Fox and P.J. Krause. Formal Definitions of Arguments and Cases. ICRF Technical Report, 1994.
P.J. Krause, J. Fox and P. Judson. An Argumentation Based Approach to Risk Assessment, IMA Journal of Mathematics Applied in Business and Industry, 5: 249–263, 1994.
P.J. Krause, S.J. Ambler, M. Elvang-Gøransson and J. Fox. A Logic of Argumentation for Reasoning under Uncertainty. Computational Intelligence, 11:113–131, 1995.
R.P. Loui. Defeat among arguments: a system of defeasible inference. Computational Intelligence, 3:100–106, 1987.
National Research Council. Risk Assessment in the Federal Government: Managing the Process. Washington DC: National Academy Press, 1992.
D. Nute. Defeasible Reasoning and Decision Support Systems. Decision Support Systems, 4:97–110, 1988.
S. Parsons. Normative argumentation and qualitative probability. Proceedings of the International Joint Conference on Practical Reasoning, Bonn, 1997.
D.L. Poole. On the comparison of theories: preferring the most specific explanation. Proc. IJCAI’ 85, Los Angeles, USA, 144–147, 1985.
Roy. Soc. Risk: Analysis, Perception & Management. London: The Royal Society, 1992.
D.M. Sanderson and C.G. Earnshaw. Computer Prediction of Possible Toxic Action from Chemical Structure; The DEREK System. Human & Experimental Toxicology, 10:261–273, 1991.
U.S. EPA. Guidelines for Carcinogen Risk Assessment. Federal Register, 51, 33991–34003, 1986.
U.S. FDA. General principles for evaluating the safety of compounds used in food-producing animals. Appendix 1. Carcinogen structure guide. Washington: U.S. Food and Drug Administration, 1986.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Krause, P., Fox, J., Judson, P., Patel, M. (1998). Qualitative risk assessment fulfils a need. In: Hunter, A., Parsons, S. (eds) Applications of Uncertainty Formalisms. Lecture Notes in Computer Science(), vol 1455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49426-X_7
Download citation
DOI: https://doi.org/10.1007/3-540-49426-X_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65312-7
Online ISBN: 978-3-540-49426-3
eBook Packages: Springer Book Archive