4. Summary
Guidance on risk assessment specific to the special characteristics of neural network software is required, and this is not presently available. General frameworks and taxonomies for software probabilistic risk assessment have been proposed, but they are not specific, nor applicable in some instances, to neural networks. This chapter, while limited in its applicability to every safety- and mission-critical neural network system, points out several possible risk assessment techniques as well as useful places to begin considering identification of risks and hazards.
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© 2006 Springer Science+Business Media, Inc.
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Pullum, L., Taylor, B.J. (2006). Risk and Hazard Analysis for Neural Network Systems. In: Methods and Procedures for the Verification and Validation of Artificial Neural Networks. Springer, Boston, MA. https://doi.org/10.1007/0-387-29485-6_3
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DOI: https://doi.org/10.1007/0-387-29485-6_3
Publisher Name: Springer, Boston, MA
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