Managing Sources of Uncertainty in Utilizing AI in Development and Deployment of Safety-Critical Autonomous Systems Article Swipe
Robert A. Lowe
,
Maria Ulan
,
Thanh Bui
,
Ana Adell
,
Jokin Labaien
,
Axel Brando
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/icsa-c65153.2025.00079
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/icsa-c65153.2025.00079
The integration of AI into safety-critical autonomous systems faces critical challenges due to various probabilistic sources of uncertainty that affect system reliability and safety. In research carried out on the SAFEXPLAIN project, we propose an end-to-end framework that addresses three key sources of uncertainty: domain uncertainty, epistemic uncertainty, and aleatoric uncertainty. In this article we focus on a reference runtime architecture that attempts to map these sources of uncertainty onto supervisory monitoring modules dedicated to each uncertainty source. This is complemented by explainable AI (XAI)-facilitated data and model learning management strategies to minimize systematic errors and ensure that model predictions remain within the safe boundaries. While aleatoric uncertainty is irreducible, we consider techniques to mitigate it, while domain and epistemic uncertainties are reduced through targeted inter-ventions during development and monitored during deployment. The end-to-end framework's holistic design aims to manage residual uncertainties, significantly lowering the risk of hazards and accidents. In the context of this framework, we provide a walkthrough of our mapping of sources of uncertainty onto our reference architecture using a use case dataset (satellite images) and allude to XAI and uncertainty reduction techniques. This serves as a proof of concept of our approach to render AI models safe to use across related autonomous systems based use cases.
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- Type
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- Language
- en
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https://doi.org/10.1109/icsa-c65153.2025.00079Digital Object Identifier
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Managing Sources of Uncertainty in Utilizing AI in Development and Deployment of Safety-Critical Autonomous SystemsWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-03-31Full publication date if available
- Authors
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Robert A. Lowe, Maria Ulan, Thanh Bui, Ana Adell, Jokin Labaien, Axel BrandoList of authors in order
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https://doi.org/10.1109/icsa-c65153.2025.00079Publisher landing page
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greenOpen access status per OpenAlex
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https://doi.org/10.1109/ICSA-C65153.2025.00079Direct OA link when available
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0Total citation count in OpenAlex
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| abstract_inverted_index.focus | 55 |
| abstract_inverted_index.model | 87, 98 |
| abstract_inverted_index.proof | 190 |
| abstract_inverted_index.these | 65 |
| abstract_inverted_index.three | 39 |
| abstract_inverted_index.using | 171 |
| abstract_inverted_index.while | 116 |
| abstract_inverted_index.across | 203 |
| abstract_inverted_index.affect | 19 |
| abstract_inverted_index.allude | 179 |
| abstract_inverted_index.design | 136 |
| abstract_inverted_index.domain | 44, 117 |
| abstract_inverted_index.during | 126, 130 |
| abstract_inverted_index.ensure | 96 |
| abstract_inverted_index.errors | 94 |
| abstract_inverted_index.manage | 139 |
| abstract_inverted_index.models | 199 |
| abstract_inverted_index.remain | 100 |
| abstract_inverted_index.render | 197 |
| abstract_inverted_index.serves | 187 |
| abstract_inverted_index.system | 20 |
| abstract_inverted_index.within | 101 |
| abstract_inverted_index.article | 53 |
| abstract_inverted_index.carried | 26 |
| abstract_inverted_index.concept | 192 |
| abstract_inverted_index.context | 152 |
| abstract_inverted_index.dataset | 175 |
| abstract_inverted_index.hazards | 147 |
| abstract_inverted_index.images) | 177 |
| abstract_inverted_index.mapping | 162 |
| abstract_inverted_index.modules | 72 |
| abstract_inverted_index.propose | 33 |
| abstract_inverted_index.provide | 157 |
| abstract_inverted_index.reduced | 122 |
| abstract_inverted_index.related | 204 |
| abstract_inverted_index.runtime | 59 |
| abstract_inverted_index.safety. | 23 |
| abstract_inverted_index.source. | 77 |
| abstract_inverted_index.sources | 15, 41, 66, 164 |
| abstract_inverted_index.systems | 7, 206 |
| abstract_inverted_index.through | 123 |
| abstract_inverted_index.various | 13 |
| abstract_inverted_index.approach | 195 |
| abstract_inverted_index.attempts | 62 |
| abstract_inverted_index.consider | 111 |
| abstract_inverted_index.critical | 9 |
| abstract_inverted_index.holistic | 135 |
| abstract_inverted_index.learning | 88 |
| abstract_inverted_index.lowering | 143 |
| abstract_inverted_index.minimize | 92 |
| abstract_inverted_index.mitigate | 114 |
| abstract_inverted_index.project, | 31 |
| abstract_inverted_index.research | 25 |
| abstract_inverted_index.residual | 140 |
| abstract_inverted_index.targeted | 124 |
| abstract_inverted_index.addresses | 38 |
| abstract_inverted_index.aleatoric | 49, 106 |
| abstract_inverted_index.dedicated | 73 |
| abstract_inverted_index.epistemic | 46, 119 |
| abstract_inverted_index.framework | 36 |
| abstract_inverted_index.monitored | 129 |
| abstract_inverted_index.reduction | 184 |
| abstract_inverted_index.reference | 58, 169 |
| abstract_inverted_index.(satellite | 176 |
| abstract_inverted_index.SAFEXPLAIN | 30 |
| abstract_inverted_index.accidents. | 149 |
| abstract_inverted_index.autonomous | 6, 205 |
| abstract_inverted_index.challenges | 10 |
| abstract_inverted_index.end-to-end | 35, 133 |
| abstract_inverted_index.framework, | 155 |
| abstract_inverted_index.management | 89 |
| abstract_inverted_index.monitoring | 71 |
| abstract_inverted_index.strategies | 90 |
| abstract_inverted_index.systematic | 93 |
| abstract_inverted_index.techniques | 112 |
| abstract_inverted_index.boundaries. | 104 |
| abstract_inverted_index.deployment. | 131 |
| abstract_inverted_index.development | 127 |
| abstract_inverted_index.explainable | 82 |
| abstract_inverted_index.framework's | 134 |
| abstract_inverted_index.integration | 1 |
| abstract_inverted_index.predictions | 99 |
| abstract_inverted_index.reliability | 21 |
| abstract_inverted_index.supervisory | 70 |
| abstract_inverted_index.techniques. | 185 |
| abstract_inverted_index.uncertainty | 17, 68, 76, 107, 166, 183 |
| abstract_inverted_index.walkthrough | 159 |
| abstract_inverted_index.<p>The | 0 |
| abstract_inverted_index.architecture | 60, 170 |
| abstract_inverted_index.complemented | 80 |
| abstract_inverted_index.irreducible, | 109 |
| abstract_inverted_index.uncertainty, | 45, 47 |
| abstract_inverted_index.uncertainty. | 50 |
| abstract_inverted_index.uncertainty: | 43 |
| abstract_inverted_index.probabilistic | 14 |
| abstract_inverted_index.significantly | 142 |
| abstract_inverted_index.uncertainties | 120 |
| abstract_inverted_index.inter-ventions | 125 |
| abstract_inverted_index.uncertainties, | 141 |
| abstract_inverted_index.safety-critical | 5 |
| abstract_inverted_index.cases.</p> | 209 |
| abstract_inverted_index.(XAI)-facilitated | 84 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.236257 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |