Knowledge quality assessment (KQA) has been developed in order to analyze the role of knowledge in situations of high stakes and urgency when characterized by deep uncertainty and ignorance. Governing coastal flood risk in the face of climate change is typical of such situations. These are situations which limit the ability to establish objective, reliable, and valid facts. This paper aims to identify the moral frameworks that stakeholders use to judge flood risk situations under climate change, and infer from these knowledge legitimacy criteria. Knowledge legitimacy, defined as being respectful of stakeholders' divergent values and beliefs, is one of the three broad quality criteria that have been proposed in order to assess knowledge quality in such situations; credibility (as scientific adequacy) and salience (relevance to the needs of decision makers) being the two others. Knowledge legitimacy is essentially the subject of a literature analyzing, ex-post (once knowledge has been deployed), how stakeholders' participation is a factor contributing to knowledge legitimacy. Very little is known about ex-ante characteristics (i.e.: that can be observed, determined, before knowledge is deployed) that would make some types of knowledge more legitimate (i.e., respectful of stakeholders' divergent values and beliefs) than others. We see this as a significant blind spot in the analysis of knowledge and its role under deep uncertainty. In this paper we posit that this blind spot may be addressed, in part. In order to achieve this we first identify the ethical frameworks that stakeholders use to judge a situation of risk under rapidly changing conditions. We then associate these ethical frameworks to characteristics of knowledge. We tested this conceptualization through a case study approach centered on flood risk on the French Atlantic coast. We have adopted a narrative approach to the analysis of two diachronic corpora consisting of interviews conducted in 2010–2012 (33 interviews) and 2020 (15 interviews). These were approached as narratives of a risk situation. We thematically coded these along themes considered as metanarratives. These metanarratives are associated with predefined (deontology, consequentialism, virtue ethics) and emerging (discourse ethics, connection ethics, and a naturalistic ethic) ethical theories. Our results show that, when faced with flood risks, stakeholders tell stories that mobilizes several metaethical frameworks as guiding principles in the form of both procedural and substantive injunctions. In order to respect what we interpret as manifestations of the moral stances of stakeholders, our results indicate that knowledge legitimacy may be assessed against the following criteria: lability, debatability and adaptability; degree of co-production invested; place-based approach; ability to include lessons that would be given by nature. The operationalization of these criteria is promising in a time when the knowledge that is used for decision making under certainty is increasingly contested on the ground of its legitimacy.
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Toward Hybrid Relational-Normative Models of Robot Cognition
Most previous work on enabling robots’ moral competence has used norm-based systems of moral reasoning. However, a number of limitations to norm-based ethical theories have been widely acknowledged. These limitations may be addressed by role-based ethical theories, which have been extensively discussed in the philosophy of technology literature but have received little attention within robotics. My work proposes a hybrid role/norm-based model of robot cognitive processes including moral cognition.
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- NSF-PAR ID:
- 10265915
- Date Published:
- Journal Name:
- ACM/IEEE International Conference on Human-Robot Interaction
- Page Range / eLocation ID:
- 568 to 570
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3434074.3446353
