No abstract

This paper brings together a multidisciplinary perspective from systems engineering, ethics, and law to articulate a common language in which to reason about the multi-faceted problem of assuring the safety of autonomous systems. The paper's focus is on the "gaps" that arise across the development process: the semantic gap, where normal conditions for a complete specification of intended functionality are not present; the responsibility gap, where normal conditions for holding human actors morally responsible for harm are not present; and the liability gap, where normal conditions for securing compensation to victims of harm are not present. By categorising these "gaps" we can expose with greater precision key sources of uncertainty and risk with autonomous systems. This can inform the development of more detailed models of safety assurance and contribute to more effective risk control.

In recent years, several new technical methods have been developed to make AI-models more transparent and interpretable. These techniques are often referred to collectively as ‘AI explainability’ or ‘XAI’ methods. This paper presents an overview of XAI methods, and links them to stakeholder purposes for seeking an explanation. Because the underlying stakeholder purposes are broadly ethical in nature, we see this analysis as a contribution towards bringing together the technical and ethical dimensions of XAI. We emphasize that use of XAI methods must be linked to explanations of human decisions made during the development life cycle. Situated within that wider accountability framework, our analysis may offer a helpful starting point for designers, safety engineers, service providers and regulators who need to make practical judgements about which XAI methods to employ or to require. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

The ethical and social implications of autonomous systems are forcing safety engineers and ethicists alike to confront new questions. This paper focuses on just one of these questions-moral responsibilitybringing together inter-disciplinary insights to an issue of growing public and regulatory concern. The central thesis is that, on a conception of moral responsibility that presupposes control, the increasing autonomy of systems prima facie diminishes the extent to which engineers and users can be considered morally responsible for system behaviour. This challenge to our normal attributions of moral responsibility as a result of autonomy has come to be known as the 'responsibility gap'. We provide a characterisation of the moral responsibility gap, which we argue has two dimensions: causal and epistemic. At the end of the paper we highlight considerations for future work.

Habitat loss is a serious issue threatening biodiversity across the planet, including coastal habitats that support important fish populations. Many coastal areas have been extensively modified by the construction of infrastructure such as ports, seawalls, docks, and armored shorelines. In addition, habitat restoration and enhancement projects often include constructed breakwaters or reefs. Such infrastructure may have incidental or intended habitat values for fish, yet their physical complexity makes quantitatively sampling these habitats with traditional gears challenging. We used a fleet of unbaited underwater video cameras to quantify fish communities across a variety of constructed and natural habitats in Perdido and Pensacola Bays in the central northern Gulf of Mexico. Between 2019 and 2021, we collected almost 350 replicate 10 min point census videos from rock jetty, seawall, commercial, public, and private docks, artificial reef, restored oyster reef, seagrass, and shallow sandy habitats. We extracted standard metrics of Frequency of Occurrence and MaxN, as well as more recently developed MeanCount for each taxon observed. Using a simple method to measure the visibility range at each sampling site, we calculated the area of the field of view to convert MeanCount to density estimates. Our data revealed abundant fish assemblages on constructed habitats, dominated by important fisheries species, including grey snapper Lutjanus griseus and sheepshead Archosargus probatocephalus. Our analyses suggest that density estimates may be obtained for larger fisheries species under suitable conditions. Although video is limited in more turbid estuarine areas, where conditions allow, it offers a tool to quantify fish communities in structurally complex habitats inaccessible to other quantitative gears.