95 research outputs found
Artificial intelligence in health care: accountability and safety
The prospect of patient harm caused by the decisions made by an artificial intelligence-based clinical tool is something to which current practices of accountability and safety worldwide have not yet adjusted. We focus on two aspects of clinical artificial intelligence used for decision-making: moral accountability for harm to patients; and safety assurance to protect patients against such harm. Artificial intelligence-based tools are challenging the standard clinical practices of assigning blame and assuring safety. Human clinicians and safety engineers have weaker control over the decisions reached by artificial intelligence systems and less knowledge and understanding of precisely how the artificial intelligence systems reach their decisions. We illustrate this analysis by applying it to an example of an artificial intelligence-based system developed for use in the treatment of sepsis. The paper ends with practical suggestions for ways forward to mitigate these concerns. We argue for a need to include artificial intelligence developers and systems safety engineers in our assessments of moral accountability for patient harm. Meanwhile, none of the actors in the model robustly fulfil the traditional conditions of moral accountability for the decisions of an artificial intelligence system. We should therefore update our conceptions of moral accountability in this context. We also need to move from a static to a dynamic model of assurance, accepting that considerations of safety are not fully resolvable during the design of the artificial intelligence system before the system has been deployed
Moral responsibility for unforeseen harms caused by autonomous systems
Autonomous systems are machines which embody Artificial Intelligence and Machine Learning and which take actions in the world, independently of direct human control. Their deployment raises a pressing question, which I call the 'locus of moral responsibility' question: who, if anyone, is morally responsible for a harm caused directly by an autonomous system? My specific focus is moral responsibility for unforeseen harms.
First, I set up the 'locus of moral responsibility' problem. Unforeseen harms from autonomous systems create a problem for what I call the Standard View, rooted in common sense, that human agents are morally responsible. Unforeseen harms give credence to the main claim of ‘responsibility gap’ arguments – that humans do not meet the control and knowledge conditions of responsibility sufficiently to warrant such an ascription.
Second, I argue a delegation framework offers a powerful route for answering the 'locus of moral responsibility' question. I argue that responsibility as attributability traces to the human principals who made the decision to delegate to the system, notwithstanding a later suspension of control and knowledge. These principals would also be blameworthy if their decision to delegate did not serve a purpose that morally justified the subsequent risk- imposition in the first place. Because I argue that different human principals share moral responsibility, I defend a pluralist Standard View.
Third, I argue that, while today’s autonomous systems do not meet the agential condition for moral responsibility, it is neither conceptually incoherent nor physically impossible that they might. Because I take it to be a contingent and not a necessary truth that human principals exclusively bear moral responsibility, I defend a soft, pluralist Standard View.
Finally, I develop and sharpen my account in response to possible objections, and I explore its wider implications
A new ERA? Electronic records in ambulances: a research programme.
In order to support the continued shift to out of hospital care, ambulance clinicians need to be able to decide which patients will benefit from being left at home, refer to alternative care providers, and ensure that appropriate patient information is passed on to them. Technology can help in a number of ways. Firstly, apps and referral tools can aid decision-making at the scene. Secondly, technology can facilitate the transfer of patient information to ambulance clinicians at the scene or even before arrival, e.g. by sharing information on past contacts with a GP, or on a DNACPR directive. Thirdly, it can support real time remote sharing of information so that, for example, an ED consultant can advise about the appropriate conveyance and care decisions while the patient is still at home. Fourthly, it can support the easy transfer of patient information to other care providers like GPs. Finally, electronic records can make data more readily available for audit, research and evaluation (Morrison et al., 2014). Data can be used in future research to inform service improvements, as well as providing ambulance services with a valuable store of information to run automated clinical and management reports, as well as defending against medico-legal action
Safe, Ethical and Sustainable : Framing the Argument
The authors have previously articulated the need to think beyond safety to encom-pass ethical and environmental (sustainability) concerns, and to address these concerns through the medium of argumentation. However, the scope of concerns is very large and there are other challenges such as the need to make trade-offs between incommensurable concerns. The paper outlines an approach to these challenges through suitably framing the argument and illustrates the approach by considering alternative concept designs for an autonomous mobility service
Recent climate-driven ecological change across a continent as perceived through local ecological knowledge
Documenting effects of climate change is an important step towards designing mitigation and adaptation responses. Impacts of climate change on terrestrial biodiversity and ecosystems have been well-documented in the Northern Hemisphere, but long-term data to detect change in the Southern Hemisphere are limited, and some types of change are generally difficult to measure. Here we present a novel approach using local ecological knowledge to facilitate a continent-scale view of climate change impacts on terrestrial biodiversity and ecosystems that people have perceived in Australia. We sought local knowledge using a national web-based survey, targeting respondents with close links to the environment (e.g. farmers, ecologists), and using a custom-built mapping tool to ask respondents to describe and attribute recent changes they had observed within an area they knew well. Results drawn from 326 respondents showed that people are already perceiving simple and complex climate change impacts on hundreds of species and ecosystems across Australia, significantly extending the detail previously reported for the continent. While most perceived trends and attributions remain unsubstantiated, \u3e35 reported anecdotes concurred with examples in the literature, and \u3e20 were reported more than once. More generally, anecdotes were compatible with expectations from global climate change impact frameworks, including examples across the spectrum from organisms (e.g. increased mortality in \u3e75 species), populations (e.g. changes in recruitment or abundance in \u3e100 species, phenological change in \u3e50 species), and species (e.g. \u3e80 species newly arriving or disappearing), to communities and landscapes (e.g. \u3e50 examples of altered ecological interactions). The overarching pattern indicated by the anecdotes suggests that people are more often noticing climate change losers (typically native species) than winners in their local areas, but with observations of potential ‘adaptation in action’ via compositional and phenological change and through arrivals and range shifts (particularly for native birds and exotic plants). A high proportion of climate change-related anecdotes also involved cumulative or interactive effects of land use. We conclude that targeted elicitation of local ecological knowledge about climate change impacts can provide a valuable complement to data-derived knowledge, substantially extending the volume of explicit examples and offering a foundation for further investigation
Physical Activity Behavior in Persons with Parkinson’s Disease
Parkinson’s Disease (PD) is the second most common neurological disorder affecting the musculoskeletal function, respiratory function, and laryngeal function. Despite these dysfunctions, persons with PD (PwPD)are still able to positively adapt to exercise training. PURPOSE: The purpose of this study is to investigate changes in physical activity (PA) in PwPD that participate in a long-term boxing training program designed for PwPD. This is a 1-month, preliminary analysis of a larger 12-month longitudinal pilot study. METHODS: Each participant (n=6) will complete a total of 104, 1-hour boxing training session, over the course of 12 months. Prior to participation in the training program and at five timepoints during training (1, 2, 3, 6, and 12 months), participants will complete a self-report survey related to PA behavior (International Physical Activity Questionnaire; IPAQ). This preliminary report is a description of PA changes between baseline and 1-month of intervention. RESULTS: One participant had to discontinue participation in the boxing program so results are based on n=5. Vigorous intensity PA activity increased in 2 participants and decreased in 3 participants resulting in an average of -19 minutes of vigorous PA/person/week. Moderate intensity PA activity increased in 3 participants and decreased in 2 participants resulting in an average of +28 minutes of moderate intensity PA/person/week. Walking time increased in 3 participants and decreased in 2 participants resulting in +14 minutes of walking time/person/week. Sitting time increased in 2 participants and decreased in 3 participants resulting in -25 minutes of sitting time/person/week. CONCLUSION: While data collection for this study is preliminary, promising trends of improved PA behavior (increased PA minutes and decreased sitting minutes) are encouraging. If trends of improved PA behavior are realized over the entirety of this study (12 months), we expect to see other positive neurological outcomes that are also being analyzed in these study participants
AI Explainability: The Technical and Ethical Dimensions
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’
Underwater Video as a Tool to Quantify Fish Density in Complex Coastal Habitats
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
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