Boris Babic,I Glenn Cohen,Julian Savulescu
Boris Babic
As artificial intelligence and machine learning (AI/ML) systems become increasingly pervasive in society, their opacity-i.e., the difficulty, and sometimes impossibility, of understanding why they make the decisions they make-has become a s...
AI ethics through a decolonial lens: what does AI ethics look like if we take seriously the push to decolonise it? [0.03%]
从去殖民视角看人工智能伦理：如果我们认真对待推动人工智能“去西方中心化”的努力，我们该如何看待人工智能伦理？
Selena Nemorin,Beatrice Bonami
Selena Nemorin
This paper offers an exploratory examination of the emerging discourse and practices on decolonising AI ethics. Whilst the field of AI ethics has made substantial progress in proposing normative frameworks for responsible innovation, these ...
Hannah S Piehl,Ricky Janssen,Bart Penders et al.
Hannah S Piehl et al.
Artificial intelligence (AI) is often presented as a transformative technology for healthcare, promising to augment clinical decision-making, streamline workflows, and enhance diagnostic precision. Yet its integration into healthcare practi...
The ethics in sustainable AI: a scoping literature review on normativity in the academic discourse on the environmental sustainability of AI [0.03%]
可持续AI伦理：学术界关于AI环境可持续性规范性的综述研究
Olya Kudina,Nynke van Uffelen,Lode Lauwaert et al.
Olya Kudina et al.
AI is developing rapidly, as are concerns about the environmental impact of its training and deployment. Studies about the environmental sustainability of AI have begun to emerge in the past five years, stressing the need for critical refle...
Beyond the algorithm: rethinking the network account of trustworthy ai through lexical threshold-based multidimensional utility analysis [0.03%]
超越算法：通过基于词典阈值的多维效用分析重新思考网络信任worthy AI的账户
Fei Song,Julian Savulescu,Michael Dunn
Fei Song
In this paper, we present an overview of the main conceptual framework for trustworthy AI and argue that the network account offers a superior alternative. We identify and illustrate the possible nodes within an AI network, specify the key ...
Realising the digital twin: a thematic review and analysis of the ethical, legal, and social issues for digital twins in healthcare [0.03%]
实现数字孪生：医疗保健领域数字孪生的伦理、法律和社会问题的主题性回顾与分析
Christopher David Burr,Shuang Qian,Peter Winter et al.
Christopher David Burr et al.
This paper examines ethical, legal, and social issues (ELSI) associated with healthcare digital twins (DTs). Using a systematic thematic analysis, we identify key themes across ethical, legal, and social categories, as well as practical bar...
'We can see a savage': a case study of the colonial gaze in generative AI algorithms [0.03%]
“我们可以看到一个野蛮人”：生成式人工智能算法中的殖民凝视案例研究
Arsenii Alenichev,Jonathan D Shaffer,Patricia Kingori et al.
Arsenii Alenichev et al.
Theorizing the failures of computer vision algorithms requires shifting from detecting and fixing biases towards understanding how algorithms are shaped by social, historical, and political real-world precursors. To better understand the so...
Understanding AI and power: situated perspectives from Global North and South practitioners [0.03%]
理解人工智能与权力：来自北方和南方实践者的视角
Venetia Brown,Retno Larasati,Joseph Kwarteng et al.
Venetia Brown et al.
Global debates on artificial intelligence (AI) ethics and governance remain dominated by high-income, AI-intensive nations, marginalizing perspectives from low- and middle-income countries and minoritized practitioners. This qualitative stu...
A rapid evidence review of evaluation techniques for large language models in legal use cases: trends, gaps, and recommendations for future research [0.03%]
大型语言模型在法律用例中的评估技术快速证据审查：趋势、差距及未来研究建议
Joshua Kelsall,Xingwei Tan,Aislinn Bergin et al.
Joshua Kelsall et al.
The legal profession faces mounting pressures, including case backlogs and limited access to legal services. Large language models (LLMs), such as OpenAI's GPT series, have been touted as potential solutions, promising to streamline tasks s...
Damian Eke,Ricardo Chavarriaga,Bernd Stahl
Damian Eke
In the last decade, several organisations, and national and international agencies have developed impact assessments (IAs) to mitigate the risks and impact of AI systems as well as to promote responsible, just and trustworthy design, develo...