The transition of Artificial Intelligence (AI) from a lab-based science to
live human contexts brings into sharp focus many historic, socio-cultural
biases, inequalities, and moral dilemmas. Many questions that have been raised
regarding the broader ethics of AI are also relevant for AI in Education
(AIED). AIED raises further specific challenges related to the impact of its
technologies on users, how such technologies might be used to reinforce or
alter the way that we learn and teach, and what we, as a society and
individuals, value as outcomes of education. This chapter discusses key ethical
dimensions of AI and contextualises them within AIED design and engineering
practices to draw connections between the AIED systems we build, the questions
about human learning and development we ask, the ethics of the pedagogies we
use, and the considerations of values that we promote in and through AIED
within a wider socio-technical system.

人工智能从实验室科学转变为实际人类环境，引发了许多历史、社会文化的偏见、不平等和道德困境。人工智能教育（AIED）提出了更多特定的挑战，涉及技术对用户的影响，这些技术如何用于加强或改变我们学习和教学的方式，以及作为社会和个体，我们对教育结果的价值观。该文章讨论了人工智能的关键伦理维度，并将其置于 AIED 设计和工程实践中，以建立我们所构建的 AIED 系统、我们提出的有关人类学习和发展的问题、我们使用的教学伦理以及我们通过 AIED 在更广泛的社会技术系统中提倡的价值观之间的联系。

教育领域中人工智能的伦理

The Ethics of AI in Education

In the past decade, the deployment of deep learning (Artificial Intelligence
(AI)) methods has become pervasive across a spectrum of real-world
applications, often in safety-critical contexts. This comprehensive research
article rigorously investigates the ethical dimensions intricately linked to
the rapid evolution of AI technologies, with a particular focus on the
healthcare domain. Delving deeply, it explores a multitude of facets including
transparency, adept data management, human oversight, educational imperatives,
and international collaboration within the realm of AI advancement. Central to
this article is the proposition of a conscientious AI framework, meticulously
crafted to accentuate values of transparency, equity, answerability, and a
human-centric orientation. The second contribution of the article is the
in-depth and thorough discussion of the limitations inherent to AI systems. It
astutely identifies potential biases and the intricate challenges of navigating
multifaceted contexts. Lastly, the article unequivocally accentuates the
pressing need for globally standardized AI ethics principles and frameworks.
Simultaneously, it aptly illustrates the adaptability of the ethical framework
proposed herein, positioned skillfully to surmount emergent challenges.

AI 技术的快速发展与伦理维度的深入研究，特别关注于医疗领域，探索透明度、数据管理、人工监督、教育要求以及国际合作等众多方面，呼吁全球统一的 AI 伦理原则和框架，并提出有益的伦理方案以应对新兴挑战。

在医疗和其他领域利用人工智能的道德框架

Ethical Framework for Harnessing the Power of AI in Healthcare and  Beyond

As part of growing NLP capabilities, coupled with an awareness of the ethical
dimensions of research, questions have been raised about whether particular
datasets and tasks should be deemed off-limits for NLP research. We examine
this question with respect to a paper on automatic legal sentencing from EMNLP
2019 which was a source of some debate, in asking whether the paper should have
been allowed to be published, who should have been charged with making such a
decision, and on what basis. We focus in particular on the role of data
statements in ethically assessing research, but also discuss the topic of dual
use, and examine the outcomes of similar debates in other scientific
disciplines.

本文讨论伦理学问题如何限制 NLP 研究，重点关注数据声明在伦理评估研究中的作用，同时讨论其他科学领域中类似辩论的结果。