Artificial Intelligence based systems increasingly use personalization to provide users with relevant content, products, and solutions. Personalization is intended to support users and address their respective needs and preferences. However, users are becoming increasingly vulnerable to online manipulation due to algorithmic advancements and lack of transparency. Such manipulation decreases users' levels of trust, autonomy, and satisfaction concerning the systems with which they interact. Increasing transparency is an important goal for personalization based systems. Unfortunately, system designers lack guidance in assessing and implementing transparency in their developed systems.
In this work we combine insights from technology ethics and computer science to generate a list of transparency best practices for machine generated personalization. Based on these best practices, we develop a checklist to be used by designers wishing to evaluate and increase the transparency of their algorithmic systems. Adopting a designer perspective, we apply the checklist to prominent online services and discuss its advantages and shortcomings. We encourage researchers to adopt the checklist in various environments and to work towards a consensus-based tool for measuring transparency in the personalization community.
Enjeux éthiques de l'IA en santé : une humanisation du parcours de soin par l'intelligence artificielle ?
考虑到使用人工智能来实现患者护理的更大个性化以及更好地管理人力和物力资源，这似乎是一个不容错过的机会。为了提供更人性化的护理途径，人工智能是医院部门决策者必须通过关注该技术产生的新道德问题和价值观冲突来适当使用的工具。Envisager le recours à l'intelligence artificielle pour une plus personnalisation de la prise en charge du patient et une meilleure gestion des resources humaines et matérielles peut sembler une opportunité à ne pas manquer.由于提出了一个更好的人性化的治疗方案，人工智能是一种方法，使医院环境中的决策者能够适当地利用这种技术产生的新的伦理学和价值冲突。
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
University of Gondar（贡德尔大学）；College of Engineering and Applied Science, University of Colorado, Colorado Springs（科罗拉多大学科罗拉多斯普林斯分校工程与应用科学学院）；Can Tho University（芹苴大学）；Ewha Womans University（梨花女子大学）；University of Colorado, Colorado Springs（科罗拉多大学科罗拉多斯普林斯分校）
The Need for Benchmarks to Advance AI-Enabled Player Risk Detection in Gambling
International Gaming Institute, University of Nevada, Las Vegas（国际博彩研究所，内华达大学拉斯维加斯分校）；Division on Addiction, Cambridge Health Alliance, Harvard Medical School（成瘾科，剑桥健康联盟，哈佛医学院）；Department of Psychology, University of Calgary（心理学系，卡尔加里大学）；Brain & Mind Centre, School of Psychology, Science Faculty, University of Sydney（脑与心智中心，心理学院，理学院，悉尼大学）；Carson College of Business, Washington State University（卡森商学院，华盛顿州立大学）；Focal Research Consultants（焦点研究咨询公司）
