Public attention towards explainability of artificial intelligence (AI)
systems has been rising in recent years to offer methodologies for human
oversight. This has translated into the proliferation of research outputs, such
as from Explainable AI, to enhance transparency and control for system
debugging and monitoring, and intelligibility of system process and output for
user services. Yet, such outputs are difficult to adopt on a practical level
due to a lack of a common regulatory baseline, and the contextual nature of
explanations. Governmental policies are now attempting to tackle such exigence,
however it remains unclear to what extent published communications,
regulations, and standards adopt an informed perspective to support research,
industry, and civil interests. In this study, we perform the first thematic and
gap analysis of this plethora of policies and standards on explainability in
the EU, US, and UK. Through a rigorous survey of policy documents, we first
contribute an overview of governmental regulatory trajectories within AI
explainability and its sociotechnical impacts. We find that policies are often
informed by coarse notions and requirements for explanations. This might be due
to the willingness to conciliate explanations foremost as a risk management
tool for AI oversight, but also due to the lack of a consensus on what
constitutes a valid algorithmic explanation, and how feasible the
implementation and deployment of such explanations are across stakeholders of
an organization. Informed by AI explainability research, we conduct a gap
analysis of existing policies, leading us to formulate a set of recommendations
on how to address explainability in regulations for AI systems, especially
discussing the definition, feasibility, and usability of explanations, as well
as allocating accountability to explanation providers.

本文通过对欧盟、美国和英国政策文件的调查，针对可解释性人工智能的技术和社会影响进行了主题和缺口分析。发现政策通常基于对解释的粗略观念和要求。最终提出了一组关于如何解释 AI 系统的建议，其中包括定义、可行性、可用性以及分配解释提供者的责任。

AI 政策中的可解释性：欧盟、美国和英国的沟通、报告、法规和标准的关键回顾

Explainability in AI Policies: A Critical Review of Communications,  Reports, Regulations, and Standards in the EU, US, and UK

We are experiencing an abundance of Internet-of-Things (IoT) middleware
solutions that provide connectivity for sensors and actuators to the Internet.
To gain a widespread adoption, these middleware solutions, referred to as
platforms, have to meet the expectations of different players in the IoT
ecosystem, including device providers, application developers, and end-users,
among others. In this article, we evaluate a representative sample of these
platforms, both proprietary and open-source, on the basis of their ability to
meet the expectations of different IoT users. The evaluation is thus more
focused on how ready and usable these platforms are for IoT ecosystem players,
rather than on the peculiarities of the underlying technological layers. The
evaluation is carried out as a gap analysis of the current IoT landscape with
respect to (i) the support for heterogeneous sensing and actuating
technologies, (ii) the data ownership and its implications for security and
privacy, (iii) data processing and data sharing capabilities, (iv) the support
offered to application developers, (v) the completeness of an IoT ecosystem,
and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims
to highlight the deficiencies of today's solutions to improve their integration
to tomorrow's ecosystems. In order to strengthen the finding of our analysis,
we conducted a survey among the partners of the Finnish IoT program, counting
over 350 experts, to evaluate the most critical issues for the development of
future IoT platforms. Based on the results of our analysis and our survey, we
conclude this article with a list of recommendations for extending these IoT
platforms in order to fill in the gaps.

通过对物联网中间件的代表性样本进行评估，本文重点关注了这些平台对不同物联网用户的预期如何满足，对当前物联网生态系统的差距进行了分析，并在此基础上提出了推荐措施。