NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS by Richard H. Thaler and Cass R. Sunstein Penguin Books, 2009, 312 pp, ISBN 978-0-14-311526-7This book is best described formally as a general explanation of and advocacy for libertarian paternalism, a term coined by the authors in earlier publications. Informally, it is about how leaders, systems, organizations, and governments can nudge people to do the things the nudgers want and need done for the betterment of the nudgees, or of society. It is paternalism in the sense that "it is legitimate for choice architects to try to influence people's behavior in order to make their lives longer, healthier, and better", (p. 5) It is libertarian in that "people should be free to do what they like - and to opt out of undesirable arrangements if they want to do so", (p. 5) The built-in possibility of opting out or making a different choice preserves freedom of choice even though people's behavior has been influenced by the nature of the presentation of the information or by the structure of the decisionmaking system. I had never heard of libertarian paternalism before reading this book, and I now find it fascinating.Written for a general audience, this book contains mostly social and behavioral science theory and models, but there is considerable discussion of structure and process that has roots in mathematical and quantitative modeling. One of the main applications of this social system is economic choice in investing, selecting and purchasing products and services, systems of taxes, banking (mortgages, borrowing, savings), and retirement systems. Other quantitative social choice systems discussed include environmental effects, health care plans, gambling, and organ donations. Softer issues that are also subject to a nudge-based approach are marriage, education, eating, drinking, smoking, influence, spread of information, and politics. There is something in this book for everyone.The basis for this libertarian paternalism concept is in the social theory called "science of choice", the study of the design and implementation of influence systems on various kinds of people. The terms Econs and Humans, are used to refer to people with either considerable or little rational decision-making talent, respectively. The various libertarian paternalism concepts and systems presented are tested and compared in light of these two types of people. Two foundational issues that this book has in common with another book, Network of Echoes: Imitation, Innovation and Invisible Leaders, that was also reviewed for this issue of the Journal are that 1 ) there are two modes of thinking (or components of the brain) - an automatic (intuitive) process and a reflective (rational) process and 2) the need for conformity and the desire for imitation are powerful forces in human behavior. …

Nudge: Improving Decisions about Health, Wealth, and Happiness

At the dawn of the fourth industrial revolution, we are witnessing a fast and widespread adoption of artificial intelligence (AI) in our daily life, which contributes to accelerating the shift towards a more algorithmic society. However, even with such unprecedented advancements, a key impediment to the use of AI-based systems is that they often lack transparency. Indeed, the black-box nature of these systems allows powerful predictions, but it cannot be directly explained. This issue has triggered a new debate on explainable AI (XAI). A research field holds substantial promise for improving trust and transparency of AI-based systems. It is recognized as the sine qua non for AI to continue making steady progress without disruption. This survey provides an entry point for interested researchers and practitioners to learn key aspects of the young and rapidly growing body of research related to XAI. Through the lens of the literature, we review the existing approaches regarding the topic, discuss trends surrounding its sphere, and present major research trajectories.

Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

人教版高中英语新课程教材中,语言运用（Using Language）是每个单元必不可少的部分,提供了围绕单元中心话题的听、说、读、写的综合性练习,是单元中心话题的延续和升华.如何设计Using Language部分的教学,使自己的教学模式既不落俗套,又能真正体现新课程标准所倡导的教学理念,正是广大一线英语教师一直努力探索的问题.

打磨Using Language,倡导新理念

There has recently been a surge of work in explanatory artificial intelligence (XAI). This research area tackles the important problem that complex machines and algorithms often cannot provide insights into their behavior and thought processes. XAI allows users and parts of the internal system to be more transparent, providing explanations of their decisions in some level of detail. These explanations are important to ensure algorithmic fairness, identify potential bias/problems in the training data, and to ensure that the algorithms perform as expected. However, explanations produced by these systems is neither standardized nor systematically assessed. In an effort to create best practices and identify open challenges, we describe foundational concepts of explainability and show how they can be used to classify existing literature. We discuss why current approaches to explanatory methods especially for deep neural networks are insufficient. Finally, based on our survey, we conclude with suggested future research directions for explanatory artificial intelligence.

Explaining Explanations: An Overview of Interpretability of Machine Learning

『Google Scholar』の利点

Text-to-image AI are capable of generating novel images for inspiration, but their applications for 3D design workflows and how designers can build 3D models using AI-provided inspiration have not yet been explored. To investigate this, we integrated DALL-E, GPT-3, and CLIP within a CAD software in 3DALL-E, a plugin that generates 2D image inspiration for 3D design. 3DALL-E allows users to construct text and image prompts based on what they are modeling. In a study with 13 designers, we found that designers saw great potential in 3DALL-E within their workflows and could use text-to-image AI to produce reference images, prevent design fixation, and inspire design considerations. We elaborate on prompting patterns observed across 3D modeling tasks and provide measures of prompt complexity observed across participants. From our findings, we discuss how 3DALL-E can merge with existing generative design workflows and propose prompt bibliographies as a form of human-AI design history.

3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows

Studies of smart speakers highlight issues people face with understanding why unexpected behaviour occurs and with recovering from mistakes due to uninformative responses. Yet, our understanding of such intelligibility issues in smart speakers — difficulties in understanding the device's behaviour — remains limited, in particular, for long-term and frequent smart speaker users who may encounter more complex situations than first-time users. We conducted an online survey and interviews with smart speaker enthusiasts to investigate how they form an understanding of the device's behaviour and what strategies they use to recover from breakdowns. We identified seven different breakdown recovery strategies and found that enthusiasts particularly struggled with breakdowns in their IoT infrastructure. Informed by our results, we propose three research directions: infrastructural breakdowns as learning opportunities for understanding the smart speaker's behaviour; leveraging aspects of non-verbal communication as opportunities for design; and considering passive users’ intelligibility and control needs.

Intelligibility Issues Faced by Smart Speaker Enthusiasts in Understanding What Their Devices Do and Why

In this workshop, we will review and discuss open issues, technical challenges and conceptual models for multi-device spatial or proxemic interaction. We aim to bring together researchers, students and practitioners working on technical infrastructures, studies and designs of spatial in-terfaces, or domain specific multi-device applications that use space as a unit of analysis. We focus specifically on analysing how such interfaces, tools and tracking technolo-gy can be deployed "in the wild". The workshop will facili-tate knowledge exchange about the current state of spatial and proxemic interactive systems, identify application do-mains and enabling technologies for cross-surface interac-tions in the wild, and establish a research community to develop effective strategies for successful design of cross-device interactions.

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Cross-Surface: Challenges and Opportunities of Spatial and Proxemic Interaction

People’s physical movement and body language implicitly convey what they think and feel, are doing or are about to do. In contrast, current smart speakers miss out on this richness of body language, primarily relying on voice commands only. We present QUBI, a dynamic smart speaker that leverages expressive physical motion – stretching, nodding, turning, shrugging, wiggling, pointing and leaning forwards/backwards – to convey cues about its underlying behaviour and activities. We conducted a qualitative Wizard of Oz lab study, in which 12 participants interacted with QUBI in four scripted scenarios. From our study, we distilled six themes: (1) mirroring and mimicking motions; (2) body language to supplement voice instructions; (3) anthropomorphism and personality; (4) audio can trump motion; (5) reaffirming uncertain interpretations to support mutual understanding; and (6) emotional reactions to QUBI’s behaviour. From this, we discuss design implications for future smart speakers.

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Machine Body Language: Expressing a Smart Speaker’s Activity with Intelligible Physical Motion

Methods to support the creation of multi-device user interfaces typically use some type of abstraction of the user interface design. To retrieve the final user interface from the abstraction a transformation will be applied that specializes the abstraction for a particular target platform. The User Interface Markup Language (UIML) offers a way to create multi- device user interface descriptions while maintaining the consistency of certain aspects of a user interface across platforms. We extended the UIML language with support for layout constraints. Designers can create layout templates based on constraints that limit the ways a user interface can rearrange across platforms. This results in a higher degree of consistency and reusability of interface designs.

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Jo Vermeulen

Papers

3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows

Intelligibility Issues Faced by Smart Speaker Enthusiasts in Understanding What Their Devices Do and Why

Cross-Surface: Challenges and Opportunities of Spatial and Proxemic Interaction

Machine Body Language: Expressing a Smart Speaker’s Activity with Intelligible Physical Motion

8 Constraint Adaptability of Multi-Device User Interfaces