Search results

This study aims to analyse the differences between professional interaction mediated by video conferencing and direct professional interaction. The research identifies diverging interests of office workers for the purpose of addressing work ethical and business ethical issues of professional collaboration, competition, and power in future hybrid work models.

Based on 28 qualitative interviews conducted between November 2020 and June 2021, and through the theoretical lens of phenomenology, the study develops explanatory hypotheses conceptualising four basic intentions of professional interaction and their corresponding preferences for video conferences and working on site.

The four intentions developed on the basis of the interviews are: the need for physical proximity; the challenge of collective creativity; the will to influence; and control of communication. This conceptual framework qualifies a moral ambivalence of professional interaction. The authors identify a connectivity paradox of professional interaction where the personal dimension remains unarticulated for the purpose of maintaining professionality. This tacit human connectivity is intertwined with latent power relations. This plasticity of both connectivity and power in direct interaction can be diminished by transferring the interaction to video conferencing.

The application of phenomenology to a collection of qualitative interviews has enabled the identification of underlying intention structures and the system in which they affect each other. This research identifies conflicts of interests between workers relative to their different self-perceived abilities to persevere in competitive professional interaction. It is therefore able to address consequences of future hybrid work models at an existential and societal level.

The purpose of this study is to create an ethical norm that will help guide the human race toward long-term survival.

The project posits a new societal ethical norm designed around a fundamental principle: the long-term survival of the human race with individual dignity. This study examines the requirements of the new norm and what is needed to achieve that goal.

There are three types of organizations that have the organizational and economic capacity to be responsible for future outcomes: governments, religions and corporations. These three types of organizations must act as if they have a moral compass that will compel them to develop and uphold the requirements for the survival of humanity with individual dignity.

The analysis shows that a new, broader ethical norm must be established, and this norm implies that large organizations must act with a future embracing ethical behavior.

This study generates specific pathways for example: governments should adopt the just war principles and prohibitions on governments or other institutions from teaching any form of class superiority. These and other pathways are designed to diffuse threats to the fundamental principle.

The fundamental principle includes universal human dignity. This means that the notion of individual dignity must be defined or understood, and the requirements to attain this goal must be identified.

This project takes concepts from long-termism, forward-looking collective responsibility, corporate social responsibility and the global catastrophic risk institute to advocate for a new ethical norm.

The ways communities have regarded disasters and natural hazards in the cultural sphere can provide a lens to inform the understanding of their ability to withstand shocks and the factors that led to such conditions. Only by tracing the complexities of creating, transmitting and preserving a culture of preparedness among disaster-vulnerable communities can researchers and practitioners claim to be working toward policy that is informed by the communities’ own experience and design policy or programming on their behalf.

In efforts to prevent, respond to and recover from disasters, what alternatives are available to top-down strategies for imposing expert knowledge on lay publics? How is the context of communities’ socioecological context understood in the development of programs and policy on their behalf? What can be learned from community narratives and cultural practices to inform disaster risk reduction?

I collected examples of how different communities perceive, prevent and respond to disaster through art, music and literature and analyzed how these were embedded into local narratives and how historical context influenced such approaches. My findings show that communities use cultural practices to contextualize experiences of hazards into their collective narrative; that is, storytelling and commemoration make disasters comprehensible. By incorporating such findings into existing policies and programs, institutions may be able to more effectively apply them to affected communities or build new ones around their actual needs and experiences.

By framing disasters as an anthropological inquiry, practitioners can better recognize the influence of a place’s nuance in the disaster management canon–guided by these details, not despite them.

This paper aims to investigate the impact of climate change news on the dynamics of US stock indices.

The empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.

The results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.

First, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”

The age of artificial intelligence (AI) is already upon us. The rapid development of AI tools is facilitating sustainable development and its corollary social good. For AI dedicated to social good to be impactful, it has to be human-centred, striving to achieve inclusiveness, sustainable livelihoods and community well-being. In short, it offers major opportunities to holistically enhance peoples' lives in diverse areas: education, health care, food security, disaster reduction, smart cities, etc. However, ethical, unbiased and ‘secure-by-design’ algorithms that power AI are crucial to building trust in this technology. Civil society's engagement can hopefully drive the features and values that should be embedded in AI.

This chapter focuses on the societal benefits that AI can deliver. Our initiatives and decisions of today will fashion the ‘Social Good’ AI applications of tomorrow. Sustainable Development Goals (SDGs) being addressed are 2–4 and 10–11.