A Code of Digital Ethics: laying the foundation for digital ethics in a science and technology company

The rapid and dynamic nature of digital transformation challenges companies that wish to develop and deploy novel digital technologies. Like other actors faced with this transformation, companies need to find robust ways to ethically guide their innovations and business decisions. Digital ethics has recently featured in a plethora of both practical corporate guidelines and compilations of high-level principles, but there remains a gap concerning the development of sound ethical guidance in specific business contexts. As a multinational science and technology company faced with a broad range of digital ventures and associated ethical challenges, Merck KGaA has laid the foundations for bridging this gap by developing a Code of Digital Ethics (CoDE) tailored for this context. Following a comprehensive analysis of existing digital ethics guidelines, we used a reconstructive social research approach to identify 20 relevant principles and derive a code designed as a multi-purpose tool. Versatility was prioritised by defining non-prescriptive guidelines that are open to different perspectives and thus well-suited for operationalisation for varied business purposes. We also chose a clear nested structure that highlights the relationships between five core and fifteen subsidiary principles as well as the different levels of reference—data and algorithmic systems—to which they apply. The CoDE will serve Merck KGaA and its new Digital Ethics Advisory Panel to guide ethical reflection, evaluation and decision-making across the full spectrum of digital developments encountered and undertaken by the company whilst also offering an opportunity to increase transparency for external partners, and thus trust.

A Machine Learning Analysis of COVID-19 Mental Health Data

In late December 2019, the novel coronavirus (Sars-Cov-2) and the resulting disease COVID-19 were first identified in Wuhan China. The disease slipped through containment measures, with the first known case in the United States being identified on January 20th, 2020. In this paper, we utilize survey data from the Inter-university Consortium for Political and Social Research and apply several statistical and machine learning models and techniques such as Decision Trees, Multinomial Logistic Regression, Naive Bayes, k-Nearest Neighbors, Support Vector Machines, Neural Networks, Random Forests, Gradient Tree Boosting, XGBoost, CatBoost, LightGBM, Synthetic Minority Oversampling, and Chi-Squared Test to analyze the impacts the COVID-19 pandemic has had on the mental health of frontline workers in the United States. Through the interpretation of the many models applied to the mental health survey data, we have concluded that the most important factor in predicting the mental health decline of a frontline worker is the healthcare role the individual is in (Nurse, Emergency Room Staff, Surgeon, etc.), followed by the amount of sleep the individual has had in the last week, the amount of COVID-19 related news an individual has consumed on average in a day, the age of the worker, and the usage of alcohol and cannabis.

Tipos de big data y análisis sociológico: usos, críticas y problemas éticos

Solo con un conocimiento más consciente de los diferentes tipos de big data y sus posibles usos, límites y ventajas la sociología se beneficiará realmente de estas bases empíricas. En este artículo, a partir de una clasificación de los diversos tipos de big data, se describen algunas áreas de uso en la investigación social destacando cuestiones críticas y problemas éticos. Los límites se vinculados a cuestiones fundamentales relativas a la calidad de los big data. Otra cuestión clave se refiere al acceso. Otro aspecto metodológico a tener en cuenta es que los datos digitales en la web deben considerarse no intrusivos. Los métodos de investigación encubiertos ha desafiado la práctica de evaluación ética establecidas adoptadas en la mayoría de las instituciones de investigación: el consentimiento informado. Las pautas éticas digitales no pueden ser universales y estar establecidas de una vez por todas. Only through expert knowledge of the different types of big data and their possible uses, limits and advantages will sociology benefit from these empirical bases. In this article, based on a classification of the various types of big data, some areas of use in social research are described, highlighting critical questions and ethical problems. The limits are related to fundamental questions regarding the quality of big data. Another paramount issue concerns access. A further methodological aspect is that digital data on the web should be considered non-intrusive. Covert research methods have challenged the established ethical evaluation practice adopted in most research institutions: informed consent. Digital ethical guidelines cannot be universal and established once and for all.

Doing Web Surveys During Uncertain Times

The chapter will focus on using a web survey administered using social networks as a gathering point to collect data on people's risk perception and their undertaking of protective behaviors during the Italian COVID-19 crisis. This was an unprecedented moment in the digital age when there was no possibility of physical contact due to the limitations imposed on coexistence by the health emergency to stem the spread of the virus. This is when digital connections are the only link among people, and the only tool that can be used for doing social research is trying to satisfy the desire for knowledge without limiting the potential for knowledge production even in times of profound uncertainty and several limitations. Analyzing the participants' feedback on web surveys during times of deep uncertainty allows the authors to show what is clearly happening to social research currently. The discussions will be supported by an auto-ethnography conducted on comments left by the respondents to the survey.

Tales of Love and Pandemic

The main argument of the chapter is the analysis of the reading and writing behaviour on Wattpad during the phases of lockdown in Italy for the COVID-19 pandemic. The COVID-19 pandemic represents the first great event of ‘data society' reactions making several authors reflect on various aspects and thoughts about social impact of tech ecosystems. Nowadays, it becomes essential to understand the role that digital technologies and media have had to soothe feelings related to social isolation and physical distancing measures. Thus, as widely acknowledged, besides providing data for social research in many aspects of life, the digital context also suggests above all innovated methods enforced by the physical distancing. This research has explored about 600 stories edited on Wattpad that have been selected through the query “Covid.” The aim of the analysis is to map collective imaginary of users about the COVID-19 pandemic within a digital medium for fanfiction, combining three fundamental approaches of digital methods.

Secondary Analysis for Digitized Data

Secondary analysis for quantitative data is a social research method traditionally employed for statistical analysis of administrative data. In the new digital society, this old research method that pre-existed the emergence of the new digital environment has been digitized to carry out its valuable activity in doing science. In this chapter, the secondary analysis for digitized data is illustrated. Thanks to the growing availability of datasets digitized on the web, the scholars of social well-being use the secondary analysis to inquiry this phenomenon through a cross-national perspective. The authors present the empirical study of World Love Index, in which the utility of the secondary analysis in finding and selecting valid indicators of social well-being is experienced.

Et Al.: New Voices in Arts Management

Et Al. imagines kaleidoscopic possibilities for the stewardship of culture and land as decolonizing practices. Culture and the arts can enhance society by strengthening our connections to each other and to the earth. This arts management book was born during a racial reckoning and accelerated by a global pandemic. What exactly is the business of no-business-as-usual? The ethical challenge for arts management is far more complex than asking how to get things done; we must also ask who gets to do things, where, and with what resources? Our task is to generate cultures that refuse to annihilate themselves or each other, much less the planet. Et Al. contributes to the conversation about arts and cultural management by providing rare, behind-the-scenes insights on justice-centered arts management praxis — ideas tied to action. The book makes space for people to publicly reflect, write, and share insights about their own ideas and ways of working. Its polyphonic voices speak to pragmatic strategies for arts management across cultures, genres, and spaces. Its stories are told from the perspective of individuals and families, micro businesses, artist collectives, and civic institutions. As a digital publication, the platform lends itself to multi-media knowledge objects; the experiences documented within it include ethnographies, qualitative social research, personal and communal manifestos, dialogues between peers, visual essays, videos, and audio tracks. This open source, multimedia book is structured into six streams which are numbered for their exponential powers: Stream¹ : Center is Everywhere; Stream² : Gathering Community; Stream³ : Honoring Histories; Stream⁴ : Shifting Research; Stream⁵ : Forging Paths; Stream⁶ : Generative Practice. The book discusses imaginative ways of generating cultural equity in praxis, and is an invitation for further imagination, conversation, and connection. Et Al. presents an interactive landscape for readers, thinkers, and creators to engage with multimedia and intergenerational essays by Amy Shimshon-Santo, Genevieve Kaplan, Gerlie Collado, Abraham Ferrer, Julie House, Britt Campbell, Delia Xóchitl Chávez, Sean Cheng, Yvonne Farrow, Allen Kwabena Frimpong, Kayla Jackson, Erika Karina Jiménez Flores, Cobi Krieger, Loreto Lopez, Cynthia Martínez Benavides, Christy McCarthy, Janice Ngan, Cailin Nolte, Michaela Paulette Shirley, Robin Sukhadia, Katrina Sullivan, and Tatiana Vahan.

Delphi MIX for the Construction of Future Critical Scenarios in Social Distancing

In the era of digital society, social research must devise innovative and adaptive methodologies in relation to new forms of communication and social interaction. The social distancing measures aimed at containing the spread of COVID-19 have produced the need for social sciences to face new research challenges by making the best possible use of information technology and tools. The researchers' aim is to present an innovative method of remote participatory social research, which can be framed in the context of future studies. This method, called Delphi MIX, has been developed by CNR-Irpps researchers since 2003, and its last adjustment has been designed as a consequence of the coronavirus crisis. Delphi MIX is a method for participatory strategic planning. It can be understood as a political agenda that aims to a desirable and achievable future.

Using Video Diaries in Social Science Research

The focus of this chapter is the use of video-diaries in social research. The aim is to examine and reflect upon the particular ethical terrain and situated ethics of using visual diary method in social science research with different participant groups who arguably present specific ethical concerns, including children and older people, people with disabilities (either physical, cognitive, or psychiatric), and older people. The authors present a discussion of the specific ethical considerations arising from the use of this method due to the particular type of data it generates, namely audio and moving visual data. As such, the process of creating a video diary and the procedures involved in collecting and analysing video diary data are fundamentally different from a paper-based (non-digital) diary. For these reasons, it is important to step back and reflect on the situated ethics, including the digital ethics encountered when using this method.

Online Research Practice and Integrated Perspectives of Inquiry

The authors reconstruct the system of advantages and limits of e-mail data collection and web survey technique in social research; for this purpose, they examine in detail a set of studies that stimulate multiple reflections, both with reference to the overall value of survey research and on the role of the web for social sciences. The subject of all selected research designs is a complex social problem that involves the internet, both focus for observation and tool for research: voting intentions, social effects of the pandemic, the quality of university life, technology addiction. In each research experience, for different reasons—above all due to the lack of a single, self-sufficient data collection mode—, the authors favor the integration of research strategies: 1) mixed-modes of data collection, 2) follow-up panel web survey, 3) mixed methods research, 4) introduction of a preliminary pilot study, 5) multilevel survey.