marc cheong

This article looks into possible scenarios where developers might consider turning their free and open source software into protestware. Using different frameworks commonly used in artificial intelligence (AI) ethics, we extend the applications of AI ethics to the study of protestware.

Generative artificial intelligence systems based on transformers, including both text generators such as GPT-4 and image generators such as DALL-E 3, have recently entered the popular consciousness. These tools, while impressive, are liable to reproduce, exacerbate, and reinforce extant human social biases, such as gender and racial biases. In this article, we systematically review the extent to which DALL-E Mini suffers from this problem. In line with the Model Card published alongside DALL-E Mini by its creators, we find that the images it produces tend to represent dozens of different occupations as populated either solely by men (e.g., pilot, builder, plumber) or solely by women (e.g., hairdresser, receptionist, dietitian). In addition, the images DALL-E Mini produces tend to represent most occupations as populated primarily or solely by White people (e.g., farmer, painter, prison officer, software engineer) and very few by non-White people (e.g., pastor, rapper). These findings suggest that exciting new AI technologies should be critically scrutinized and perhaps regulated before they are unleashed on society.

The Australasian Journal of Information Systems is a refereed journal that publishes articles contributing to Information Systems theory and practice.

This paper presents a critical review of key ethical issues raised by the emergence of mental health chatbots. Chatbots use varying degrees of artificial intelligence and are increasingly deployed in many different domains including mental health. The technology may sometimes be beneficial, such as when it promotes access to mental health information and services. Yet, chatbots raise a variety of ethical concerns that are often magnified in people experiencing mental ill-health. These ethical challenges need to be appreciated and addressed throughout the technology pipeline. After identifying and examining four important ethical issues by means of a recognised ethical framework comprised of five key principles, the paper offers recommendations to guide chatbot designers, purveyers, researchers and mental health practitioners in the ethical creation and deployment of chatbots for mental health.

Social media has become a basis for helping us maintain human contact, especially as our alienation from our phenomenological experiences of ‘being human’ is becoming apparent due to the pandemic. I argue for how existentialist philosophy is crucial, more than ever, to interrogate our social media usage, which is a ‘necessary evil’ in our daily lives. Firstly, Kierkegaard’s critiques of the crowd and of the press are equally applicable to social media, which plays both roles: enabling an anonymous mass of public opinion and doubling-up as an information source, reducing responsibility on the individual. Secondly, social media leads to an intrinsic pressure to objectify one’s self (as portrayed) due to the possibility of an omnipresent Other, based on the technological design of networks. I will link my arguments on social media to other existential ideals and will conclude by suggesting changes that may promote existential ideals in one’s social media portrayal and engagement.

Governments and businesses worldwide deployed a variety of technological measures to help prevent and track the spread of COVID-19. In Australia, these applications contained usability, accessibility, and security flaws that hindered their effectiveness and adoption. Australia, like most countries, has transitioned to treating COVID as endemic. However it is yet to absorb lessons from the technological issues with its approach to the pandemic. In this short paper we a) provide a systematization of the most notable events; b) identify and review different failure modes of these applications; and c) develop recommendations for developing apps in the face of future crises. Our work focuses on a single country. However, Australia’s issues are particularly instructive as they highlight surprisingly pitfalls that countries should address in the face of a future pandemic.

INTRODUCTION: The provision of maternity services in Australia has been significantly disrupted in response to the COVID-19 pandemic. Many changes were initiated quickly, often with rapid dissemination of information to women. The aim of this study was to better understand what information and messages were circulating regarding COVID-19 and pregnancy in Australia and potential information gaps. METHODS: This study adopted a qualitative approach using social media and interviews. A data analytics tool (TIGER-C19) was used to extract data from social media platforms Reddit and Twitter from June to July 2021 (in the middle of the third COVID-19 wave in Australia). A total of 21 individual semi-structured interviews were conducted with those who were, or had been, pregnant in Australia since March 2020. Social media data were analysis via inductive content analysis and interview data were thematically analysed. RESULTS: Social media provided a critical platform for sharing and seeking information, as well as highlighting attitudes of the community towards COVID-19 vaccines in pregnancy. Women interviewed described wanting further information on the risks COVID-19 posed to themselves and their babies, and greater familiarity with the health service during pregnancy, in which they would labour and give birth. Health providers were a trusted source of information. Communication strategies that allowed participants to engage in real-time interactive discussions were preferred. A real or perceived lack of information led participants to turn to informal sources, increasing the potential for exposure to misinformation. CONCLUSION: It is vital that health services communicate effectively with pregnant women, early and often throughout public health crises, such as the COVID-19 pandemic. This was particularly important during periods of increased restrictions on accessing hospital services. Information and communication strategies need to be clear, consistent, timely and accessible to reduce reliance on informal and potentially inaccurate sources.

The epistemic position of an agent often depends on their position in a larger network of other agents who provide them with information. In general, agents are better off if they have diverse and independent sources. Sullivan et al. [19] developed a method for quantitatively characterizing the epistemic position of individuals in a network that takes into account both diversity and independence and presented a proof-of-concept, closed-source implementation on a small graph derived from Twitter data [19]. This paper reports on an open-source re-implementation of their algorithm in Python, optimized to be usable on much larger networks. In addition to the algorithm and package, we also show the ability to scale up our package to large synthetic social network graph profiling, and finally demonstrate its utility in analyzing real-world empirical evidence of ‘echo chambers’ on online social media, as well as interdisciplinary diversity in an academic communications network.

Intellectual humility (IH) is often conceived as the recognition of, and appropriate response to, your own intellectual limitations. As far as we are aware, only a handful of studies look at interventions to increase IH – e.g. through journalling – and no study so far explores the extent to which having high or low IH can be predicted. This paper uses machine learning and natural language processing techniques to develop a predictive model for IH and identify top terms and features that indicate degrees of IH. We trained our classifier on the dataset from an existing psychological study on IH, where participants were asked to journal their experiences with handling social conflicts over 30 days. We used Logistic Regression (LR) to train a classifier and the Linguistic Inquiry and Word Count (LIWC) dictionaries for feature selection, picking out a range of word categories relevant to interpersonal relationships. Our results show that people who differ on IH do in fact systematically express themselves in different ways, including through expression of emotions (i.e., positive, negative, and specifically anger, anxiety, sadness, as well as the use of swear words), use of pronouns (i.e., first person, second person, and third person) and time orientation (i.e., past, present, and future tenses). We discuss the importance of these findings for IH and the value of using such techniques for similar psychological studies, as well as some ethical concerns and limitations with the use of such semi-automated classifications.

Trust in vaccination is eroding, and attitudes about vaccination have become more polarized. This is an observational study of Twitter analyzing the impact that COVID-19 had on vaccine discourse. We identify the actors, the language they use, how their language changed, and what can explain this change. First, we find that authors cluster into several large, interpretable groups, and that the discourse was greatly affected by American partisan politics. Over the course of our study, both Republicans and Democrats entered the vaccine conversation in large numbers, forming coalitions with Antivaxxers and public health organizations, respectively. After the pandemic was officially declared, the interactions between these groups increased. Second, we show that the moral and non-moral language used by the various communities converged in interesting and informative ways. Finally, vector autoregression analysis indicates that differential responses to public health measures are likely part of what drove this convergence. Taken together, our results suggest that polarization around vaccination discourse in the context of COVID-19 was ultimately driven by a trust-first dynamic of political engagement.

The rise of social media mediated celebrity culture raises several philosophical concerns. It is not uncommon to see, for example, Hollywood actors being placed in the same bracket as YouTube artists and Instagram influencers. The increased perceived ‘connectivity’ afforded by social media allows online celebrities to reach more fans and increases the perceived engagement or intimacy in the fan-celebrity relationship. In the present article I argue that this online relationship, which is beneficial to celebrities (for brand development) and social media companies (in profiting from the high engagement), has the potential to cause harm to both the celebrities as well as their fanbases (and sometimes innocent third parties). Firstly, I argue that celebrities’ attempts to be more intimate or authentic with their fanbase can turn out to be – more often than not – acts of Sartrean bad faith. Celebrities who tend to project a certain self-styled ‘online authenticity’, given the context of social media’s attention economy, can run the risk of treating a fan as a means-to-an-end, rather than an autonomous for-itself. Secondly, I argue that this phenomenon can catalyse real-world harms, by drawing upon network theory and social psychology. I argue that the connectedness of social media, ‘blending into the crowd’, and social media technologies’ ethos of optimising-for-engagement, leads to real harms to human wellbeing when fans do not engage critically and mindfully with online celebrities. Examples include Trump-esque celebrity politicians trying to drum up populist influence; celebrities feuding online encouraging fans’ conduct of harmful trolling and harassment; and vilification of those who do not subscribe to the same perceived worldview of a celebrity’s fandom. Following my arguments within, I shall outline an online celebrity’s ethical duties in their social media engagement, with emphasis on the duties that celebrity status comes with, particularly in preventing harms that transcend the online into the offline.

Many scholars agree that the Internet plays a pivotal role in self-radicalization, which can lead to behaviors ranging from lone-wolf terrorism to participation in white nationalist rallies to mundane bigotry and voting for extremist candidates. However, the mechanisms by which the Internet facilitates self-radicalization are disputed; some fault the individuals who end up self-radicalized, while others lay the blame on the technology itself. In this paper, we explore the role played by technological design decisions in online self-radicalization in its myriad guises, encompassing extreme as well as more mundane forms. We begin by characterizing the phenomenon of technological seduction. Next, we distinguish between top-down seduction and bottom-up seduction. We then situate both forms of technological seduction within the theoretical model of dynamical systems theory. We conclude by articulating strategies for combating online self-radicalization.