Manh-Toan Ho

Recent advances in machine learning and neuroscience, the abundances of sensors and emotion data have endowed machines with ability to detect, classify, and interact with human emotions. This study philosophize about affective computing devices by examining emotional artificial intelligence (AI) through the lens of affective artifacts, focusing on as personal AI assistants, work-related emotion trackers, and emotional AI toys and robots. Drawing from philosophical accounts on affective artifacts and empirical evidence on human-AI interaction, we argue how emotional AI technologies fulfill the criteria of being affective artifacts from the four key properties: underlying algorithmic complexity, artifactual nature, semi-agentive capabilities, and semi-interpersonal interactions. Furthermore, recognizing that the underlying algorithmic complexity renders these technologies easily manipulated for emotion-related tasks, we also analyze how these tools help us regulate emotions and influence self-perception, interconnecting with the maintenance and construction of our sense of self and identity, blurring the lines between the infosphere and lived experience.

Starting the book by asking the readers to ponder a thin line between “A green brave world” and “A green panopticon,” Mark Coeckelbergh’s Green Leviathan or the Poetics of Political Liberty explores the paths of political thinking’s evolution in response to current technological and environmental challenges, highlighting the overlooked deep connection between traditional philosophical notions of political freedom and the threats of authoritarianism and hidden manipulation amid our urgent ecological challenges. This review examines how the book offers a philosophical orientation for navigating the delicate balance between security and liberty, proposing a “third way” that promotes a relational, capabilities-focused, and positive understanding of freedom. It advocates for the integration of AI and other technologies into a larger “poetic-political project of liberation and democratization,” seeking to construct new common worlds that support both human and non-human flourishing. This vision emphasizes that freedom should be associated with human dignity and the genuine conditions necessary for prosperity, extending beyond individuals to include non-humans, animals, climate, viruses, and indeed AI. The vision presented in the book contributes to the enriching of our growing understanding of the human–technology–nature nexus, as it bridges political philosophy with environmental ethics and technological ethics through the concept of freedom.

This essay seeks to understand what it means for the human collective when AI technologies have become a predominant force in each of our lives through identifying three moral dilemmas (i.e., tragedy of the commons, tragedy of commonsense morality, tragedy of apathy) that shape human choices. In the first part, we articulate AI-driven versions of the three moral dilemmas. Then, in the second part, drawing from evolutionary psychology, existentialism, and East Asian philosophies, we argue that a deep appreciation of three shades of human finitude can help us mitigate harmful effects of the AI-driven versions of the three tragedies and even transcend them.

In recent years, with the advances in machine learning and neuroscience, the abundances of sensors and emotion data, computer engineers have started to endow machines with ability to detect, classify, and interact with human emotions. Emotional artificial intelligence (AI), also known as a more technical term in affective computing, is increasingly more prevalent in our daily life as it is embedded in many applications in our mobile devices as well as in physical spaces. Critically, emotional AI systems have not only the ability to not passively read and classify emotions, but most also have an ability to predict and ‘nudge’ users to certain desired emotional states. Drawing from Piredda (2020)’s account on affective artifacts and other recent accounts, we've examined various emerging emotion-sensing technologies such as recommender algorithms, personal AI assistants, work-related emotion trackers, and emotional AI toys and robots through the lens of affective artifacts. We show how these technologies fulfill the criteria of being affective artifacts: they are artifactual, multifunctional, semi-agentive, and semi-interpesonal. Emotional AI systems as affective artifacts can influence the affective states of the users (e.g., help regulate emotions of ourselves and others), and importantly, our manipulation of these algorithms can intersect with the maintenance and construction of our sense of self and identity.

Vietnam is a fast-growing economy with a population of more than 100 million people. Along with the stable development of the country’s economy, a mindset focusing on making money is also growing in Vietnam. Nonetheless, there has been a noticeable lack of formal education in economics for young people, especially in high school curriculum. Thus, this paper provides a quick look at the issue from the perspective of influential journal articles and books on Vietnam economy. Currently, as the high school curriculum does not include economics, the high school students do not have a formal source of information. Even when they can easily find documents on the Internet, the quick survey suggested a scarcity of trustworthy documents for students. The findings suggest that economics education in Vietnam is currently behind the economic development of the country.

The indirect costs of the COVID-19 pandemic, specifically extended work absenteeism and possible loss of productivity, are discussed focusing on the research community and its publishing. We suggest that the community should learn strategic and innovative decision-making as well as crisis management from business management to think ahead, especially about working effectively and being productive in times of crisis. The main challenges are: 1) communicating scientific and credible information about the pandemic, 2) focusing on being productive to provide some certainty, and 3) adopting a new mindset and being open to unexpected opportunities.

Starting with the first international publication of Le Van Thiem (Lê Văn Thiêm) in 1947, modern mathematics in Vietnam is a longstanding research field. However, what is known about its development usually comes from discrete essays such as anecdotes or interviews of renowned mathematicians. We introduce SciMath—a database on publications of Vietnamese mathematicians. To ensure this database covers as many publications as possible, data entries are manually collected from scientists’ publication records, journals’ websites, universities, and research institutions. Collected data went through various verification steps to ensure data quality and minimize errors. At the time of this report, the database covered 8372 publications, profiles of 1566 Vietnamese, and 1492 foreign authors since 1947. We found a growing capability in mathematics research in Vietnam in various aspects: scientific output, publications on influential journals, or collaboration. The database and preliminary results were presented to the Scientific Council of Vietnam Institute for Advanced Study in Mathematics (VIASM) on November 13th, 2020.

Vietnam, with a geographical proximity and a high volume of trade with China, was the first country to record an outbreak of the new Coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. While the country was expected to have a high risk of transmission, as of April 4, 2020—in comparison to attempts to contain the disease around the world—responses from Vietnam are being seen as prompt and effective in protecting the interests of its citizens, with 239 confirmed cases and no fatalities. This study analyzes the situation in terms of Vietnam’s policy response, social media and science journalism. A self-made web crawl engine was used to scan and collect official media news related to COVID-19 between the beginning of January and April 4, yielding a comprehensive dataset of 14,952 news items. The findings shed light on how Vietnam—despite being under-resourced—has demonstrated political readiness to combat the emerging pandemic since the earliest days. Timely communication on any developments of the outbreak from the government and the media, combined with up-to-date research on the new virus by the Vietnamese science community, have altogether provided reliable sources of information. By emphasizing the need for immediate and genuine cooperation between government, civil society and private individuals, the case study offers valuable lessons for other nations concerning not only the concurrent fight against the COVID-19 pandemic but also the overall responses to a public health crisis.

United Nations’ Sustainable Development Goals 4 Quality Education has highlighted major challenges for all nations to ensure inclusive and equitable quality access to education, facilities for children, and young adults. The SDG4 is even more important for developing nations as receiving proper education or vocational training, especially in science and technology, means a foundational step in improving other aspects of their citizens’ lives. However, the extant scientific literature about STEM education still lacks focus on developing countries, even more so in the rural area. Using a dataset of 4967 observations of junior high school students from a rural area in a transition economy, the article employs the Bayesian approach to identify the interaction between gender, socioeconomic status, and students’ STEM academic achievements. The results report gender has little association with STEM academic achievements; however, female students (αa_Sex[2] = 2.83) appear to have achieved better results than their male counterparts (αa_Sex[1] = 2.68). Families with better economic status, parents with a high level of education (βb(EduMot) = 0.07), or non-manual jobs (αa_SexPJ[4] = 3.25) are found to be correlated with better study results. On the contrary, students with zero (βb(OnlyChi) = -0.14) or more than two siblings (βb(NumberofChi) = -0.01) are correlated with lower study results compared to those with only one sibling. These results imply the importance of providing women with opportunities for better education. Policymakers should also consider maintaining family size so the parents can provide their resources to each child equally.

Universities and funders in many countries have been using Journal Impact Factor (JIF) as an indicator for research and grant assessment despite its controversial nature as a statistical representation of scientific quality. This study investigates how the changes of JIF over the years can affect its role in research evaluation and science management by using JIF data from annual Journal Citation Reports (JCR) to illustrate the changes. The descriptive statistics find out an increase in the median JIF for the top 50 journals in the JCR, from 29.300 in 2017 to 33.162 in 2019. Moreover, on average, elite journal families have up to 27 journals in the top 50. In the group of journals with a JIF of lower than 1, the proportion has shrunk by 14.53% in the 2015–2019 period. The findings suggest a potential ‘JIF bubble period’ that science policymaker, university, public fund managers, and other stakeholders should pay more attention to JIF as a criterion for quality assessment to ensure more efficient science management.