Conversational AI and equity through assessing GPT-3's communication with diverse social groups on contentious topics.

Autoregressive language models, which use deep learning to produce human-like texts, have surged in prevalence. Despite advances in these models, concerns arise about their equity across diverse populations. While AI fairness is discussed widely, metrics to measure equity in dialogue systems are lacking. This paper presents a framework, rooted in deliberative democracy and science communication studies, to evaluate equity in human-AI communication. Using it, we conducted an algorithm auditing study to examine how GPT-3 responded to different populations who vary in sociodemographic backgrounds and viewpoints on crucial science and social issues: climate change and the Black Lives Matter (BLM) movement. We analyzed 20,000 dialogues with 3290 participants differing in gender, race, education, and opinions. We found a substantively worse user experience among the opinion minority groups (e.g., climate deniers, racists) and the education minority groups; however, these groups changed attitudes toward supporting BLM and climate change efforts much more compared to other social groups after the chat. GPT-3 used more negative expressions when responding to the education and opinion minority groups. We discuss the social-technological implications of our findings for a conversational AI system that centralizes diversity, equity, and inclusion.

Twitter as research data Tools, costs, skill sets, and lessons learned.

Scholars increasingly use Twitter data to study the life sciences and politics. However, Twitter data collection tools often pose challenges for scholars who are unfamiliar with their operation. Equally important, although many tools indicate that they offer representative samples of the full Twitter archive, little is known about whether the samples are indeed representative of the targeted population of tweets. This article evaluates such tools in terms of costs, training, and data quality as a means to introduce Twitter data as a research tool. Further, using an analysis of COVID-19 and moral foundations theory as an example, we compared the distributions of moral discussions from two commonly used tools for accessing Twitter data (Twitter's standard APIs and third-party access) to the ground truth, the Twitter full archive. Our results highlight the importance of assessing the comparability of data sources to improve confidence in findings based on Twitter data. We also review the major new features of Twitter's API version 2.

Narratives in Public Deliberation: Empowering Gene Editing Debate with Storytelling.

Gene editing in the environment must consider uncertainty about potential benefits and risks for different populations and under different conditions. There are disagreements about the weight and balance of harms and benefits. Deliberative and community-led approaches offer the opportunity to engage and empower diverse publics to co-create responses and solutions to controversial policy choices in a manner that is inclusive of diverse perspectives. Stories, understood as situated accounts that reflect a person's life experiences, can enable the articulation of nuanced perspectives, diversify how perspectives are communicated, encourage wider participation, open dominant perspectives to challenge, and invite participants to assess appropriate empathy and precaution in collective positions. An emphasis on storytelling in deliberations on gene editing of organisms emphasizes carefully designed recruitment and facilitation to support hearing from a range of perspectives, including those that present a different set of assumptions than those that may be held by experts or other stakeholders, among these, consideration of how to understand our relationships to nature.

Intracounty modeling of COVID-19 infection with human mobility: Assessing spatial heterogeneity with business traffic, age, and race.

The COVID-19 pandemic is a global threat presenting health, economic, and social challenges that continue to escalate. Metapopulation epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic, and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What's more, variation of intracounty environments creates spatial heterogeneity of transmission in different regions. To address this issue, we develop a human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behaviors. This modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and business foot traffic, race and ethnicity, and age structure are then investigated. The results reveal that, in a college town (Dane County), the most important heterogeneity is age structure, while, in a large city area (Milwaukee County), racial and ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate to various reopening policies, which suggests that policy makers may need to take these heterogeneities into account very carefully when designing policies for mitigating the ongoing spread of COVID-19 and reopening.

How deliberative designs empower citizens' voices: A case study on Ghana's deliberative poll on agriculture and the environment.

Empowering ordinary citizens with the capacity to deliberate is a core issue in science communication. Despite growing deliberative practices in developed nations, it is significantly less understood how public deliberation can happen among populations who live with limited educational resources and poor urban infrastructure in developing countries. This article studied a case of a well-designed deliberation method, Deliberative Poll, in Tamale, Ghana. I analyzed the stimulus information video and thousands of speech acts from deliberation transcripts to examine how expertise was used and what was deliberated in public dialogue. A broad range of expertise and interests were represented. Participants had thoughtful discussions on complex policy issues and their discussion results were considered by local policymakers. This article contributes to our understanding of how to effectively foster public deliberation among populations in the Global South and measure the nuances of expertise and public reasoning on science.

Secondary metabolites from the fermented rice of the fungus Monascus purpureus and their bioactivities.

Phytochemical investigation of the EtOAc-soluble fraction of the ethanolic extract of a yellow mutant of the fungus Monascus purpureus BCRC 38110 (Eurotiaceae) grown on rice resulted in the isolation of one new azaphilone derivative, monapurpureusone (1), one acetophenone metabolite isolated for the first time from natural source, monapurpureusin (2), along with four known compounds, TW94a (3), ergosterol (4), monascin (5), and ankaflavin (6). The structures and relative configurations of these compounds were elucidated by spectroscopic analyses, including 1D- and 2D-NMR spectroscopy and mass spectrometry, and by the comparison of their NMR data with those of related compounds. Some phytochemicals were evaluated for both anti-inflammatory activity through the measurement of nitric oxide (NO) production levels in lipopolysaccharide (LPS)-stimulated murine-derived macrophages RAW264.7 cell lines and antioxidant activities.

Computational design of high efficiency nonplanar tri-s-triazine-based ambipolar host materials for phosphorescent blue emitters.

A series of nonplanar tri-s-triazine-based molecules were designed, and their optical, electronic, and charge transport properties as ambipolar host materials for blue electrophosphorescence emitters were explored by density functional theory. The influence of the linkage between tri-s-triazine and carbazole, diphenylamine and triphenylamine, as well as the influence of a series of electron-donating and electron-withdrawing substituents on triplet energy, energy level matching and charge transport of the designed molecules was discussed in detail. Our results reveal that the molecules under investigation can serve as host materials for blue electrophosphorescence emitters. We also predicted the mobility of designed molecules with better performance in the P1[combining macron] space group. Based on the investigated results, we proposed a rational way for the design of host materials for OLEDs, and also expanded the application field of tri-s-triazine.

Monascusazaphilones A-C, three new azaphilone analogues isolated from the fungus Monascus purpureus BCRC 38108.

Investigation of the 95% EtOH extract of red yeast rice fermented with the pink mutant of the fungus Monascus purpureus BCRC 38108 led to the isolation of three new azaphilone derivatives, namely monascusazaphilones A-C (1-3), together with two known compounds. Compounds 1-3 were isolated from this species for the first time. Their structures were elucidated by 1-D and 2-D nuclear magnetic resonance spectroscopy together with HR-ESI-MS analysis and comparison of the spectroscopic data with those reported in the literatures. All isolates were evaluated for their inhibitory effects on nitric oxide (NO) production by macrophages. Among the isolates, compound 1 demonstrated stronger inhibition on NO production.

Monasnicotinates A-D, four new pyridine alkaloids from the fungal strain Monascus pilosus BCRC 38093.

Four new pyridine derivatives, monasnicotinates A-D (1-4) were isolated from the red yeast rice of Monascus pilosus BCRC 38093. Their structures were elucidated on the basis of physicochemical evidence, in-depth NMR spectroscopic analysis, and high-resolution mass spectrometry. Their inhibitory effects on NO production was also evaluated.