It's clear that, with AI becoming embedded in all aspects of our life, companies need to do more to ensure their systems are free of bias and even find ways to use the technology to help mitigate harmful biases in order to make fairer business decisions. So how do we do that? It starts by building a diverse team, something the industry is still failing to do; according to research published by the AI Now Institute, 80% of AI professors are men, and only 15% of AI researchers at Facebook and 10% of AI researchers at Google are women. Jen Rodvold, head of digital ethics and tech for good at Sopra Steria, comments: "Diversity is key not only to driving a successful AI strategy, but essential to a business' bottom line. A diverse workforce will offer a range of different perspectives, flag any bias involved in the development process and help to interrogate wider organisational processes that could be perpetuating bias and impacting the way your technology is developed in unforeseen ways."

In October 2019, Idaho proposed changing its Medicaid program. The state needed approval from the federal government, which solicited public feedback via Medicaid.gov. But half came not from concerned citizens or even internet trolls. They were generated by artificial intelligence. And a study found that people could not distinguish the real comments from the fake ones.

A minority of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmit most infections. How does this happen? Sun et al. reconstructed transmission in Hunan, China, up to April 2020. Such detailed data can be used to separate out the relative contribution of transmission control measures aimed at isolating individuals relative to population-level distancing measures. The authors found that most of the secondary transmissions could be traced back to a minority of infected individuals, and well over half of transmission occurred in the presymptomatic phase. Furthermore, the duration of exposure to an infected person combined with closeness and number of household contacts constituted the greatest risks for transmission, particularly when lockdown conditions prevailed. These findings could help in the design of infection control policies that have the potential to minimize both virus transmission and economic strain. Science , this issue p. [eabe2424][1] ### INTRODUCTION The role of transmission heterogeneities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dynamics remains unclear, particularly those heterogeneities driven by demography, behavior, and interventions. To understand individual heterogeneities and their effect on disease control, we analyze detailed contact-tracing data from Hunan, a province in China adjacent to Hubei and one of the first regions to experience a SARS-CoV-2 outbreak in January to March 2020. The Hunan outbreak was swiftly brought under control by March 2020 through a combination of nonpharmaceutical interventions including population-level mobility restriction (i.e., lockdown), traveler screening, case isolation, contact tracing, and quarantine. In parallel, highly detailed epidemiological information on SARS-CoV-2–infected individuals and their close contacts was collected by the Hunan Provincial Center for Disease Control and Prevention. ### RATIONALE Contact-tracing data provide information to reconstruct transmission chains and understand outbreak dynamics. These data can in turn generate valuable intelligence on key epidemiological parameters and risk factors for transmission, which paves the way for more-targeted and cost-effective interventions. ### RESULTS On the basis of epidemiological information and exposure diaries on 1178 SARS-CoV-2–infected individuals and their 15,648 close contacts, we developed a series of statistical and computational models to stochastically reconstruct transmission chains, identify risk factors for transmission, and infer the infectiousness profile over the course of a typical infection. We observe overdispersion in the distribution of secondary infections, with 80% of secondary cases traced back to 15% of infections, which indicates substantial transmission heterogeneities. We find that SARS-CoV-2 transmission risk scales positively with the duration of exposure and the closeness of social interactions, with the highest per-contact risk estimated in the household. Lockdown interventions increase transmission risk in families and households, whereas the timely isolation of infected individuals reduces risk across all types of contacts. There is a gradient of increasing susceptibility with age but no significant difference in infectivity by age or clinical severity. Early isolation of SARS-CoV-2–infected individuals drastically alters transmission kinetics, leading to shorter generation and serial intervals and a higher fraction of presymptomatic transmission. After adjusting for the censoring effects of isolation, we find that the infectiousness profile of a typical SARS-CoV-2 patient peaks just before symptom onset, with 53% of transmission occurring in the presymptomatic phase in an uncontrolled setting. We then use these results to evaluate the effectiveness of individual-based strategies (case isolation and contact quarantine) both alone and in combination with population-level contact reductions. We find that a plausible parameter space for SARS-CoV-2 control is restricted to scenarios where interventions are synergistically combined, owing to the particular transmission kinetics of this virus. ### CONCLUSION There is considerable heterogeneity in SARS-CoV-2 transmission owing to individual differences in biology and contacts that is modulated by the effects of interventions. We estimate that about half of secondary transmission events occur in the presymptomatic phase of a primary case in uncontrolled outbreaks. Achieving epidemic control requires that isolation and contact-tracing interventions are layered with population-level approaches, such as mask wearing, increased teleworking, and restrictions on large gatherings. Our study also demonstrates the value of conducting high-quality contact-tracing investigations to advance our understanding of the transmission dynamics of an emerging pathogen. ![Figure][2] Transmission chains, contact patterns, and transmission kinetics of SARS-CoV-2 in Hunan, China, based on case and contact-tracing data from Hunan, China. (Top left) One realization of the reconstructed transmission chains, with a histogram representing overdispersion in the distribution of secondary infections. (Top right) Contact matrices of community, social, extended family, and household contacts reveal distinct age profiles. (Bottom) Earlier isolation of primary infections shortens the generation and serial intervals while increasing the relative contribution of transmission in the presymptomatic phase. A long-standing question in infectious disease dynamics concerns the role of transmission heterogeneities, which are driven by demography, behavior, and interventions. On the basis of detailed patient and contact-tracing data in Hunan, China, we find that 80% of secondary infections traced back to 15% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primary infections, which indicates substantial transmission heterogeneities. Transmission risk scales positively with the duration of exposure and the closeness of social interactions and is modulated by demographic and clinical factors. The lockdown period increases transmission risk in the family and households, whereas isolation and quarantine reduce risks across all types of contacts. The reconstructed infectiousness profile of a typical SARS-CoV-2 patient peaks just before symptom presentation. Modeling indicates that SARS-CoV-2 control requires the synergistic efforts of case isolation, contact quarantine, and population-level interventions because of the specific transmission kinetics of this virus. [1]: /lookup/doi/10.1126/science.abe2424 [2]: pending:yes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence peaked in Manaus, Brazil, in May 2020 with a devastating toll on the city's inhabitants, leaving its health services shattered and cemeteries overwhelmed. Buss et al. collected data from blood donors from Manaus and São Paulo, noted when transmission began to fall, and estimated the final attack rates in October 2020 (see the Perspective by Sridhar and Gurdasani). Heterogeneities in immune protection, population structure, poverty, modes of public transport, and uneven adoption of nonpharmaceutical interventions mean that despite a high attack rate, herd immunity may not have been achieved. This unfortunate city has become a sentinel for how natural population immunity could influence future transmission. Events in Manaus reveal what tragedy and harm to society can unfold if this virus is left to run its course. Science , this issue p. [288][1]; see also p. [230][2] Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly in Manaus, the capital of Amazonas state in northern Brazil. The attack rate there is an estimate of the final size of the largely unmitigated epidemic that occurred in Manaus. We use a convenience sample of blood donors to show that by June 2020, 1 month after the epidemic peak in Manaus, 44% of the population had detectable immunoglobulin G (IgG) antibodies. Correcting for cases without a detectable antibody response and for antibody waning, we estimate a 66% attack rate in June, rising to 76% in October. This is higher than in São Paulo, in southeastern Brazil, where the estimated attack rate in October was 29%. These results confirm that when poorly controlled, COVID-19 can infect a large proportion of the population, causing high mortality. [1]: /lookup/doi/10.1126/science.abe9728 [2]: /lookup/doi/10.1126/science.abf7921

Thermal screening to spot people infected with coronavirus is more reliable when scanning the eyeball and fingertip than taking body or forehead measurements. Experts in human physiology published a scientific article on the usefulness of thermometers which scan a person's skin to detect a fever. They say the current process is fundamentally flawed and produces a large number of false negatives, as well as some false positives, and also because not all people infected with the coronavirus develop a fever. A fever is defined as a temperature of greater than or equal to 100.4F (38 C) if spotted outside of a healthcare environment. In healthcare settings, such as a hospital, a fever is technically defined as anything greater than or equal to 100.0F (37.8 C).

Scientists from the Max Planck Institute of Psychiatry, led by Nikolaos Koutsouleris, combined psychiatric assessments with machine-learning models that analyze clinical and biological data. Although psychiatrists make very accurate predictions about positive disease outcomes, they might underestimate the frequency of adverse cases that lead to relapses. The algorithmic pattern recognition helps physicians to better predict the course of disease. The results of the study show that it is the combination of artificial and human intelligence that optimizes the prediction of mental illness. "This algorithm enables us to improve the prevention of psychosis, especially in young patients at high risk or with emerging depression, and to intervene in a more targeted and well-timed manner" explains Koutsouleris.

The Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE) taskforce on AI & COVID-19 supported the creation of a research group focused on AI-assisted diagnosis of COVID-19 pneumonia. The first results demonstrate the great potential of AI-assisted diagnostic imaging. Furthermore, the impact of the taskforce work is much larger, and it embraces the cross-fertilisation of artificial intelligence (AI) and high-performance computing (HPC): a partnership with rocketing potential for many scientific domains. Through several initiatives aimed at improving the knowledge of COVID-19, containing its diffusion, and limiting its effects, CLAIRE's COVID-19 taskforce was able to organise 150 volunteer scientists, divided into seven groups covering different aspects of how AI could be used to tackle the pandemic. Emanuela Girardi, the co-coordinator of the CLAIRE taskforce on AI & COVID-19, supported the setup of a novel European group to study the diagnosis of COVID-19 pneumonia assisted by artificial intelligence.

Empathic behaviors play crucial roles in human society by regulating social interactions, promoting cooperation toward a common goal, and providing the basis for moral decision-making ([ 1 ][1], [ 2 ][2]). Understanding the neural basis of empathy is crucial to understanding not only the human mind but also the neural mechanisms that give rise to social behaviors and the principles of our societies. Functional imaging studies in humans have identified essential brain regions that are engaged when people empathize with the affective experiences of others. However, human neuroimaging studies provide only limited spatial resolution and are solely correlative in nature. It has thus remained unclear how empathy with distinct affective experiences is set apart within the brain. On page 153 of this issue, Smith et al. ([ 3 ][3]) investigated the social transfer of pain, pain relief, or fear in mice to address how the sharing of diverse affective states is differentiated within the brain. Although long thought of as an exclusively human ability, a basic requirement for empathy is “the ability to share the affective state of others” ([ 4 ][4], [ 5 ][5]). It was proposed that empathy can be viewed as a multilevel process, in which the simplest form—namely, adopting another's affective state (emotion contagion)—lies at the core of all empathic behaviors. More complex levels of empathy, including prosocial behaviors and learning from the state of the other, evolved later and build on this core of affect sharing ([ 4 ][4], [ 5 ][5]). According to this definition, there is ample evidence that many animal species exhibit primitive forms of empathy, suggesting that the building blocks of human empathy are deeply rooted in evolution. ![Figure][6] Empathy circuits in mice Smith et al. induced three different affective states in demonstrator mice and investigated the neuronal pathways required in the observer mice to share the diverse affective states of the other. Although the pathway from the anterior cingulate cortex (ACC) to the nucleus accumbens (NAc) was essential for the transfer of both pain and pain relief, a neuronal pathway from the ACC to the basolateral amygdala (BLA) mediated the social transfer of fear. GRAPHIC: KELLIE HOLOSKI/ SCIENCE To date, numerous studies have demonstrated that rodents also express empathic behaviors, including emotion contagion, but also observational affective learning, or prosocial behaviors such as consolation or helping behaviors ([ 6 ][7]–[ 8 ][8]). Furthermore, homologous brain regions have consistently been described to underlie empathy in humans and animals. One of the most consistently found brain regions in humans and rodents, the anterior cingulate cortex (ACC), has been shown to be involved when empathizing with different sensory and affective states, including pain, disgust, or fear ([ 9 ][9]–[ 14 ][10]). However, whether the ACC contributes to discrimination of the transfer of different affective states that elicit distinct empathic behaviors is an important unanswered issue. Smith et al. demonstrate that the social transfer of pain or fear are mediated by two separate projections from the ACC to distinct subcortical targets in mice (see the figure). Social transfer of pain refers to the phenomenon that a brief exposure to a conspecific (an animal of the same species) who is experiencing pain will lead to a transfer of the same emotion state to the observer. As a result, the observer, who has not experienced any pain itself, is more sensitive to painful stimuli and experiences pain more easily, a phenomenon called hyperalgesia. Similarly, observing a conspecific being in fear will transfer and induce fear reactions in the observer. Using these primitive forms of empathy-like behaviors in mice, Smith et al. demonstrate that social transfer of pain relied on a neural pathway from the ACC to the nucleus accumbens (NAc) in the observer mouse. However, this pathway was not required for the social transfer of fear, which involved a separate pathway from the ACC to the basolateral amygdala (BLA). Notably, the authors also found that a positive affective state, the relief from pain, could be socially transmitted. Observer mice who were in pain themselves exhibited lessened pain responses when they had a chance to observe other mice that had undergone pain-relief treatment with morphine. A deeper understanding of how and why analgesia can be transmitted socially may well have important future implications for pain management in humans. The authors report that the same neuronal pathway from the ACC to the NAc is involved in both the socially mediated positive and negative modulation of subjective pain. How does this single neuronal pathway drive socially transferred analgesia and hyperalgesia at the same time? Perhaps different cell types are targeted in the NAc, which affect distinct downstream brain regions. Understanding this will be an important matter for future studies. Disentangling the circuits for social transmission more generally for positive versus negative affective states may improve our understanding of social and emotion disorders in humans. The findings of Smith et al. also raise the question of whether the ACC-to-BLA fear projection might be involved not only in the social transfer of fear but also in the “relief from fear.” It has already been shown that mice are able to reduce their fear behavior in the presence of a nonfearful partner ([ 6 ][7], [ 15 ][11]). However, the neuronal basis of this social buffering of fear remains elusive. The ACC-to-BLA projection may be a promising candidate for this phenomenon. One of the most accepted theories for the neuronal mechanisms of empathy is the “perception-action model” (PAM) ([ 4 ][4], [ 5 ][5]). According to this view, attending to another's affective state is assumed to activate the observer's own neuronal representation and associated feelings of the same state. Smith et al. could show that a socially shared emotion causes a generalized pain state in the observer. Both hyperalgesia and analgesia modulated different forms of pain sensitivity and affected the entire body of the observer mouse, suggesting that the observer mouse may truly experience a generalized change of internal state. Indeed, studies in monkeys and rodents have demonstrated the existence of “mirror neurons” in the ACC. These are single nerve cells that are activated both when an individual observes a sensory experience or motor action, or experiences or performs the same condition itself. 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Physiological functions of the microtubule cytoskeleton are expected to be regulated by a variety of posttranslational tubulin modifications. For instance, tubulin glycylation is almost exclusively found in cilia and flagella, but its role in the function of these organelles remains unclear. Gadadhar et al. now demonstrate in mice that glycylation, although nonessential for the formation of cilia and flagella, coordinates the beat waveform of sperm flagella. This activity is a prerequisite for progressive sperm swimming and thus for male fertility. At the ultrastructural level, lack of glycylation perturbed the distribution of axonemal dynein conformations, which may explain the observed defects in flagellar beat. Science , this issue p. [eabd4914][1] ### INTRODUCTION Microtubules are key components of the eukaryotic cytoskeleton. Although they are involved in a wide variety of functions, microtubules are structurally highly similar across most cell types and organisms. It was suggested that a “tubulin code,” formed by combinations of tubulin posttranslational modifications, adapts individual microtubules to specific functions within living cells. However, clear-cut functional and mechanistic data verifying this concept are still scarce. Glycylation is among the least explored posttranslational modifications of tubulin and has, so far, exclusively been found on microtubules of cilia and flagella from a variety of species. Previous work has suggested that glycylation might be essential for cilia and flagella, but mechanistic insight remains lacking. ### RATIONALE Two enzymes from the tubulin-tyrosine ligase-like (TTLL) family, TTLL3 and TTLL8, are essential to initiate glycylation of tubulin in mammals. To entirely abolish glycylation at the organism level and to determine its physiological function, we generated a double-knockout mouse lacking both glycylating enzymes ( Ttll3−/−Ttll8−/− ). Inactivation of these two enzymes led to a lack of glycylation in all analyzed cilia and flagella. This allowed us to investigate the role of glycylation in the function of these organelles. ### RESULTS Despite the absence of glycylation in Ttll3−/−Ttll8−/− mice, no gross defects were observed at the organism and tissue levels. Motile ependymal cilia in brain ventricles as well as motile cilia in the respiratory tract were present and appeared normal. Sperm flagella were also assembled normally, and sperm were able to swim. However, in vitro fertility assays showed that male Ttll3−/−Ttll8−/− mice were subfertile. Computer-assisted sperm analyses revealed motility defects of Ttll3−/−Ttll8−/− sperm. Further analyses showed that lack of glycylation leads to perturbed flagellar beat patterns, causing Ttll3−/−Ttll8−/− sperm to swim predominantly along circular paths. This is highly unusual for mammalian sperm and interferes with their ability to reach the oocyte for fertilization. To determine the molecular mechanisms underlying this aberrant flagellar beat, we used cryo–electron tomography. The three-dimensional structure of the 96-nm repeat of the Ttll3−/−Ttll8−/− sperm axoneme showed no aberrations in its overall assembly. By contrast, the structure of both outer and inner dynein arms (ODAs and IDAs) was perturbed in Ttll3−/−Ttll8−/− flagella. Classification analysis showed that the incidence and distribution of pre-powerstroke and post-powerstroke conformations of ODAs and IDAs were altered in Ttll3−/−Ttll8−/− sperm. These ultrastructural findings indicate that glycylation is required to efficiently control the dynein powerstroke cycle, which is essential for the generation of a physiological flagellar beat. ### CONCLUSION Our work shows that tubulin glycylation regulates the beat of mammalian flagella by modulating axonemal dynein motor activity. Lack of glycylation leads to perturbed sperm motility and male subfertility in mice. Considering that human sperm are more susceptible than mouse sperm to deficiencies in sperm motility, our findings imply that a perturbation of tubulin glycylation could underlie some forms of male infertility in humans. ![Figure][2] Tubulin glycylation controls sperm motility. ( A ) Microtubules in sperm flagella are rich in tubulin posttranslational modifications. Mice deficient for the glycylating enzymes TTLL3 and TTLL8 lack glycylation. ( B ) Mammalian sperm swim in linear paths. In the absence of glycylation, abnormal, mostly circular swimming patterns are observed, which impede progressive swimming. ( C ) Absence of glycylation leads to perturbed distribution of axonemal dynein conformations in Ttll3−/−Ttll8−/− flagella, which impedes normal flagellar beating. Posttranslational modifications of the microtubule cytoskeleton have emerged as key regulators of cellular functions, and their perturbations have been linked to a growing number of human pathologies. Tubulin glycylation modifies microtubules specifically in cilia and flagella, but its functional and mechanistic roles remain unclear. In this study, we generated a mouse model entirely lacking tubulin glycylation. Male mice were subfertile owing to aberrant beat patterns of their sperm flagella, which impeded the straight swimming of sperm cells. Using cryo–electron tomography, we showed that lack of glycylation caused abnormal conformations of the dynein arms within sperm axonemes, providing the structural basis for the observed dysfunction. Our findings reveal the importance of microtubule glycylation for controlled flagellar beating, directional sperm swimming, and male fertility. [1]: /lookup/doi/10.1126/science.abd4914 [2]: pending:yes

As research pushes the boundaries of what's possible with AI, the popularity of art created by algorithms -- generative art -- continues to grow. From creating paintings to inventing new art styles, AI-based generative art has been showcased in a range of applications. But a new study from researchers at Fujitsu investigates whether biases might creep into the AI tools used to create art. Leveraging models, they claim that current AI methods fail to take into account socioeconomic impacts and exhibit clear prejudices. In their work, the researchers surveyed academic papers, online platforms, and apps that generate art using AI, selecting examples that focused on simulating established art schools and styles.