Persistent interaction patterns across social media platforms and over time.

Growing concern surrounds the impact of social media platforms on public discourse1-4 and their influence on social dynamics5-9, especially in the context of toxicity10-12. Here, to better understand these phenomena, we use a comparative approach to isolate human behavioural patterns across multiple social media platforms. In particular, we analyse conversations in different online communities, focusing on identifying consistent patterns of toxic content. Drawing from an extensive dataset that spans eight platforms over 34 years-from Usenet to contemporary social media-our findings show consistent conversation patterns and user behaviour, irrespective of the platform, topic or time. Notably, although long conversations consistently exhibit higher toxicity, toxic language does not invariably discourage people from participating in a conversation, and toxicity does not necessarily escalate as discussions evolve. Our analysis suggests that debates and contrasting sentiments among users significantly contribute to more intense and hostile discussions. Moreover, the persistence of these patterns across three decades, despite changes in platforms and societal norms, underscores the pivotal role of human behaviour in shaping online discourse.

An autonomous debating system.

Artificial intelligence (AI) is defined as the ability of machines to perform tasks that are usually associated with intelligent beings. Argument and debate are fundamental capabilities of human intelligence, essential for a wide range of human activities, and common to all human societies. The development of computational argumentation technologies is therefore an important emerging discipline in AI research1. Here we present Project Debater, an autonomous debating system that can engage in a competitive debate with humans. We provide a complete description of the system's architecture, a thorough and systematic evaluation of its operation across a wide range of debate topics, and a detailed account of the system's performance in its public debut against three expert human debaters. We also highlight the fundamental differences between debating with humans as opposed to challenging humans in game competitions, the latter being the focus of classical 'grand challenges' pursued by the AI research community over the past few decades. We suggest that such challenges lie in the 'comfort zone' of AI, whereas debating with humans lies in a different territory, in which humans still prevail, and for which novel paradigms are required to make substantial progress.

Syllables and their beginnings have a special role in the mental lexicon.

The beginnings of words are, in some informal sense, special. This intuition is widely shared, for example, when playing word games. Less apparent is whether the intuition is substantiated empirically and what the underlying organizational principle(s) might be. Here, we answer this seemingly simple question in a quantitatively clear way. Based on arguments about the interplay between lexical storage and speech processing, we examine whether the distribution of information among different speech sounds of words is governed by a critical computational unit for online speech perception and production: syllables. By analyzing lexical databases of twelve languages, we demonstrate that there is a compelling asymmetry between syllable beginnings (onsets) versus ends (codas) in their involvement in distinguishing words stored in the lexicon. In particular, we show that the functional advantage of syllable onset reflects an asymmetrical distribution of lexical informativeness within the syllable unit but not an effect of a global decay of informativeness from the beginning to the end of a word. The converging finding across languages from a range of typological families supports the conjecture that the syllable unit, while being a critical primitive for both speech perception and production, is also a key organizational constraint for lexical storage.

Human infants are aroused and concerned by moral transgressions.

Humans reason and care about ethical issues, such as avoiding unnecessary harm. But what enables us to develop a moral capacity? This question dates back at least to ancient Greece and typically results in the traditional opposition between sentimentalism (the view that morality is mainly driven by socioaffective processes) and rationalism [the view that morality is mainly driven by (socio)cognitive processes or reason]. Here, we used multiple methods (eye-tracking and observations of expressive behaviors) to assess the role of both cognitive and socioaffective processes in infants' developing morality. We capitalized on the distinction between moral (e.g., harmful) and conventional (e.g., harmless) transgressions to investigate whether 18-mo-old infants understand actions as distinctively moral as opposed to merely disobedient or unexpected. All infants watched the same social scene, but based on prior verbal interactions, an actor's tearing apart of a picture (an act not intrinsically harmful) with a tool constituted either a conventional (wrong tool), a moral (producing harm), or no violation (correct tool). Infants' anticipatory looks differentiated between conventional and no violation conditions, suggesting that they processed the verbal interactions and built corresponding expectations. Importantly, infants showed a larger increase in pupil size (physiological arousal), and more expressions indicating empathic concern, in response to a moral than to a conventional violation. Thus, infants differentiated between harmful and harmless transgressions based solely on prior verbal interactions. Together, these convergent findings suggest that human infants' moral development is fostered by both sociocognitive (inferring harm) and socioaffective processes (empathic concern for others' welfare).

The debate over understanding in AI's large language models.

We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language-and the physical and social situations language encodes-in any humanlike sense. We describe arguments that have been made for and against such understanding and key questions for the broader sciences of intelligence that have arisen in light of these arguments. We contend that an extended science of intelligence can be developed that will provide insight into distinct modes of understanding, their strengths and limitations, and the challenge of integrating diverse forms of cognition.

The build-up of the present-day tropical diversity of tetrapods.

The extraordinary number of species in the tropics when compared to the extra-tropics is probably the most prominent and consistent pattern in biogeography, suggesting that overarching processes regulate this diversity gradient. A major challenge to characterizing which processes are at play relies on quantifying how the frequency and determinants of tropical and extra-tropical speciation, extinction, and dispersal events shaped evolutionary radiations. We address this question by developing and applying spatiotemporal phylogenetic and paleontological models of diversification for tetrapod species incorporating paleoenvironmental variation. Our phylogenetic model results show that area, energy, or species richness did not uniformly affect speciation rates across tetrapods and dispute expectations of a latitudinal gradient in speciation rates. Instead, both neontological and fossil evidence coincide in underscoring the role of extra-tropical extinctions and the outflow of tropical species in shaping biodiversity. These diversification dynamics accurately predict present-day levels of species richness across latitudes and uncover temporal idiosyncrasies but spatial generality across the major tetrapod radiations.

The narrowing of literature use and the restricted mobility of papers in the sciences.

It is a matter of debate whether a shrinking proportion of scholarly literature is getting most of the citations over time. It is also less well understood how a narrowing use of literature would affect the circulation of ideas in the sciences. Here, I show that the utilization of scientific literature follows dual tendencies over time: while a larger proportion of literature is cited at least a few times, citations are also concentrated more at the top of the citation distribution. Parallel to the latter trend, a paper's future importance increasingly depends on its past citation performance. A random network model shows that the citation concentration is directly related to the greater stability of citation performance. The presented evidence suggests that the growing heterogeneity of citation impact restricts the mobility of research articles that do not gain attention early on. While concentration grows from the beginning of the studied period in 1970, citation dispersion manifests itself significantly only from the mid-1990s, when the popularity of freshly published papers also increased. Most likely, advanced information technologies to disseminate papers are behind both of these latter trends.

Gregor Johann Mendel: From peasant to priest, pedagogue, and prelate.

Gregor Mendel was an Augustinian priest in the Monastery of St. Thomas in Brünn (Brno, Czech Republic) as well as a civilian employee who taught natural history and physics in the Brünn Modern School. The monastery's secular function was to provide teachers for the public schools across Moravia. It was a cultural, educational, and artistic center with an elite core of friar-teachers with a well-stocked library and other amenities including a gourmet kitchen. It was wealthy, with far-flung holdings yielding income from agricultural productions. Mendel had failed his tryout as a parish priest and did not complete his examination for teaching certification despite 2 y of study at the University of Vienna. In addition to his teaching and religious obligations, Mendel carried out daily meteorological and astronomical observations, cared for the monastery's fruit orchard and beehives, and tended plants in the greenhouse and small outdoor gardens. In the years 1856 to 1863, he carried out experiments on heredity of traits in garden peas regarded as revolutionary today but not widely recognized during his lifetime and until 16 y after his death. In 1868 he was elected abbot of the monastery, a significantly elevated position in the ecclesiastical and civil hierarchy. While he had hoped to be elected, and was honored to accept, he severely underestimated its administrative responsibilities and gradually had to abandon his scientific interests. The last decade of his life was marred by an ugly dispute with civil authorities over monastery taxation.

Individuals prefer to harm their own group rather than help an opposing group.

Group-based conflict enacts a severe toll on society, yet the psychological factors governing behavior in group conflicts remain unclear. Past work finds that group members seek to maximize relative differences between their in-group and out-group ("in-group favoritism") and are driven by a desire to benefit in-groups rather than harm out-groups (the "in-group love" hypothesis). This prior research studies how decision-makers approach trade-offs between two net-positive outcomes for their in-group. However, in the real world, group members often face trade-offs between net-negative options, entailing either losses to their group or gains for the opposition. Anecdotally, under such conditions, individuals may avoid supporting their opponents even if this harms their own group, seemingly inconsistent with "in-group love" or a harm minimizing strategy. Yet, to the best of our knowledge, these circumstances have not been investigated. In six pre-registered studies, we find consistent evidence that individuals prefer to harm their own group rather than provide even minimal support to an opposing group across polarized issues (abortion access, political party, gun rights). Strikingly, in an incentive-compatible experiment, individuals preferred to subtract more than three times as much from their own group rather than support an opposing group, despite believing that their in-group is more effective with funds. We find that identity concerns drive preferences in group decision-making, and individuals believe that supporting an opposing group is less value-compatible than harming their own group. Our results hold valuable insights for the psychology of decision-making in intergroup conflict as well as potential interventions for conflict resolution.

Opposition to voluntary and mandated COVID-19 vaccination as a dynamic process: Evidence and policy implications of changing beliefs.

SignificanceThe challenge of securing adherence to public health policies is compounded when an emerging threat and a set of unprecedented remedies are not fully understood among the general public. The evolution of citizens' attitudes toward vaccination during the COVID-19 pandemic offers psychologically and sociologically grounded insights that enrich the conventional incentives- and constraints-based approach to policy design. We thus contribute to a behavioral science of policy compliance during public health emergencies of the kind that we may increasingly face in the future. From early in the pandemic, we have tracked the same individuals, providing a lens into the conditions under which people's attitudes toward voluntary and mandated vaccinations change, providing essential information for COVID-19 policy not available from cross-section data.

Disagreement Gets Mistaken for Bad Listening.

It is important for people to feel listened to in professional and personal communications, and yet they can feel unheard even when others have listened well. We propose that this feeling may arise because speakers conflate agreement with listening quality. In 11 studies (N = 3,396 adults), we held constant or manipulated a listener's objective listening behaviors, manipulating only after the conversation whether the listener agreed with the speaker. Across various topics, mediums (e.g., video, chat), and cues of objective listening quality, speakers consistently perceived disagreeing listeners as worse listeners. This effect persisted after controlling for other positive impressions of the listener (e.g., likability). This effect seemed to emerge because speakers believe their views are correct, leading them to infer that a disagreeing listener must not have been listening very well. Indeed, it may be prohibitively difficult for someone to simultaneously convey that they disagree and that they were listening.