When combinations of humans and AI are useful: A systematic review and meta-analysis.

Inspired by the increasing use of artificial intelligence (AI) to augment humans, researchers have studied human-AI systems involving different tasks, systems and populations. Despite such a large body of work, we lack a broad conceptual understanding of when combinations of humans and AI are better than either alone. Here we addressed this question by conducting a preregistered systematic review and meta-analysis of 106 experimental studies reporting 370 effect sizes.

Too much focus on your health might be bad for your health: Reddit user's communication style predicts their Long COVID likelihood.

Long Covid is a chronic disease that affects more than 65 million people worldwide, characterized by a wide range of persistent symptoms following a Covid-19 infection. Previous studies have investigated potential risk factors contributing to elevated vulnerability to Long Covid. However, research on the social traits associated with affected patients is scarce.

Can Plants Perceive Human Gestures? Using AI to Track Eurythmic Human-Plant Interaction.

This paper explores if plants are capable of responding to human movement by changes in their electrical signals. Toward that goal, we conducted a series of experiments, where humans over a period of 6 months were performing different types of eurythmic gestures in the proximity of garden plants, namely salad, basil, and tomatoes. To measure plant perception, we used the plant SpikerBox, which is a device that measures changes in the voltage differentials of plants between roots and leaves.

Leveraging the Sensitivity of Plants with Deep Learning to Recognize Human Emotions.

Recent advances in artificial intelligence combined with behavioral sciences have led to the development of cutting-edge tools for recognizing human emotions based on text, video, audio, and physiological data. However, these data sources are expensive, intrusive, and regulated, unlike plants, which have been shown to be sensitive to human steps and sounds. A methodology to use plants as human emotion detectors is proposed.

A taste of ambrosia: Do Olympic medalists live longer than Olympic losers?

Objective: To investigate the longevity of a large sample of Olympic Games participants, considering the interaction between different types of sports and medal awards.

Methodolgy: Data scraping from Wikipedia and Wikidata allowed us to collect a sample of 102,993 famous athletes. We selected 20 of the most populated disciplines to make the groups comparable.

Can Plants Sense Humans? Using Plants as Biosensors to Detect the Presence of Eurythmic Gestures.

This paper describes the preliminary results of measuring the impact of human body movements on plants. The scope of this project is to investigate if a plant perceives human activity in its vicinity. In particular, we analyze the influence of eurythmic gestures of human actors on lettuce and beans.

Comparing Synchronicity in Body Movement among Jazz Musicians with Their Emotions.

This paper presents novel preliminary research that investigates the relationship between the flow of a group of jazz musicians, quantified through multi-person pose synchronization, and their collective emotions. We have developed a real-time software to calculate the physical synchronicity of team members by tracking the difference in arm, leg, and head movements using Lightweight OpenPose. We employ facial expression recognition to evaluate the musicians' collective emotions.

Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing.

Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use.

Measuring ethical behavior with AI and natural language processing to assess business success.

Everybody claims to be ethical. However, there is a huge difference between declaring ethical behavior and living up to high ethical standards. In this paper, we demonstrate that "hidden honest signals" in the language and the use of "small words" can show true moral values and behavior of individuals and organizations and that this ethical behavior is correlated to real-world success; however not always in the direction we might expect.

A Social Network Analysis of Tweets Related to Mandatory COVID-19 Vaccination in Poland.

Poland's efforts to combat COVID-19 were hindered by endemic vaccination hesitancy and the prevalence of opponents to pandemic restrictions. In this environment, the policy of a COVID-19 vaccination mandate faces strong resistance in the public debate. Exploring the discourse around this resistance could help uncover the motives and develop an understanding of vaccination hesitancy in Poland.

Organiational Structure and Created Values. Review of Methods of Studying Collective Intelligence in Policymaking.

The domain of policymaking, which used to be limited to small groups of specialists, is now increasingly opening up to the participation of wide collectives, which are not only influencing government decisions, but also enhancing citizen engagement and transparency, improving service delivery and gathering the distributed wisdom of diverse participants. Although collective intelligence has become a more common approach to policymaking, the studies on this subject have not been conducted in a systematic way. Nevertheless, we hypothesized that methods and strategies specific to different types of studies in this field could be identified and analyzed.

Quantifying collective intelligence in human groups.

Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group's ability to work together across a diverse set of tasks.

Managing the COVID-19 emergency: A coordination framework to enhance response practices and actions.

The global outbreak of the coronavirus pneumonia (COVID-19) showed how epidemics today can spread very rapidly, with potentially ruinous impact on economies and societies. Whereas medical research is crucial to define effective treatment protocols, technology innovation and social research can contribute by defining effective approaches to emergency management, especially to optimize the complex dynamics arising within actors and systems during the outbreak. The purpose of this article is to define a framework for modeling activities, actors and resources coordination in the epidemic management scenario, and to reflect on its use to enhance response practices and actions.

"Towards Re-Inventing Psychohistory": Predicting the Popularity of Tomorrow's News from Yesterday's Twitter and News Feeds.

Rapid advances in machine learning combined with wide availability of online social media have created considerable research activity in predicting what might be the news of tomorrow based on an analysis of the past. In this work, we present a deep learning forecasting framework which is capable to predict tomorrow's news topics on Twitter and news feeds based on yesterday's content and topic-interaction features. The proposed framework starts by generating topics from words using word embeddings and K-means clustering.

Integrated information as a metric for group interaction.

Researchers in many disciplines have previously used a variety of mathematical techniques for analyzing group interactions. Here we use a new metric for this purpose, called "integrated information" or "phi." Phi was originally developed by neuroscientists as a measure of consciousness in brains, but it captures, in a single mathematical quantity, two properties that are important in many other kinds of groups as well: differentiated information and integration.

Dynamics of collective performance in collaboration networks.

Today, many complex tasks are assigned to teams, rather than individuals. One reason for teaming up is expansion of the skill coverage of each individual to the joint team skill set. However, numerous empirical studies of human groups suggest that the performance of equally skilled teams can widely differ.

Co-Designing a Collaborative Chronic Care Network (C3N) for Inflammatory Bowel Disease: Development of Methods.

Background: Our health care system fails to deliver necessary results, and incremental system improvements will not deliver needed change. Learning health systems (LHSs) are seen as a means to accelerate outcomes, improve care delivery, and further clinical research; yet, few such systems exist. We describe the process of codesigning, with all relevant stakeholders, an approach for creating a collaborative chronic care network (C3N), a peer-produced networked LHS.

Exploration of Online Culture Through Network Analysis of Wikipedia.

Understanding online culture is becoming crucial in the global and connected world. Contrary to conventional attitudinal surveys used in cultural research, this study uses the approach of directly observing culture-specific behavior that emerges from online collaboration on the Internet. The editing data of Wikipedia were analyzed in 12 languages.

Reading the Mind in the Eyes or reading between the lines? Theory of Mind predicts collective intelligence equally well online and face-to-face.

Recent research with face-to-face groups found that a measure of general group effectiveness (called "collective intelligence") predicted a group's performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members' ability to reason about the mental states of others (an ability called "Theory of Mind" or "ToM"). Since ToM was measured in this work by a test that requires participants to "read" the mental states of others from looking at their eyes (the "Reading the Mind in the Eyes" test), it is uncertain whether the same results would emerge in online groups where these visual cues are not available.