skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Social dimensions of fertility behavior and consumption patterns in the Anthropocene
We consider two aspects of the human enterprise that profoundly affect the global environment: population and consumption. We show that fertility and consumption behavior harbor a class of externalities that have not been much noted in the literature. Both are driven in part by attitudes and preferences that are not egoistic but socially embedded; that is, each household’s decisions are influenced by the decisions made by others. In a famous paper, Garrett Hardin [G. Hardin, Science 162, 1243–1248 (1968)] drew attention to overpopulation and concluded that the solution lay in people “abandoning the freedom to breed.” That human attitudes and practices are socially embedded suggests that it is possible for people to reduce their fertility rates and consumption demands without experiencing a loss in wellbeing. We focus on fertility in sub-Saharan Africa and consumption in the rich world and argue that bottom-up social mechanisms rather than top-down government interventions are better placed to bring about those ecologically desirable changes.  more » « less
Award ID(s):
1636476
PAR ID:
10212869
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; ; « less
Date Published:
Journal Name:
Proceedings of the National Academy of Sciences
Volume:
117
Issue:
12
ISSN:
0027-8424
Page Range / eLocation ID:
6300 to 6307
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. During emergencies, it is often necessary to evacuate vulnerable people to safer places to reduce loss of lives and cope with human suffering. Shelters are publically available places to evacuate, especially for people who do not have any other choices. This paper overviews emergency shelter planning in disaster mitigation and preparation and discusses the need for better responding to people who need to evacuate during emergencies. Recent evacuation studies pay attention to integrating social factors into evacuation modeling for better prediction of evacuation decisions. Our goal is to address the impact of social behavior on the sheltering choices of evacuees and to explore the potential contributions of including social network characteristics in the decision-making process of authorities. We present the shelter utilization problem in South Carolina during Hurricane Florence and discuss an agent-based modeling approach that considers social community structures in modeling the shelter choice behavior of socially connected individuals 
    more » « less
  2. null (Ed.)
    Mobile robots are increasingly populating homes, hospitals, shopping malls, factory floors, and other human environments. Human society has social norms that people mutually accept; obeying these norms is an essential signal that someone is participating socially with respect to the rest of the population. For robots to be socially compatible with humans, it is crucial for robots to obey these social norms. In prior work, we demonstrated a Socially-Aware Navigation (SAN) planner, based on Pareto Concavity Elimination Transformation (PaCcET), in a hallway scenario, optimizing two objectives so the robot does not invade the personal space of people. This article extends our PaCcET-based SAN planner to multiple scenarios with more than two objectives. We modified the Robot Operating System’s (ROS) navigation stack to include PaCcET in the local planning task. We show that our approach can accommodate multiple Human-Robot Interaction (HRI) scenarios. Using the proposed approach, we achieved successful HRI in multiple scenarios such as hallway interactions, an art gallery, waiting in a queue, and interacting with a group. We implemented our method on a simulated PR2 robot in a 2D simulator (Stage) and a pioneer-3DX mobile robot in the real-world to validate all the scenarios. A comprehensive set of experiments shows that our approach can handle multiple interaction scenarios on both holonomic and non-holonomic robots; hence, it can be a viable option for a Unified Socially-Aware Navigation (USAN). 
    more » « less
  3. We propose VLM-Social-Nav, a novel Vision-Language Model (VLM) based navigation approach to compute a robot's motion in human-centered environments. Our goal is to make real-time decisions on robot actions that are socially compliant with human expectations. We utilize a perception model to detect important social entities and prompt a VLM to generate guidance for socially compliant robot behavior. VLM-Social-Nav uses a VLM-based scoring module that computes a cost term that ensures socially appropriate and effective robot actions generated by the underlying planner. Our overall approach reduces reliance on large training datasets and enhances adaptability in decision-making. In practice, it results in improved socially compliant navigation in human-shared environments. We demonstrate and evaluate our system in four different real-world social navigation scenarios with a Turtlebot robot. We observe at least 27.38% improvement in the average success rate and 19.05% improvement in the average collision rate in the four social navigation scenarios. Our user study score shows that VLM-Social-Nav generates the most socially compliant navigation behavior. 
    more » « less
  4. Abstract Global change is increasing the frequency and severity of human‐wildlife interactions by pushing people and wildlife into increasingly resource‐limited shared spaces. To understand the dynamics of human‐wildlife interactions and what may constitute human‐wildlife coexistence in the Anthropocene, there is a critical need to explore the spatial, temporal, sociocultural and ecological variables that contribute to human‐wildlife conflicts in urban areas.Due to their opportunistic foraging and behavioural flexibility, coyotes (Canis latrans) frequently interact with people in urban environments. San Francisco, California, USA hosts a very high density of coyotes, making it an excellent region for analysing urban human‐coyote interactions and attitudes toward coyotes over time and space.We used a community‐curated long‐term data source from San Francisco Animal Care and Control to summarise a decade of coyote sightings and human‐coyote interactions in San Francisco and to characterise spatiotemporal patterns of attitudes and interaction types in relation to housing density, socioeconomics, pollution and human vulnerability metrics, and green space availability.We found that human‐coyote conflict reports have been significantly increasing over the past 5 years and that there were more conflicts during the coyote pup‐rearing season (April–June), the dry season (June–September) and the COVID‐19 pandemic. Conflict reports were also more likely to involve dogs and occur inside of parks, despite more overall sightings occurring outside of parks. Generalised linear mixed models revealed that conflicts were more likely to occur in places with higher vegetation greenness and median income. Meanwhile reported coyote boldness, hazing and human attitudes toward coyotes were also correlated with pollution burden and human population vulnerability indices.Synthesis and applications: Our results provide compelling evidence suggesting that human‐coyote conflicts are intimately associated with social‐ecological heterogeneities and time, emphasizing that the road to coexistence will require socially informed strategies. Additional long‐term research articulating how the social‐ecological drivers of conflict (e.g. human food subsidies, interactions with domestic species, climate‐induced droughts, socioeconomic disparities, etc.) change over time will be essential in building adaptive management efforts that effectively mitigate future conflicts from occurring. Read the freePlain Language Summaryfor this article on the Journal blog. 
    more » « less
  5. Recently, there has been a proliferation of personal health applications describing to use Artificial Intelligence (AI) to assist health consumers in making health decisions based on their data and algorithmic outputs. However, it is still unclear how such descriptions influence individuals' perceptions of such apps and their recommendations. We therefore investigate how current AI descriptions influence individuals' attitudes towards algorithmic recommendations in fertility self-tracking through a simulated study using three versions of a fertility app. We found that participants preferred AI descriptions with explanation, which they perceived as more accurate and trustworthy. Nevertheless, they were unwilling to rely on these apps for high-stakes goals because of the potential consequences of a failure. We then discuss the importance of health goals for AI acceptance, how literacy and assumptions influence perceptions of AI descriptions and explanations, and the limitations of transparency in the context of algorithmic decision-making for personal health. 
    more » « less