Anticipatory Thinking Challenges in Open Worlds: Risk Management

Anticipatory thinking drives our ability to manage risk - identification and mitigation - in everyday life, from bringing an umbrella when it might rain to buying car insurance. As AI systems become part of everyday life, they too have begun to manage risk. Autonomous vehicles log millions of miles, StarCraft and Go agents have similar capabilities to humans, implicitly managing risks presented by their opponents. To further increase performance in these tasks, out-of-distribution evaluation can characterize a model's bias, what we view as a type of risk management. However, learning to identify and mitigate low-frequency, high-impact risks is at odds with the observational bias required to train machine learning models. StarCraft and Go are closed-world domains whose risks are known and mitigations well documented, ideal for learning through repetition. Adversarial filtering datasets provide difficult examples but are laborious to curate and static, both barriers to real-world risk management. Adversarial robustness focuses on model poisoning under the assumption there is an adversary with malicious intent, without considering naturally occurring adversarial examples. These methods are all important steps towards improving risk management but do so without considering open-worlds. We unify these open-world risk management challenges with two contributions. The first is our perception challenges, designed for agents with imperfect perceptions of their environment whose consequences have a high impact. Our second contribution are cognition challenges, designed for agents that must dynamically adjust their risk exposure as they identify new risks and learn new mitigations. Our goal with these challenges is to spur research into solutions that assess and improve the anticipatory thinking required by AI agents to manage risk in open-worlds and ultimately the real-world.Comment: 4 pages, 3 figures, appeared in the non-archival AAAI 2022 Spring Syposium on "Designing Artificial Intelligence for Open Worlds

Towards a fuller understanding of neurons with Clustered Compositional Explanations

Compositional Explanations is a method for identifying logical formulas of concepts that approximate the neurons' behavior. However, these explanations are linked to the small spectrum of neuron activations (i.e., the highest ones) used to check the alignment, thus lacking completeness. In this paper, we propose a generalization, called Clustered Compositional Explanations, that combines Compositional Explanations with clustering and a novel search heuristic to approximate a broader spectrum of the neurons' behavior. We define and address the problems connected to the application of these methods to multiple ranges of activations, analyze the insights retrievable by using our algorithm, and propose desiderata qualities that can be used to study the explanations returned by different algorithms.Comment: Accepted at NeurIPS 202

Monitoring Scene Understanders with Conceptual Primitive Decomposition and Commonsense Knowledge

Although there have been many key advancements in connecting text and perception, computer- generated image captions still lack common sense. As a first step towards constraining these perception mechanisms to commonsense judgment, we have developed reasonableness monitors: a wrapper interface that can explain if the descriptive output of an opaque deep neural network is plausible. These monitor a standalone system that uses careful dependency tracking, commonsense knowledge, and conceptual primitives to explain a perceived scene description to be reasonable or not. If such an explanation cannot be made, it is evidence that something unreasonable has been perceived. The development of reasonableness monitors is work towards generalizing that vision, with the intention of developing a system-construction methodology that enhances robustness at run time by dynamic checking and explaining of the behaviors of scene understanders for reasonableness in contex

The effect of sexual selection on adaptation and extinction under increasing temperatures

Strong sexual selection has been reported to both enhance and hinder the adaptive capacity and persistence of populations when exposed to novel environments. Consequently, how sexual selection influences population adaption and persistence under stress remains widely debated. Here we present two empirical investigations of the fitness consequences of sexual selection on populations of the Indian meal moth, Plodia interpunctella, exposed to stable or gradually increasing temperatures. When faced with increasing temperatures strong sexual selection was associated with both increased fecundity and offspring survival compared to populations experiencing weak sexual selection, suggesting sexual selection acts to drive adaptive evolution by favouring beneficial alleles. Strong sexual selection did not, however, delay extinction when the temperature became excessively high. By manipulating individuals’ mating opportunities during fitness assays we were able to assess the effect of multiple mating independently from the effect of population-level sexual selection, and found that polyandry has a positive effect on both fecundity and offspring survival under increasing temperatures in those populations evolving with weak sexual selection. Within stable temperatures there were some benefits from strong sexual selection but these were not consistent across the entire experiment, possibly reflecting changing costs and benefits of sexual selection under stabilising and directional selection. These results indicate that sexual selection can provide a buffer against climate change and increase adaptation rates within a continuously changing environment. These positive effects of sexual selection may however be too small to protect populations and delay extinction when environmental changes are relatively rapid

Fur seal microbiota are shaped by the social and physical environment, show mother‐offspring similarities and are associated with host genetic quality

Despite an increasing appreciation of the importance of host‐microbe interactions in ecological and evolutionary processes, the factors shaping microbial communities in wild populations remain poorly understood. We therefore exploited a natural experiment provided by two adjacent Antarctic fur seal (Arctocephalus gazella) colonies of high and low social density and combined 16S rRNA metabarcoding with microsatellite profiling of mother‐offspring pairs to investigate environmental and genetic influences on skin microbial communities. Seal‐associated bacterial communities differed profoundly between the two colonies, despite the host populations themselves being genetically undifferentiated. Consistent with the hypothesis that social stress depresses bacterial diversity, we found that microbial alpha diversity was significantly lower in the high‐density colony. Seals from one of the colonies that contained a stream also carried a subset of freshwater‐associated bacteria, indicative of an influence of the physical environment. Furthermore, mothers and their offspring shared similar microbial communities, in support of the notion that microbes may facilitate mother‐offspring recognition. Finally, a significant negative association was found between bacterial diversity and heterozygosity, a measure of host genetic quality. Our study thus uncovers a complex interplay between environmental and host genetic effects, while also providing empirical support for the leash model of host control, which posits that bacterial communities are driven not only by bottom‐up species interactions, but also by top‐down host regulation. Taken together, our findings have broad implications for understanding host‐microbe interactions as well as prokaryotic diversity in general

Economic development, human development, and the pursuit of happiness, April 1, 2, and 3, 2004

This repository item contains a single issue of the Pardee Conference Series, a publication series that began publishing in 2006 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future. This was the Center's spring conference, which took place during April 1, 2, and 3, 2004.The conference asks the questions, how can we make sure that the benefits of economic growth flow into health, education, welfare, and other aspects of human development; and what is the relationship between human development and economic development? Speakers and participants discuss the role that culture, legal and political institutions, the UN Developmental Goals, the level of decision-making, and ethics, play in development