Integrated Calendar

In natural settings, we make decisions based on streams of partial and noisy information. Arguably, we summarize the perceived information into a probabilistic model of the world, which we can exploit to make decisions. This talk will explore such ‘mental models’ in the context of idealized tasks that can be carried out in the laboratory and modeled quantitatively. The starting point of the talk will be a sequential inference task that probes inference in changing environments, in humans. I will describe the task and an experimental finding, namely, that humans make use of fine differences in temporal statistics when making inferences. While our observations agrees qualitatively with an optimal inference model, the data exhibit biases. What is more, human responses, unlike those of the optimal model, are variable, and this behavioral variability is itself modulated during the inference task. In order to uncover the putative algorithmic framework employed by humans, I will go on to examine a family of models that break away from the optimal model in diverse ways. This investigation will suggest a picture in which humans carry out inference using noisy mental representations. More specifically, rather than representing a whole probability function, human subjects may manipulate probabilities using a (possibly modest) number of samples. The approach just outlined illustrates a range of possible computational structures of sub-optimal inference, but it lacks the appeal of a normative framework. If time permits, I will discuss recent ideas on a normative approach to human inference subject to internal ‘costs’ or ‘drives’, which can explain various biases. While different in its formulation, this approach shares conceptual commonalities with the rational inattention theory and other constrained optimization frameworks in cognitive science.

Sedimentary basins are commonly viewed as archives of ancient depositional environments and geochemical signals measured in these basins are frequently interpreted as proxies for ancient Earth-surface environments. However, in the course of the sedimentary basins life-cycle, sedimentary rocks can undergo alteration in diagenetic, epigenetic and metamorphic environments. When put in the correct context, these altered geochemical records are valuable sources of information that reflect the complex thermal, compositional, and deformational histories experienced by the sedimentary rocks. Additionally these measurements can serve as key observations in the study of the interactions among the Earth’s surface and internal processes.
In the talk, I will demonstrate how carbonate clumped isotope thermometry (a relatively new temperature-proxy) can be used to study the thermal history of the Colorado Plateau (southwestern N. America), and constrain the oxygen isotope composition of the Phanerozoic Ocean. Clumped and single isotope compositions of calcite and dolomite minerals collected from the Paleozoic sedimentary sequence at the Grand Canyon are consistent with isotopic alteration through open-system recrystallization and/or solid-state isotopic reordering at elevated burial temperatures. By comparing these values with modeled predictions of isotopic signal alteration, we constrain the peak burial temperatures and thermal gradient, and infer the total overburden and exhumation above the top Paleozoic datum at the Colorado Plateau. We also use our data to back-calculate the oxygen isotope composition of dolomite parental water and our results indicate that the oxygen isotope composition of seawater has remained stable throughout the Phanerozoic. This stability suggests that the fluxes of globally averaged oxygen isotope exchange, associated with weathering and hydrothermal alteration reactions, have remained proportional through time. This observation is consistent with the hypothesis that a steady-state balance exists between seafloor hydrothermal activity and surface weathering.

The Global Burden of Disease relates premature mortality to a range of causes, including air pollution by ozone and fine particulate matter (PM2.5). Quantifying the role of air pollution has been a challenge, in part due to uncertainty about human exposure to air pollution worldwide. We present results from a global atmospheric chemistry model, combined with population data, country-level health statistics and pollution exposure response functions. We calculate that outdoor air pollution, mostly by PM2.5, leads to about 4.5 million premature deaths/year worldwide, predominantly in Asia (75%). This is three times the rate by HIV/AIDS and malaria together. Contrary to the common view that traffic, industry and power generation are dominant sources, we show that residential energy use (e.g. heating, cooking) is the largest category worldwide due to its prevalence in India and China. Strong control measures are needed to substantially lower morbidity and mortality from air pollution. Clean air is a human right, being fundamental to many sustainable development goals of the United Nations.