Reliance on metrics is a fundamental challenge for AI.

Through a series of case studies, we review how the unthinking pursuit of metric optimization can lead to real-world harms, including recommendation systems promoting radicalization, well-loved teachers fired by an algorithm, and essay grading software that rewards sophisticated garbage. The metrics used are often proxies for underlying, unmeasurable quantities (e.g.

Differential cell counts using center-point networks achieves human-level accuracy and efficiency over segmentation.

Differential cell counts is a challenging task when applying computer vision algorithms to pathology. Existing approaches to train cell recognition require high availability of multi-class segmentation and/or bounding box annotations and suffer in performance when objects are tightly clustered. We present differential count network ("DCNet"), an annotation efficient modality that utilises keypoint detection to locate in brightfield images the centre points of cells (not nuclei) and their cell class.

Stability of ring patterns arising from two-dimensional particle interactions.

Pairwise particle interactions arise in diverse physical systems ranging from insect swarms to self-assembly of nanoparticles. In the presence of long-range attraction and short-range repulsion, such systems can exhibit bound states. We use linear stability analysis of a ring equilibrium to classify the morphology of patterns in two dimensions.

A mathematical model of a crocodilian population using delay-differential equations.

The crocodilia have multiple interesting characteristics that affect their population dynamics. They are among several reptile species which exhibit temperature-dependent sex determination (TSD) in which the temperature of egg incubation determines the sex of the hatchlings. Their life parameters, specifically birth and death rates, exhibit strong age-dependence.

Vorticity dynamics and sound generation in two-dimensional fluid flow.

An approximate solution to the two-dimensional incompressible fluid equations is constructed by expanding the vorticity field in a series of derivatives of a Gaussian vortex. The expansion is used to analyze the motion of a corotating Gaussian vortex pair, and the spatial rotation frequency of the vortex pair is derived directly from the fluid vorticity equation. The resulting rotation frequency includes the effects of finite vortex core size and viscosity and reduces, in the appropriate limit, to the rotation frequency of the Kirchhoff point vortex theory.