Detecting disparities in police deployments using dashcam data

Large-scale policing data is vital for detecting inequity in police behavior and policing algorithms. However, one important type of policing data remains largely unavailable within the United States: aggregated police deployment data capturing which neighborhoods have the heaviest police presences. Here we show that disparities in police deployment levels can be quantified by detecting police vehicles in dashcam images of public street scenes. Using a dataset of 24,803,854 dashcam images from rideshare drivers in New York City, we find that police vehicles can be detected with high accuracy (average precision 0.82, AUC 0.99) and identify 233,596 images which contain police vehicles. There is substantial inequality across neighborhoods in police vehicle deployment levels. The neighborhood with the highest deployment levels has almost 20 times higher levels than the neighborhood with the lowest. Two strikingly different types of areas experience high police vehicle deployments - 1) dense, higher-income, commercial areas and 2) lower-income neighborhoods with higher proportions of Black and Hispanic residents. We discuss the implications of these disparities for policing equity and for algorithms trained on policing data.Comment: To appear in ACM Conference on Fairness, Accountability, and Transparency (FAccT) '2

Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheets

Design space exploration (DSE) for Text-to-Image (TTI) models entails navigating a vast, opaque space of possible image outputs, through a commensurately vast input space of hyperparameters and prompt text. Minor adjustments to prompt input can surface unexpectedly disparate images. How can interfaces support end-users in reliably steering prompt-space explorations towards interesting results? Our design probe, DreamSheets, supports exploration strategies with LLM-based functions for assisted prompt construction and simultaneous display of generated results, hosted in a spreadsheet interface. The flexible layout and novel generative functions enable experimentation with user-defined workflows. Two studies, a preliminary lab study and a longitudinal study with five expert artists, revealed a set of strategies participants use to tackle the challenges of TTI design space exploration, and the interface features required to support them - like using text-generation to define local "axes" of exploration. We distill these insights into a UI mockup to guide future interfaces.Comment: 13 pages, 14 figures, currently under revie

SPADE: Synthesizing Data Quality Assertions for Large Language Model Pipelines

Large language models (LLMs) are being increasingly deployed as part of pipelines that repeatedly process or generate data of some sort. However, a common barrier to deployment are the frequent and often unpredictable errors that plague LLMs. Acknowledging the inevitability of these errors, we propose {\em data quality assertions} to identify when LLMs may be making mistakes. We present SPADE, a method for automatically synthesizing data quality assertions that identify bad LLM outputs. We make the observation that developers often identify data quality issues during prototyping prior to deployment, and attempt to address them by adding instructions to the LLM prompt over time. SPADE therefore analyzes histories of prompt versions over time to create candidate assertion functions and then selects a minimal set that fulfills both coverage and accuracy requirements. In testing across nine different real-world LLM pipelines, SPADE efficiently reduces the number of assertions by 14\% and decreases false failures by 21\% when compared to simpler baselines. SPADE has been deployed as an offering within LangSmith, LangChain's LLM pipeline hub, and has been used to generate data quality assertions for over 2000 pipelines across a spectrum of industries.Comment: 17 pages, 6 figure

A topological classification of convex bodies

The shape of homogeneous, generic, smooth convex bodies as described by the Euclidean distance with nondegenerate critical points, measured from the center of mass represents a rather restricted class M_C of Morse-Smale functions on S^2. Here we show that even M_C exhibits the complexity known for general Morse-Smale functions on S^2 by exhausting all combinatorial possibilities: every 2-colored quadrangulation of the sphere is isomorphic to a suitably represented Morse-Smale complex associated with a function in M_C (and vice versa). We prove our claim by an inductive algorithm, starting from the path graph P_2 and generating convex bodies corresponding to quadrangulations with increasing number of vertices by performing each combinatorially possible vertex splitting by a convexity-preserving local manipulation of the surface. Since convex bodies carrying Morse-Smale complexes isomorphic to P_2 exist, this algorithm not only proves our claim but also generalizes the known classification scheme in [36]. Our expansion algorithm is essentially the dual procedure to the algorithm presented by Edelsbrunner et al. in [21], producing a hierarchy of increasingly coarse Morse-Smale complexes. We point out applications to pebble shapes.Comment: 25 pages, 10 figure

Liver retransplantation as a therapeutic method in graft dysfunctions in the immediate postoperative period

Departament Chirurgie Generală, I.C. Fundeni, București, România, Al XIII-lea Congres al Asociației Chirurgilor „Nicolae Anestiadi” și al III-lea Congres al Societății de Endoscopie, Chirurgie miniminvazivă și Ultrasonografie ”V.M.Guțu” din Republica MoldovaCu toate că în ultimii ani au apărut progrese importante în domeniul hepatic, problema prevenirii apariției disfuncției și eșecului post-transplant nu a prezentat progrese semnificative. Intrucât disfuncția hepatică primară influențează dramatic evoluția grefei și a pacientului transplantat hepatic, prevenirea acestui fenomen devine obligatoriu. Creșterea penuriei de organe și a numărului persoanelor aflate pe lista de așteptare a dus la folosirea unor grefe ce depășesc criteriile normale de selecție pentru recoltare precum și transplantarea unor donatori considerați marginali. Aceste circumstanțe au adus în prim plan importanța diagnosticării și tratamentului disfuncției hepatice primare. Conceptul de disfuncție hepatică primară nu este clar definit. Există un spectru de evenimente ce definesc disfuncția hepatică postoperatorie precoce: non funcția primară (PNF), nonfuncția întârziată, funcția slabă/săracă inițială (initial poor function – IPF), non funcția inițială, insuficiența hepatică primară și disfuncția primară. Distincția între aceste entități ia în considerare gradul disfuncției hepatice, necesitatea retransplantării urgente, precum și apariția și durata acestor evenimente după transplantul hepatic.Although important progress has been made over the last few years, the problem of preventing dysfunction and post-transplant liver failure has not shown significant progress. Since primary liver dysfunction dramatically influences the progress of the graft and the liver transplant patient, prevention of this phenomenon becomes obligatory. The increase in organ shortage and the number of people on the waiting list led to the use of grafts that exceeded the normal selection criteria for harvesting as well as the transplantation of marginal donors. These circumstances have highlighted the importance of diagnosis and treatment of primary hepatic dysfunction. The concept of primary liver dysfunction is not clearly defined. There is a spectrum of events that defines early postoperative liver dysfunction: primary non-function (PNF), delayed dysfunction, initial poor function (IPF), primary hepatic failure, and primary dysfunction. The distinction between these entities takes into account the degree of hepatic dysfunction, the need for urgent retransplantation, and the occurrence and duration of these events after liver transplantation

Arguing with behavior influence: A model for web-based group decision support systems

In this work, we propose an argumentation-based dialogue model designed for Web-based Group Decision Support Systems, that considers the decision-makers' intentions. The intentions are modeled as behavior styles which allow agents to interact with each other as humans would in face-to-face meetings. In addition, we propose a set of arguments that can be used by the agents to perform and evaluate requests, while considering the agents' behavior style. The inclusion of decision-makers' intentions intends to create a more reliable and realistic process. Our model proved, in different contexts, that higher levels of consensus and satisfaction are achieved when using agents modeled with behavior styles compared to agents without any features to represent the decision-makers' intentions.- (undefined