Results 81 to 90 of about 6,437 (212)
Fairness‐aware insurance pricing: A multi‐objective optimization approach
Journal of Risk and Insurance, EarlyView.Abstract Machine‐learning models can provide accurate predictions in insurance pricing, but can also increase disparities between protected groups. Existing fairness‐aware pricing approaches typically target one fairness notion at a time, making it difficult to compare trade‐offs between predictive accuracy, group fairness, individual fairness, and ...
Tim J. Boonen, Xinyue Fan, Zixiao Quan
wiley +1 more source
In many settings, human beings are boundedly rational. A distinctive and insufficiently explored legal response to bounded rationality is to attempt to "debias through law," by steering people in more rational directions.
Cass R. Sunstein, Christine Jolls
core
A hard to read font reduces the causality bias
Judgment and Decision Making, 2019 Previous studies have demonstrated that fluency affects judgment and decision-making. The purpose of the present research was to investigate the effect of perceptual fluency in a causal learning task that usually induces an illusion of causality in non ...
Marcos Díaz-Lago, Helena Matute
doaj +1 more source
Penalized Convex Estimation in Dynamic Location Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
wiley +1 more source
Modeling and debiasing resource saving judgments
Judgment and Decision Making, 2014 Svenson (2011) showed that choices of one of two alternative productivity increases to save production resources (e.g., man-months) were biased. Judgments of resource savings following a speed increase from a low production speed line were underestimated
Ola Svenson +2 more
doaj +1 more source
Assessing the Effectiveness of Workers' Selection Exams: The Case of the Bank of Italy
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT High‐stakes exams can be used to rank and select candidates for job openings, and the ability of those selected hinges on the design of the exam. I propose a method to model candidates' performance to assess how effective the exam is at selecting high‐ability candidates.
Santiago Pereda‐Fernández
wiley +1 more source
ADEPT: A DEbiasing PrompT Framework
, 2022 Several works have proven that finetuning is an applicable approach for debiasing contextualized word embeddings. Similarly, discrete prompts with semantic meanings have shown to be effective in debiasing tasks.
Yang, Ke +4 more
core
, 2006 In many settings, human beings are boundedly rational. A distinctive and insufficiently explored legal response to bounded rationality is to attempt to debias through law by steering people in more rational directions.
Jolls, Christine, Sunstein, Cass R.
core +1 more source
Do Not Harm Protected Groups in Debiasing Language Representation Models [PDF]
, 2023 Language Representation Models (LRMs) trained with real-world data may capture and exacerbate undesired bias and cause unfair treatment of people in various demographic groups.
Fain, Brandon +2 more
core +1 more source
Inequality of Opportunity in Wealth: Levels, Trends and Drivers in Germany
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT This paper studies inequality of opportunity (IOp) in individual net wealth in Germany from 2002 to 2019 using the Socio‐Economic Panel (SOEP). Applying the ex‐ante IOp framework, we quantify the share of wealth inequality attributable to immutable circumstances and benchmark it against IOp in gross labour earnings.
Daniel Graeber +2 more
wiley +1 more source