Results 21 to 30 of about 3,053,264 (345)
The Journal of Finance, 2023 ABSTRACTWe construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and nonvisual object characteristics. We find that higher automated valuations relative to auction house presale estimates are associated with substantially higher price‐to‐estimate ratios and lower buy‐in rates, pointing to ...
Aubry, M. +3 more
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The Political Biases of ChatGPT
The social science, 2023 Recent advancements in Large Language Models (LLMs) suggest imminent commercial applications of such AI systems where they will serve as gateways to interact with technology and the accumulated body of human knowledge. The possibility of political biases
David Rozado
semanticscholar +1 more source
Astronomy Reports, 2021 We study biasing as a physical phenomenon by analysing power spectra (PS) and correlation functions (CF) of simulated galaxy samples and dark matter (DM) samples. We apply an algorithm based on the local densities of particles, $ $, to form populations of simulated galaxies, using particles with $ \ge _0$. We calculate two-point CF of projected (2D)
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Mitigating Unwanted Biases with Adversarial Learning [PDF]
AAAI/ACM Conference on AI, Ethics, and Society, 2018 Machine learning is a tool for building models that accurately represent input training data. When undesired biases concerning demographic groups are in the training data, well-trained models will reflect those biases.
B. Zhang +2 more
semanticscholar +1 more source
Biases in Large Language Models: Origins, Inventory, and Discussion
ACM Journal of Data and Information Quality, 2023 In this article, we introduce and discuss the pervasive issue of bias in the large language models that are currently at the core of mainstream approaches to Natural Language Processing (NLP).
Roberto Navigli +2 more
semanticscholar +1 more source
Journal of Economic Behavior & Organization, 2014 Organizations can use subjective performance pay when verifiable performance measures are imperfect. However, this gives supervisors the power to direct employees toward tasks that mainly benefit the supervisor rather than the organization. We cast a principal–supervisor–agent model in a multitask setting, where the supervisor has an intrinsic ...
Josse Delfgaauw, Michiel Souverijn
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Mitigating Label Biases for In-context Learning [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Various design settings for in-context learning (ICL), such as the choice and order of the in-context examples, can bias the model’s predictions.
Yu Fei +3 more
semanticscholar +1 more source
Biophysical Journal, 2016 G-protein-coupled receptors (GPCRs) constitute a large group of integral membrane proteins that transduce extracellular signals from a wide range of agonists into targeted intracellular responses. Although the responses can vary depending on the category of G-proteins activated by a particular receptor, responses were also found to be triggered by ...
Stuart J, Edelstein +1 more
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Eliminating Explicit and Implicit Biases in Health Care: Evidence and Research Needs
Annual Review of Public Health, 2022 Health care providers hold negative explicit and implicit biases against marginalized groups of people such as racial and ethnic minoritized populations. These biases permeate the health care system and affect patients via patient–clinician communication,
Monica B. Vela +5 more
semanticscholar +1 more source
Probabilistic biases meet the Bayesian brain [PDF]
, 2020 Bayesian cognitive science sees the mind as a spectacular probabilistic inference machine. But Judgment and Decision Making research has spent half a century uncovering how dramatically and systematically people depart from rational norms.
Chater, Nick +5 more
core +1 more source