7 research outputs found
Western, Religious or Spiritual: An Evaluation of Moral Justification in Large Language Models
The increasing success of Large Language Models (LLMs) in variety of tasks
lead to their widespread use in our lives which necessitates the examination of
these models from different perspectives. The alignment of these models to
human values is an essential concern in order to establish trust that we have
safe and responsible systems. In this paper, we aim to find out which values
and principles are embedded in LLMs in the process of moral justification. For
this purpose, we come up with three different moral perspective categories:
Western tradition perspective (WT), Abrahamic tradition perspective (AT), and
Spiritualist/Mystic tradition perspective (SMT). In two different experiment
settings, we asked models to choose principles from the three for suggesting a
moral action and evaluating the moral permissibility of an action if one tries
to justify an action on these categories, respectively. Our experiments
indicate that tested LLMs favors the Western tradition moral perspective over
others. Additionally, we observe that there potentially exists an
over-alignment towards religious values represented in the Abrahamic Tradition,
which causes models to fail to recognize an action is immoral if it is
presented as a "religious-action". We believe that these results are essential
in order to direct our attention in future efforts.Comment: 16 pages total, 8 pages main pape
AugCSE: contrastive sentence embedding with diverse augmentations
Data augmentation techniques have been proven useful in many applications in NLP fields. Most augmentations are task-specific, and cannot be used as a general-purpose tool. In our work, we present AugCSE, a unified framework to utilize diverse sets of data augmentations to achieve a better, general-purpose, sentence embedding model. Building upon the latest sentence embedding models, our approach uses a simple antagonistic discriminator that differentiates the augmentation types. With the finetuning objective borrowed from domain adaptation, we show that diverse augmentations, which often lead to conflicting contrastive signals, can be tamed to produce a better and more robust sentence representation. Our methods achieve state-of-the-art results on downstream transfer tasks and perform competitively on semantic textual similarity tasks, using only unsupervised data.000000000000000000000000000000000000000000000000000000010241 - University of California, Berkeleyhttps://aclanthology.org/2022.aacl-main.30/First author draf
A Novel Method for Analysing Racial Bias: Collection of Person Level References
Long term exposure to biased content in literature or media can significantly
influence people's perceptions of reality, leading to the development of
implicit biases that are difficult to detect and address (Gerbner 1998). In
this study, we propose a novel method to analyze the differences in
representation between two groups and use it examine the representation of
African Americans and White Americans in books between 1850 to 2000 with the
Google Books dataset (Goldberg and Orwant 2013). By developing better tools to
understand differences in representation, we aim to contribute to the ongoing
efforts to recognize and mitigate biases. To improve upon the more common
phrase based (men, women, white, black, etc) methods to differentiate context
(Tripodi et al. 2019, Lucy; Tadimeti, and Bamman 2022), we propose collecting a
comprehensive list of historically significant figures and using their names to
select relevant context. This novel approach offers a more accurate and nuanced
method for detecting implicit biases through reducing the risk of selection
bias. We create group representations for each decade and analyze them in an
aligned semantic space (Hamilton, Leskovec, and Jurafsky 2016). We further
support our results by assessing the time adjusted toxicity (Bassignana,
Basile, and Patti 2018) in the context for each group and identifying the
semantic axes (Lucy, Tadimeti, and Bamman 2022) that exhibit the most
significant differences between the groups across decades. We support our
method by showing that our proposed method can capture known socio political
changes accurately and our findings indicate that while the relative number of
African American names mentioned in books have increased over time, the context
surrounding them remains more toxic than white Americans.Comment: Main paper is 9 page
Challenges in measuring bias via open-ended language generation
Googlehttps://aclanthology.org/2022.gebnlp-1.9/First author draf
Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries
Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
An investigation of pulse transit time as a blood pressure measurement method in patients undergoing carotid artery stenting
Conclusion After carotid stenting, the PTT increases significantly because of the lowering of the blood pressure. However, the relationship is not strong enough for the PTT to be used for blood pressure estimation. Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved