The Only Way is Ethics: A Guide to Ethical Research with Large Language Models
- URL: http://arxiv.org/abs/2412.16022v1
- Date: Fri, 20 Dec 2024 16:14:43 GMT
- Title: The Only Way is Ethics: A Guide to Ethical Research with Large Language Models
- Authors: Eddie L. Ungless, Nikolas Vitsakis, Zeerak Talat, James Garforth, Björn Ross, Arno Onken, Atoosa Kasirzadeh, Alexandra Birch,
- Abstract summary: 'LLM Ethics Whitepaper' is an open resource for NLP practitioners and those tasked with evaluating the ethical implications of others' work.
Our goal is to translate ethics literature into concrete recommendations and provocations for thinking with clear first steps.
'LLM Ethics Whitepaper' distils a thorough literature review into clear Do's and Don'ts, which we present also in this paper.
- Score: 53.316174782223115
- License:
- Abstract: There is a significant body of work looking at the ethical considerations of large language models (LLMs): critiquing tools to measure performance and harms; proposing toolkits to aid in ideation; discussing the risks to workers; considering legislation around privacy and security etc. As yet there is no work that integrates these resources into a single practical guide that focuses on LLMs; we attempt this ambitious goal. We introduce 'LLM Ethics Whitepaper', which we provide as an open and living resource for NLP practitioners, and those tasked with evaluating the ethical implications of others' work. Our goal is to translate ethics literature into concrete recommendations and provocations for thinking with clear first steps, aimed at computer scientists. 'LLM Ethics Whitepaper' distils a thorough literature review into clear Do's and Don'ts, which we present also in this paper. We likewise identify useful toolkits to support ethical work. We refer the interested reader to the full LLM Ethics Whitepaper, which provides a succinct discussion of ethical considerations at each stage in a project lifecycle, as well as citations for the hundreds of papers from which we drew our recommendations. The present paper can be thought of as a pocket guide to conducting ethical research with LLMs.
Related papers
- Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models [53.316174782223115]
This whitepaper offers an overview of the ethical considerations surrounding research into or with large language models (LLMs)
As LLMs become more integrated into widely used applications, their societal impact increases, bringing important ethical questions to the forefront.
arXiv Detail & Related papers (2024-10-17T18:36:02Z) - Exploring and steering the moral compass of Large Language Models [55.2480439325792]
Large Language Models (LLMs) have become central to advancing automation and decision-making across various sectors.
This study proposes a comprehensive comparative analysis of the most advanced LLMs to assess their moral profiles.
arXiv Detail & Related papers (2024-05-27T16:49:22Z) - A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law [65.87885628115946]
Large language models (LLMs) are revolutionizing the landscapes of finance, healthcare, and law.
We highlight the instrumental role of LLMs in enhancing diagnostic and treatment methodologies in healthcare, innovating financial analytics, and refining legal interpretation and compliance strategies.
We critically examine the ethics for LLM applications in these fields, pointing out the existing ethical concerns and the need for transparent, fair, and robust AI systems.
arXiv Detail & Related papers (2024-05-02T22:43:02Z) - EALM: Introducing Multidimensional Ethical Alignment in Conversational
Information Retrieval [43.72331337131317]
We introduce a workflow that integrates ethical alignment with an initial ethical judgment stage for efficient data screening.
We present the QA-ETHICS dataset adapted from the ETHICS benchmark, which serves as an evaluation tool by unifying scenarios and label meanings.
In addition, we suggest a new approach that achieves top performance in both binary and multi-label ethical judgment tasks.
arXiv Detail & Related papers (2023-10-02T08:22:34Z) - Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics [26.977005985123615]
We conduct a qualitative analysis of 27 AI ethics toolkits to examine how the work of ethics is imagined and how it is supported by these toolkits.
We identify a mismatch between the imagined work of ethics and the support the toolkits provide for doing that work.
arXiv Detail & Related papers (2022-02-17T17:55:26Z) - Thinking Through and Writing About Research Ethics Beyond "Broader
Impact" [1.505509197162783]
In March 2021, we held the first instalment of the tutorial on thinking through and writing about research ethics beyond 'Broader Impact'
The goal of this tutorial was to offer a conceptual and practical starting point for engineers and social scientists interested in thinking more expansively.
This report provides an outline of the tutorial, and contains our 'lifecourse checklist'
arXiv Detail & Related papers (2021-04-16T16:24:05Z) - Case Study: Deontological Ethics in NLP [119.53038547411062]
We study one ethical theory, namely deontological ethics, from the perspective of NLP.
In particular, we focus on the generalization principle and the respect for autonomy through informed consent.
We provide four case studies to demonstrate how these principles can be used with NLP systems.
arXiv Detail & Related papers (2020-10-09T16:04:51Z) - On the Morality of Artificial Intelligence [154.69452301122175]
We propose conceptual and practical principles and guidelines for Machine Learning research and deployment.
We insist on concrete actions that can be taken by practitioners to pursue a more ethical and moral practice of ML aimed at using AI for social good.
arXiv Detail & Related papers (2019-12-26T23:06:54Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.