An Ethical Framework for Guiding the Development of Affectively-Aware Artificial Intelligence

• URL: http://arxiv.org/abs/2107.13734v1
• Date: Thu, 29 Jul 2021 03:57:53 GMT
• Title: An Ethical Framework for Guiding the Development of Affectively-Aware Artificial Intelligence
• Authors: Desmond C. Ong
• Abstract summary: We propose guidelines for evaluating the (moral and) ethical consequences of affectively-aware AI. We propose a multi-stakeholder analysis framework that separates the ethical responsibilities of AI Developers vis-a-vis the entities that deploy such AI. We end with recommendations for researchers, developers, operators, as well as regulators and law-makers.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The recent rapid advancements in artificial intelligence research and deployment have sparked more discussion about the potential ramifications of socially- and emotionally-intelligent AI. The question is not if research can produce such affectively-aware AI, but when it will. What will it mean for society when machines -- and the corporations and governments they serve -- can "read" people's minds and emotions? What should developers and operators of such AI do, and what should they not do? The goal of this article is to pre-empt some of the potential implications of these developments, and propose a set of guidelines for evaluating the (moral and) ethical consequences of affectively-aware AI, in order to guide researchers, industry professionals, and policy-makers. We propose a multi-stakeholder analysis framework that separates the ethical responsibilities of AI Developers vis-\`a-vis the entities that deploy such AI -- which we term Operators. Our analysis produces two pillars that clarify the responsibilities of each of these stakeholders: Provable Beneficence, which rests on proving the effectiveness of the AI, and Responsible Stewardship, which governs responsible collection, use, and storage of data and the decisions made from such data. We end with recommendations for researchers, developers, operators, as well as regulators and law-makers.

Related papers

• The Narrow Depth and Breadth of Corporate Responsible AI Research [3.364518262921329]
  We show that the majority of AI firms show limited or no engagement in this critical subfield of AI. Leading AI firms exhibit significantly lower output in responsible AI research compared to their conventional AI research. Our results highlight the urgent need for industry to publicly engage in responsible AI research.
  arXiv  Detail & Related papers  (2024-05-20T17:26:43Z)
• Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits [54.648819983899614]
  General purpose AI seems to have lowered the barriers for the public to use AI and harness its power. We introduce PARTICIP-AI, a framework for laypeople to speculate and assess AI use cases and their impacts.
  arXiv  Detail & Related papers  (2024-03-21T19:12:37Z)
• Responsible Artificial Intelligence: A Structured Literature Review [0.0]
  The EU has recently issued several publications emphasizing the necessity of trust in AI. This highlights the urgent need for international regulation. This paper introduces a comprehensive and, to our knowledge, the first unified definition of responsible AI.
  arXiv  Detail & Related papers  (2024-03-11T17:01:13Z)
• Investigating Responsible AI for Scientific Research: An Empirical Study [4.597781832707524]
  The push for Responsible AI (RAI) in such institutions underscores the increasing emphasis on integrating ethical considerations within AI design and development. This paper aims to assess the awareness and preparedness regarding the ethical risks inherent in AI design and development. Our results have revealed certain knowledge gaps concerning ethical, responsible, and inclusive AI, with limitations in awareness of the available AI ethics frameworks.
  arXiv  Detail & Related papers  (2023-12-15T06:40:27Z)
• Responsible AI Research Needs Impact Statements Too [51.37368267352821]
  Work in responsible artificial intelligence (RAI), ethical AI, or ethics in AI is no exception. Work in responsible artificial intelligence (RAI), ethical AI, or ethics in AI is no exception.
  arXiv  Detail & Related papers  (2023-11-20T14:02:28Z)
• Cybertrust: From Explainable to Actionable and Interpretable AI (AI2) [58.981120701284816]
  Actionable and Interpretable AI (AI2) will incorporate explicit quantifications and visualizations of user confidence in AI recommendations. It will allow examining and testing of AI system predictions to establish a basis for trust in the systems' decision making.
  arXiv  Detail & Related papers  (2022-01-26T18:53:09Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)
• The State of AI Ethics Report (October 2020) [30.265104923077185]
  The State of AI Ethics captures the most relevant developments in the field of AI Ethics since July 2020. This report aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the ever-changing developments in the field. The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments.
  arXiv  Detail & Related papers  (2020-11-05T12:36:16Z)
• Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims [59.64274607533249]
  AI developers need to make verifiable claims to which they can be held accountable. This report suggests various steps that different stakeholders can take to improve the verifiability of claims made about AI systems. We analyze ten mechanisms for this purpose--spanning institutions, software, and hardware--and make recommendations aimed at implementing, exploring, or improving those mechanisms.
  arXiv  Detail & Related papers  (2020-04-15T17:15:35Z)

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.