Ethics in the Age of AI: An Analysis of AI Practitioners' Awareness and Challenges

• URL: http://arxiv.org/abs/2307.10057v1
• Date: Fri, 14 Jul 2023 02:50:46 GMT
• Title: Ethics in the Age of AI: An Analysis of AI Practitioners' Awareness and Challenges
• Authors: Aastha Pant, Rashina Hoda, Simone V. Spiegler, Chakkrit Tantithamthavorn, Burak Turhan
• Abstract summary: We conducted a survey aimed at understanding AI practitioners' awareness of AI ethics and their challenges in incorporating ethics. Based on 100 AI practitioners' responses, our findings indicate that majority of AI practitioners had a reasonable familiarity with the concept of AI ethics. Formal education/training was considered somewhat helpful in preparing practitioners to incorporate AI ethics.
• Score: 11.656193349991609
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Ethics in AI has become a debated topic of public and expert discourse in recent years. But what do people who build AI - AI practitioners - have to say about their understanding of AI ethics and the challenges associated with incorporating it in the AI-based systems they develop? Understanding AI practitioners' views on AI ethics is important as they are the ones closest to the AI systems and can bring about changes and improvements. We conducted a survey aimed at understanding AI practitioners' awareness of AI ethics and their challenges in incorporating ethics. Based on 100 AI practitioners' responses, our findings indicate that majority of AI practitioners had a reasonable familiarity with the concept of AI ethics, primarily due to workplace rules and policies. Privacy protection and security was the ethical principle that majority of them were aware of. Formal education/training was considered somewhat helpful in preparing practitioners to incorporate AI ethics. The challenges that AI practitioners faced in the development of ethical AI-based systems included (i) general challenges, (ii) technology-related challenges and (iii) human-related challenges. We also identified areas needing further investigation and provided recommendations to assist AI practitioners and companies in incorporating ethics into AI development.

Related papers

• Raising AI Ethics Awareness through an AI Ethics Quiz for Software Practitioners [7.928588994077104]
  Research indicates a significant gap in practitioners' awareness and knowledge of AI ethics and ethical principles. We developed a software-based tool, the AI Ethics Quiz, to raise awareness and enhance the knowledge of AI ethics among software practitioners.
  arXiv  Detail & Related papers  (2024-08-28T23:36:13Z)
• FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare [73.78776682247187]
  Concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare.
  arXiv  Detail & Related papers  (2023-08-11T10:49:05Z)
• Ever heard of ethical AI? Investigating the salience of ethical AI issues among the German population [0.0]
  General interest in AI and a higher educational level are predictive of some engagement with AI. Ethical issues are voiced only by a small subset of citizens with fairness, accountability, and transparency being the least mentioned ones. Once ethical AI is top of the mind, there is some potential for activism.
  arXiv  Detail & Related papers  (2022-07-28T13:46:13Z)
• AI Ethics: An Empirical Study on the Views of Practitioners and Lawmakers [8.82540441326446]
  Transparency, accountability, and privacy are the most critical AI ethics principles. Lack of ethical knowledge, no legal frameworks, and lacking monitoring bodies are the most common AI ethics challenges.
  arXiv  Detail & Related papers  (2022-06-30T17:24:29Z)
• Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review [12.941478155592502]
  In recent years, numerous incidents have raised the profile of ethical issues in AI development and led to public concerns about the proliferation of AI technology in our everyday lives. We conducted a grounded theory literature review (GTLR) of 38 primary empirical studies that included AI practitioners' views on ethics in AI. We present a taxonomy of ethics in AI from practitioners' viewpoints to assist AI practitioners in identifying and understanding the different aspects of AI ethics.
  arXiv  Detail & Related papers  (2022-06-20T00:28:51Z)
• AI Ethics Issues in Real World: Evidence from AI Incident Database [0.6091702876917279]
  We identify 13 application areas which often see unethical use of AI, with intelligent service robots, language/vision models and autonomous driving taking the lead. Ethical issues appear in 8 different forms, from inappropriate use and racial discrimination, to physical safety and unfair algorithm.
  arXiv  Detail & Related papers  (2022-06-15T16:25:57Z)
• 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)
• Trustworthy AI: A Computational Perspective [54.80482955088197]
  We focus on six of the most crucial dimensions in achieving trustworthy AI: (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being. For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.
  arXiv  Detail & Related papers  (2021-07-12T14:21:46Z)
• 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 Short Anthropological Guide to the Study of Ethical AI [91.3755431537592]
  Short guide serves as both an introduction to AI ethics and social science and anthropological perspectives on the development of AI. Aims to provide those unfamiliar with the field with an insight into the societal impact of AI systems and how, in turn, these systems can lead us to rethink how our world operates.
  arXiv  Detail & Related papers  (2020-10-07T12:25:03Z)

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.