With Clear Intention—An Ethical Responsibility Model for Robot Governance

Author:

Rousi Rebekah

Abstract

There is much discussion about super artificial intelligence (AI) and autonomous machine learning (ML) systems, or learning machines (LM). Yet, the reality of thinking robotics still seems far on the horizon. It is one thing to define AI in light of human intelligence, citing the remoteness between ML and human intelligence, but another to understand issues of ethics, responsibility, and accountability in relation to the behavior of autonomous robotic systems within a human society. Due to the apparent gap between a society in which autonomous robots are a reality and present-day reality, many of the efforts placed on establishing robotic governance, and indeed, robot law fall outside the fields of valid scientific research. Work within this area has concentrated on manifestos, special interest groups and popular culture. This article takes a cognitive scientific perspective toward characterizing the nature of what true LMs would entail—i.e., intentionality and consciousness. It then proposes the Ethical Responsibility Model for Robot Governance (ER-RoboGov) as an initial platform or first iteration of a model for robot governance that takes the standpoint of LMs being conscious entities. The article utilizes past AI governance model research to map out the key factors of governance from the perspective of autonomous machine learning systems.

Publisher

Frontiers Media SA

Subject

General Medicine

Reference105 articles.

1. “Governance of ethical and trustworthy al systems: research gaps in the ECCOLA method,”;Agbese;2021 IEEE 29th International Requirements Engineering Conference Workshops (REW).,2021

2. Assemblages of practice. A conceptual framework for exploring human–thing relations in archaeology;Antczak;Arch. Dia,2019

3. AsaroP. MillarJ. ThomasenK. We Robot 2015 Conference – Robotic Governance Panel. University of Washington School of Law, Seattle, WA, 102015

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3