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UKRI Trustworthy Autonomous Systems Node in Trust

UKRI 值得信赖的自治系统节点

基本信息

批准号：
EP/V026682/1
负责人：
Helen Hastie
金额：
$ 389.49万
依托单位：
Heriot-Watt University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FV026682%2F1
关键词：
UKRI Trustworthy Autonomous Systems Node

项目摘要

Engineered systems are increasingly being used autonomously, making decisions and taking actions without human intervention. These Autonomous Systems are already being deployed in industrial sectors but in controlled scenarios (e.g. static automated production lines, fixed sensors). They start to get into difficulties when the task increases in complexity or the environment is uncontrolled (e.g. drones for offshore windfarm inspection), or where there is a high interaction with people and entities in the world (e.g. self-driving cars) or where they have to work as a team (e.g. cobots working in a factory). The EN-TRUST Vision is that these systems learn situations where trust is typically lost unnecessarily, adapting this prediction for specific people and contexts. Stakeholder trust will be managed through transparent interaction, increasing the confidence of the stakeholders to use the Autonomous Systems, meaning that they can be adopted in scenarios never before thought possible, such as doing the jobs that endanger humans (e.g. first responders or pandemic related tasks). The EN-TRUST 'Trust' Node will perform foundational research on how humans and Autonomous Systems (AS) can work together by building a shared reality, based on mutual understanding through trustworthy interaction. The EN-TRUST Node will create a UK research centre of excellence for trust that will inform the design of Autonomous Systems going forward, ensuring that they are widely used and accepted in a variety of applications. This cross-cutting multidisciplinary approach is grounded in Psychology and Cognitive Science and consists of three "pillars of trust": 1) computational models of human trust in AS; 2) adaptation of these models in the face of errors and uncontrolled environments; and 3) user validation and evaluation across a broad range of sectors in realistic scenarios. This EN-TRUST framework will explore how to best establish, maintain and repair trust by incorporating the subjective view of human trust towards Autonomous Systems, thus maximising their positive societal and economic benefits.

工程系统越来越多地被自主使用，在没有人为干预的情况下做出决策和采取行动。这些自主系统已经在工业部门部署，但在受控场景中（例如静态自动化生产线，固定传感器）。当任务复杂性增加或环境不受控制时（例如用于海上风电场检查的无人机），或者与世界上的人和实体进行高度互动时（例如自动驾驶汽车），或者他们必须作为一个团队工作时（例如在工厂工作的协作机器人），他们开始陷入困境。EN-TRUST的愿景是，这些系统可以学习通常不必要地失去信任的情况，并根据特定的人和环境调整这种预测。利益相关者的信任将通过透明的互动来管理，增加利益相关者使用自治系统的信心，这意味着它们可以在以前认为不可能的情况下被采用，例如从事危及人类的工作（例如第一响应者或与流行病相关的任务）。EN-TRUST“信任”节点将对人类和自治系统（AS）如何通过建立共享现实来共同工作进行基础研究，基于通过可信赖的交互进行相互理解。EN-TRUST节点将创建一个英国卓越的信任研究中心，为未来自主系统的设计提供信息，确保它们在各种应用中得到广泛使用和接受。这种跨学科的多学科方法以心理学和认知科学为基础，由三个“信任支柱”组成：1）人类对AS信任的计算模型; 2）面对错误和不受控制的环境，这些模型的适应性; 3）在现实场景中，在广泛的领域进行用户验证和评估。这个EN-TRUST框架将探索如何通过纳入人类对自治系统信任的主观观点来最好地建立、维护和修复信任，从而最大限度地发挥其积极的社会和经济效益。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

On Specifying for Trustworthiness

DOI：
10.1145/3624699
发表时间：
2022-06
期刊：
Communications of the ACM
影响因子：
22.7
作者：
Dhaminda B. Abeywickrama;A. Bennaceur;Greg Chance;Y. Demiris;Anastasia Kordoni;Mark Levine;Luke Moffat-Luke
通讯作者：
Dhaminda B. Abeywickrama;A. Bennaceur;Greg Chance;Y. Demiris;Anastasia Kordoni;Mark Levine;Luke Moffat-Luke

Artificial intelligence and human behavioral development: A perspective on new skills and competences acquisition for the educational context

DOI：
10.1016/j.chb.2023.107903
发表时间：
2023-08
期刊：
Comput. Hum. Behav.
影响因子：
0
作者：
M. Benvenuti;A. Cangelosi;A. Weinberger;E. Mazzoni;M. Benassi;Mattia Barbaresi;M. Orsoni
通讯作者：
M. Benvenuti;A. Cangelosi;A. Weinberger;E. Mazzoni;M. Benassi;Mattia Barbaresi;M. Orsoni

Cognitive Robotics