报告人：Yanqing Duan（英国University of Bedfordshire教授，商学院信息系统研究中心主任）

报告时间：2020年11月27日15:00-16:00

线上报告：腾讯会议

会议ID：953 460 033

联系人：张小栓 zhxshuan@cau.edu.cn

欢迎各位老师同学线上参加。

专家简介： Yanqing Duan (BSc, MSc, PhD, SFHEA) is a Professor of Information Systems. She is also the founder and director of Business and Information Systems Research Centre (BISC) at the Business School, University of Bedfordshire. Professor Duan received her BSc and MSc from China Agricultural University and PhD from Aston University, UK. Her principal research interest is the development and use of emerging ICTs and their impact on organisational performance, sustainable agriculture and aquaculture production, decision making, and knowledge transfer, For example, the development, use and impact of Big Data Analytics, Internet of Things, AI, smart agriculture, sustainable food supply chains, and SME’s adoption of emerging digital technologies.

She is a regular expert evaluator for various funding bodies including EU H2020. She is the associate editor of Decision support systems and International Journal of Information Management.

Professor Duan has worked on various research projects on digital business, digital agriculture and aquaculture in collaboration with international, European, and UK partners. Her research helps to understand and address digital business adoption barriers, to identify key success factors and to develop relevant technologies and strategies to achieve positive impacts. She has been very active in raising awareness among food SMEs on the business value of emerging digital technologies, such as Big Data, IoT, Analytics  and AI,  and helping business adopt the most relevant ICTs for gaining business benefits.

She has received many research grants from various funding sources, such as: European Commission, Innovate UK, UK Department For International Development (DFID), BBSRC, JISC, British Council, etc. She has published over 240 peer reviewed articles, including papers in European Journal of Operational Research, European Journal Information Systems, IEEE transaction on Engineering Management, Information & Management, European Journal of Marketing, Journal of Business Research, Industrial Marketing Management, Production Planning & Control, Expert Systems with Applications, The Information Society, Information Technology & People.

报告题目：Impact of Covid 19 Pandemic on Artificial Intelligence Research and Practice from a Decision Making Perspective

报告内容：

As the ability for Artificial Intelligence (AI) to overcome some of the computationally intensive, intellectual and even creative limitations of humans, opens up new application domains (Dwivedi et al., 2019), AI has been hailed as a super power that is capable of performing tasks not only as good as humans, but also better than humans. While the world is suffering from the COVID -19 pandemic and witnessing the situation becoming worsened on a daily basis, there are many opportunities for harnessing the benefit of AI. However, information on the role and impact of AI during the pandemic appears to be limited. Has AI failed the COVID -19 pandemic test? Where is AI when we need it most?

There is no doubt that one of the most critical challenges in dealing with the COVID -19 pandemic is making the right decisions at the right time for the right reasons. Decision makers in all sectors including government, public services, health care, social care, commercial companies, etc. appear to be struggling with making effective decisions quickly at all decision making levels from strategic, tactical to operational. Many leaders and managers are constantly being criticised for mismanagement due to bad decisions that led to unnecessary loss of human lives and economic damages. The need for utilising technologies, especially AI, to assist decision makers in making the most effective and efficient decisions to deal with unprecedented crisis has becoming ever more imperative. This presentation aims to analyse and highlight the impact of the COVID-19 pandemic on AI research and practice for information management from a decision making perspective.