The First International Workshop on Trustworthy AI for the Future of Risk 
Management
TAI-RM 2022 (https://computing.ulster.ac.uk/TAI-RM2022/)
In association with WoWMoM 2022 
(https://computing.ulster.ac.uk/WoWMoM2022/index.html)
June 14th 2022
Belfast, Northern Ireland, UK

Motivation:

Wireless, mobile, and multimedia networking are critical part of services in 
modern life within the Internet of Things (IoT) context and present 
far-reaching opportunities for businesses. However, the growing complexity, 
pace and scale of global interconnectivity of tomorrow will present 
organisations with increasing systemic digital threats and challenges in risk 
management.

AI and predictive analytics are powerful tools to have in the arsenal of any 
risk management strategy and offers exciting prospects. AI, however, also 
brings new risks and manifests those risks in perplexing ways that is hard to 
ignore, e.g., AI's disruptive and, sometimes, disorderly capabilities. Their 
ability in effective risk management hinges on establishing a trustworthy AI 
foundation. Actually, building trustworthy AI systems is paramount as AI 
becomes more prominent across the globe. Trustworthy AI represents the 
evolution of AI, and offers opportunities for industries to create AI system 
that are transparent, explainable, fair, robust, and preserve privacy 
(so-called five pillars of trustworthy AI representing important factors in 
establishing reliable technology), especially in high-risk and safety-critical 
applications.

TAI-RM2022 workshop will be held as one of the workshops of WoWMoM2022. The 
local organizer of the first TAI-RM 2022 workshop is Artificial Intelligence 
Research Center (AIRC) from the School of Computing, Ulster University, 
Belfast, Northern Ireland, UK. This is also a joint event associated with the 
IEEE SMC (System, Man and Cybernetics) Ireland Chapter 28 Annual Workshop. It 
aims to bring together academic researchers, industry practitioners, regulators 
and stakeholders to share their latest results, gather new problems, explore 
the deep understanding of trustworthy AI, understand the implications of 
trustworthy AI for existing risk management practices and the broader 
regulatory context, discuss the foundations in the design of every AI system in 
terms of those 5 pillars, the practical challenges associated with the 
implementation of the state-of-art trustworthy AI methods, as well as discuss 
the key opportunities and focus areas within trustworthy AI to face the unique 
challenge
 s in the future of risk management in different areas, especially in IoT area.

Topics:

Potential topics include, but are not limited to, the following:

- Novel theoretical achievements for TAI methodology.
- Novel developments for existing TAI techniques.
- Practical deployment of TAI within different domains: best practices and 
lessons learned.
- Reviews highlighting important challenges and open problems within TAI.
- Case studies of use response to TAI techniques and AI model outputs.
- Novel datasets for use within the TAI in application community.
- Discussion on industry areas where how best to leverage TAI moving forward.
- TAI related regulation description and enforcement.

Important Dates:

Abstract submission deadline: 15 February 2022
Paper submission deadline: 01 March 2022
Paper acceptance notification: 01 April 2022
Camera-ready paper submission: 15 April 2022
Workshop: 14 June 2022

Organizers:

Artificial Intelligence Research Center (AIRC), School of Computing, Ulster 
University
IEEE SMC Ireland Chapter (SMC28)

Best regards

Jun
TAI-RM2022 Organizing Chair

Dr Jun Liu | Reader in Computer Science |Director of Artificial Intelligence 
Research Centre (AIRC) | School of Computing | Faculty of Computing, 
Engineering and the Built Environment | Ulster University at Jordanstown 
Campus| Shore Road, Newtownabbey BT37 0QB | County Antrim, Northern Ireland, 
UK| Tel: +44 (0) 28 95365687 | Email: j....@ulster.ac.uk | Homepage: 
https://www.ulster.ac.uk/staff/j-liu | AIRC twitter: 
https://twitter.com/UlsterUniAi



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