Calls for Papers (special): Journal of Cases on Information Technology (JCIT)


Special Issue On: Digital Transformation for Regulation 4.0

Submission Due Date
11/30/2023

Guest Editors
Saikat Gochhait
SIDTM Symbiosis International Deemed University, India
(saikat.gochhait@sidtm.edu.in)

P. Vigneswara Ilavarasan
Indian Institue of Technology Delhi, India
(vignes@iitd.ac.in)


Introduction
As incumbents are embracing "industry 4.0"- the industrial revolution for the digital age - regulation will need to follow suit by embracing "regulation 4.0" - the regulatory approach for the digital age. In this report, we set out two future scenarios for how regulators will respond to innovation and why this matters for incumbents' digital transformation.
The rise of information technology (IT) in organizations has been an inherent part of an agenda to increase and shape forms of social control. Despite the inherent link between uses of IT and social control, the topic of regulation has not received significant attention in the information system field - neither theoretically nor empirically. This special seeks to address this gap. The issue explores the growing and significant interplay between IT and regulation in the age digitalization, where new challenges with social control with IT are emerging. In this special issue, we are interested in two broad domains of research related to regulation and IT: regulation through IT and regulation of IT.
The first domain - regulation through IT - concerns new forms and arenas of regulation enacted through innovative IT solutions (often called "RegTech"). These technologies which are increasingly implicated in regulatory practices include new forms of real-time big data analytics, machine learning and other artificial intelligence (AI) techniques, use of blockchains and distributed ledgers, Internet of Things solutions or natural language processing techniques. These technologies change the ways organizations and industrial sectors respond to and comply with a growing number of regulatory obligations and needs (Butler and O'Brien, 2019; Gozman et al 2018). These technologies are also driving changes in the ways in which regulators seek to supervise and monitor firms and the ways in which firms comply with laws and regulations.
Greater market and organizational transparency and enhanced supervision are now advocated as critical responses to organizational misconduct and associated risks (Currie, Gozman and Seddon 2018; Roberts, 2009). This has resulted in an increasing call for bureaucratization and (over-)regulation (Graeber, 2013). Call for greater monitoring, supervision and sanctioning have been driven by concerns regarding the environment, health and safety risks, corporate fiscal and fiduciary scandals (e.g. Enron), financial failures leading to financial crisis in 2007-2008, or growing violations of data privacy (e.g., General Data Protection Regulation) increased the "volume, velocity and variety" of laws and regulations that organizations must comply with and the range of novel IT based solutions they need to comply to such demands (Gozman and Currie, 2014; Vaujany, Fomin, Haefliger, and Lyytinen, 2018; Butler & O'Brien, 2019). Regulators have also shown a growing appetite to measure performance, to quantify financial, regulatory and operational risk and to improve compliance reporting through new technologies that assign accountability, enforce security and behavioral control, automate monitor and enhance record keeping (Williams 2012; Baskerville et al. 2018).
The second domain - regulation of IT - is the wide range deployment and associated regulatory effects of new IT (esp. concerns of security, privacy and/or safety). There is a notable gap in the field's knowledge regarding new demands and ways of regulating IT (e.g., social media) given its scale, complexity and pervasive use. Concerns regarding the pervasive effects of platform businesses (e.g., Facebook, Google, Amazon etc.) on privacy, competition and information veracity have invited calls to control and scrutinize technology vendors (e.g., Zuboff 2015, 2019). Similar issues are likely to emerge in autonomous cars, user-based insurance, health policies and so on. There are consequently increased demands to regulate various IT solutions and to increase regulatory powers of governments related to IT uses, including through introducing entirely new regulatory bodies. If platform providers and vendors, or organizations offering extensive algorithmic solutions as parts of their related services (e.g., Uber), are subjected to new regulatory structures, then important questions arise regarding what degrees of transparency reporting are appropriate and how related forms of supervision and sanctioning would function that need to regulate actual systems and their functioning and those who are implicated in their design.
We invite empirical and theoretical research that contribute to our understanding and application how regulation is enacted through IT or how uses of IT can be regulated. We encourage submissions that use diverse epistemological and methodological approaches to focus on emerging and new regulatory solutions and practices. Submissions may engage in cross-disciplinary inquiries and should offer novel knowledge and fresh methodological approaches to focus on emerging and new regulatory solutions and practices. Submissions may engage in cross-disciplinary inquiries and should offer novel knowledge and fresh methodological, theoretical and empirical insights how regulation and IT evolve and are related. The papers will be evaluated for their interestingness, novelty and credibility of the contribution. If in doubt, interested authors should consult the special issue guest editors whether their papers fall within the scope of the special issue. To this end, authors are encouraged to submit an extended abstract to the editors for initial feedback.
Baskerville, R., Rowe, F., & Wolff, F.C.(2018). Integration of Information Systems and Cybersecurity Countermeasures: An Exposure to Risk Perspective. The Database for Advances in Information Systems, 49(1), 33-52.
Butler, T. (2017. Towards a Standards-based Technology Architecture for RegTech. Journal of Financial Transformation, 45(1), 49-59.
Butler. T., & O'Brien, L. (2019). Understanding RegTech for Digital Regulatory Compliance. In: Disrupting Finance, pp. 85-102, Palgrave.
Currie, W. L., Gozman, D.P. & Seddon, J.J. (2018). Dialectic Tensions in the Financial Markets: A Longitudinal Study of Pre- and Post-Crisis Regulatory Technology. Journal of Information Technology, 33(4), 304-325.
De Vaujany, F.X., Fomin, V.V., Haefliger, S., & Lyytinen, K. (2018). Rules, Practices, and IT: A Trifecta of Organizational Regulation. Information Systems Research, 29(3), 755-773.
Gozman, D., & Currie, W. (2014). The Role of Investment Management Systems in Regulatory Compliance: A Post-Financial Crisis Study of Displacement Mechanisms. Journal of Information Technology, 29(1), 44-58.
Gozman, D., Liebenau, J., & Mangan, J. (2018). The Innovation Mechanisms of Fintech Start-Ups: Insights from Swift's Innotribe Competition. Journal of Management Information Systems, 35(1), 145-179.
Graeber, D. (2015). The Utopia of Rules: On Technology, Stupidity, and the Secret Joys of Bureaucracy. Melville House.
Roberts, J. (2009). No One Is Perfect: The Limits of Transparency and an Ethic for 'Intelligent' Accountability, Accounting, Organizations and Society 34(8): 957-970.
Williams, J. W. (2013) Regulatory Technologies, Risky Subjects, and Financial Boundaries: Governing "Fraud" in the Financial Markets, Accounting, Organizations and Society 38(6), 544-558.


Objective
As incumbents are embracing "industry 4.0" - the industrial revolution for the digital age - regulation will need to follow suit by embracing "regulation 4.0" - the regulatory approach for the digital age. In this report, we set out two future scenarios for how regulators will respond to innovation and why this matter for incumbents' digital transformation.

Recommended Topics
Domain 1: Regulatory technologies for supervising and complying ("regulation through IT")
  • Theoretical analyses and frames for understanding regulatory technologies and how they shape social control and its various forms.
  • New roles and demands for IT based audits and related challenges.
  • The changing role of IT for regulatory intelligence and change management.
  • Managerial implications of regulatory technologies in vertical industries such as financial services, pharmaceuticals, petrochemicals, healthcare, aviation etc.
  • The nature, scope and effects of digitization of governance, risk and compliance practices and related mechanisms.
  • Innovation and entrepreneurship in regulatory technologies (e.g., sandboxes, incubators, accelerators).
  • C-suite roles and responses with regard to regulatory technologies and the changing nature and role of regulatory function organizations.
  • Technologies for identifying, monitoring and mitigating operational and financial risks
  • Managing organizational failures using RegTech.
  • Using digital technologies to address anti-money laundering (AML), terrorist financing and fraud.
  • The use of regulatory technology in developing countries.
Domain 2: Regulating new technologies and platforms ("regulation of IT")
  • Regulation of social media technologies and platforms.
  • Regulation of IT solutions and related solutions during design, implementation and use
  • Regulation of AI.
  • How to bridge the gap between ethics and policy (e.g., for AI)? Where is the overlap and divergence?
  • Strategic implications of regulating technologies for nations, industries and firms.
  • Solutions for data privacy, protection, governance and "fake news".
  • Cybersecurity obligations and mitigating related risks at the organizational level including network security and defense systems implementation and management.


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Digital Transformation for Regulation 4.0 on or before November 30th, 2023. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations. This is a full open access journal. Authors of manuscripts that are accepted to publish in this special issue will be expected to pay the article processing charge.

Open Access Resources:

All inquiries should be directed to the attention of:
Saikat Gochhait
Guest Editor
Journal of Cases on Information Technology (JCIT)
Emails: saikat.gochhait@sidtm.edu.in

P. Vigneswara Ilavarsan
Guest Editor
Journal of Cases on Information Technology (JCIT)
Emails: vignes@iitd.ac.in
Submit a Manuscript to: Digital Transformation fo...

Special Issue On: Explainable Deep Learning on Multimedia Computing

Submission Due Date
11/30/2023

Guest Editors
Shoulin Yin
Harbin Institute of Technology, China
(yslin@hit.edu.cn)
Asif Ali Laghari
Sindh Madressatul Islam University, Pakistan
(asif.laghari@smiu.edu.pk)


Introduction
Deep learning (DL) provides computational models of multiple processing layers to learn and represent data with multiple levels of abstraction It is able to implicitly capture intricate structures of large-scale data and ideally suited to some of the hardware architectures that are currently available. DL has recently achieved outstanding performance in academic and industrial fields, and become a vital utensil in a wide range of multimedia computing tasks, including VI(video image) processing, multimedia data compression, etc.
DL, especially deep neural networks, and artificial intelligence, have contributed to the recent big progresses in a wide range of research and applications in computer vision, intelligence systems, and natural language processing tasks, etc. As DL related technologies become more ubiquitous, researchers in the whole DL community find that the need to trust these DL based systems with all manner of decision making is paramount. Despite the unprecedented practical success of DL in the field of multimedia, the inability to "explain" DL-based models' decisions in a human understandable way still limits their effectiveness. To explain why a DL model achieves a certain result is a so far still extremely difficult, since it is complicated and often impossible to get insights into the internal workings of a model. Therefore, explainable DL (XDL) has started to catch people's attention. Efforts in explainable DL not only attempt to open the "black box" of DL models, but also attempt to develop models that can provide intuitive explanations of the results for the users, and system designers, which can help to ameliorate the model transparency and effectiveness.
While DL models give impressively high predictive accuracy, they are recognized as black-boxes with deep and complicated layers. In the meantime, DLs have been recently reported as defenseless to spoofing with elegant hand-designed input samples. This principally takes place in multimedia computing field, where a single incorrect prediction might be very detrimental, and the trust on the trained DL model and its capacity to deliver both efficient robust data processing must be pledged. Therefore, understanding how the DL models works, and thus creating explainable DL models have become an elemental problem.
Currently, it is still not clear what information must be delivered to DL models, and how DL models work to warrant a rapid, safe and robust prediction. Hence, experts/users request to know the latest research advances of XDL. This critical research topic will bring new challenges and opportunities to the AI community.
This special issue aims to bring together researchers and practitioners in both industrial and academic communities to discuss the interpretability, transparency for DL in the field of multimedia and safety of applying these technologies in critical applications, such as the medical computer-aided diagnosis, the automatic driving systems, and privacy-aware computation tasks. It can provide a diverse, but complementary, set of contributions to demonstrate new developments and applications of XDL, to solve problems in multimedia computing. It is hoped that sufficient progress can be achieved to help improve the DL algorithm's transparency, and explainabilty, while maintaining its power and high accuracy. The ultimate goal is to promote research and development of XDL for multimedia computing by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field.

Objective
To bring together researchers and practitioners in both industrial and academic communities to discuss the interpretability, transparency for DL in the field of multimedia and the safety of applying these technologies in critical applications.

Recommended Topics
  • Multimedia computing tasks
  • VI(video image) processing
  • multimedia data compressions


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Explainable Deep Learning on Multimedia Computing on or before November 30th, 2023. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations. This is a full open access journal. Authors of manuscripts that are accepted to publish in this special issue will be expected to pay the article processing charge.

Open Access Resources:

All inquiries should be directed to the attention of:
Shoulin Yin
Guest Editor
Journal of Cases on Information Technology (JCIT)
Email: yslin@hit.edu.cn

Asif Ali Laghari
Guest Editor
Journal of Cases on Information Technology (JCIT)
Email: asif.laghari@miu.edu.pk
Submit a Manuscript to: Explainable Deep Learning...