LEVERAGING GENERATIVE AI FOR SUSTAINABLE DIGITAL EMPOWERMENT IN INDIGENOUS COMMUNITIES

In an endeavour to tackle global inequality through digitalization, this study concentrates on utilizing the capabilities of Generative Artificial Intelligence (Generative AI) to empower Indigenous communities. The aim of this research is to investigate how Generative AI can mitigate socio-economic disparities by safeguarding indigenous knowledge and promoting social justice, all while being conscious of the historical biases faced by these communities. By employing innovative research tools that leverage Generative AI, the researchers delve into its applications within Indigenous contexts in India. Their findings underscore the potential of Generative AI in advancing cultural preservation, strengthening social cohesion, and establishing sustainable economic opportunities. This research sheds light on a transformative path toward digital empowerment and social justice for marginalized Indigenous communitie

An approach to identify issues affecting ERP implementation in Indian SMEs

Purpose: The purpose of this paper is to present the findings of a study which is based on the results of a comprehensive compilation of literature and subsequent analysis of ERP implementation success issues in context to Indian Small and Medium scale Enterprises (SME’s). This paper attempts to explore the existing literature and highlight those issues on ERP implementation and further to this the researchers applied TOPSIS (Technique for order preference by similarity to ideal solution) method to prioritize issues affecting successful implementation of ERP. Design/methodology/approach: Based on the literature review certain issues leading to successful ERP implementation have been identified and to identify key issues Pareto Analysis (80-20 Rule) have been applied. Further to extraction of key issues a survey based on TOPSIS was carried out in Indian small and medium scale enterprises. Findings: Based on review of literature 25 issues have been identified and further Pareto analysis has been done to extract key issues which is further prioritized by applying Topsis method. Research limitations/implications: Beside those identified issues there may be other issues that need to be explored. There is scope to enhance this study by taking into consideration different type of industries and by extending number of respondents. Practical implications: By identifying key issues for SMEs, managers can better prioritize issues to make implementation process smooth without disruption. ERP vendors can take inputs from this study to change their implementation approach while targeting small scale enterprises. Originality/value: There is no published literature available which followed a similar approach in identification of the critical issues affecting ERP in small and mid-sized companies in India or in any developing economyPeer Reviewe

Towards AI ethics-led sustainability frameworks and toolkits: Review and research agenda

Artificial intelligence (AI) is instrumental in building human skills, accessing knowledge, creating businesses, addressing societal concerns–including environmental issues–and much more. However, unfair, inequitable, and biased data usage for AI deployments does exist and raises ethical and sustainability debates and concerns. AI deployment frameworks are majorly developed by standard societies/groups, technology organisations, analyst groups and federal/government agencies. The paper explores the central themes of AI ethics and sustainability frameworks in declarative standards and statements published by various institutions. The paper offers a thematic analysis of the literature on AI ethics-led sustainability frameworks using MAXQDA software and identifies common principles. We show that there are an established 28 AI ethics-led sustainability frameworks that agencies and groups have disseminated. As well, 6 practical AI ethics toolkits/products are evaluated to translate common AI ethics-led sustainability framework recommendations to deploy AI ethics-led sustainability toolkits programmatically. The research findings validate that beneficence, non-maleficence, justice, explainability, autonomy, privacy, and biasedness need severe attention and postulating algorithmic trust based on AI ethics-led sustainability frameworks. The paper contributes to the unique AI ethics-led sustainability body of knowledge to become a helpful resource for both praxis and researchers

Analyzing the interplay between social media analytics and nudges in pandemic control

This study employs a data-driven approach to examine the government's use of data insights and nudges to promote social distancing during the pandemic. Drawing from well-established technology adoption theories, a nationwide online survey was conducted among professionals and postgraduate students adapting to remote work and learning. The study unveils that access to suitable information and communication technology (ICT) significantly influences people's willingness to adhere to social distancing and work from home (WFH). Moreover, respondents' expectations of WFH's impact on job performance emerged as a critical driver for sustained social distancing, with individuals' habits playing a pivotal role in enhancing WFH performance expectancy. Notably, the study pioneers in exploring the psychological effects of government nudges during a pandemic, shedding light on an uncharted aspect of pandemic control strategies

From Physical Food Security to Digital Food Security. Delivering value through blockchain

The objective of this study is to present a technology-enabled public distribution system (PDS) for a developing economy that faces significant leakages and misplacements. It is in this respect that we explore the quantitative benefits of the integration of Radio Frequency Identification (RFID) with Blockchain Technology (BT) in the Indian Targeted Pub- lic Distribution System (TPDS). A mathematical formulation has been proposed to iden- tify the potential benefits of adopting such technologies to minimise the social costs of both human suffering (deprivation cost) and the economic costs associated with it. Sec- ondary data pertaining to the PDS has been analysed to gain insights into the extent of leakages of food grains from the system and the probable benefits of using these technol- ogies in addressing them. The findings of the study reveal that the adoption of the Block- chain-based framework can significantly reduce the overall leakages and eliminate ghost demand from the system. Also, the study recommends the usage of Blockchain technology for information sharing in a secure, scalable, traceable, and transparent environment to address the institutional independence and accountability over the entire TPDS process