Current

In 2023, the U.S. Securities and Exchange Commission (“SEC” or “Commission”) proposed rules that would have required broker-dealers and investment advisers (collectively, “firms”) to eliminate, or neutralize the effect of, conflicts of interest arising from firms’ use of predictive data analytics (“PDA”) and similar technologies in their interactions with investors. The Commission withdrew the proposal in June 2025 without finalizing it, but the episode remains instructive: it was one of the first serious attempts by a securities regulator anywhere to regulate algorithmic and AI-driven conflicts of interest directly, and its reception illustrates both the promise and the pitfalls of that approach. This article situates the proposal within the broader use of PDA-like technologies in investment advice, examines its substantive provisions, and argues that the rule as drafted was overbroad, inadequately justified, and likely to harm investors, competition, and innovation more than it protected any of them. Drawing on comparative experience—including India’s Securities and Exchange Board’s (“SEBI”) more incremental approach of extending existing suitability and conflict-of-interest obligations to automated advice—the article argues that a narrower rule, tied to the specific risks of opaque, self-optimizing systems and harmonized with the Commission’s existing Regulation Best Interest and fiduciary-duty frameworks, would better serve investors than the Commission’s 2023 proposal did. The analysis is offered both as a critical account of a specific rulemaking effort and as a set of recommendations for regulators, in the United States and elsewhere, who revisit this question in the future.

The largest part of the world's child population lives in Bharat, where various legislations have been introduced to protect the rights and dignity of children. This research paper is primarily aimed at identifying the developmental ramifications of child sexual abuse (CSA) followed by summarizing the roles and responsibilities of educators for child protection with special reference to National Curriculum Framework-School Education (NCF-SE) 2023. The researchers employed a qualitative document-analysis approach to achieve the mentioned objectives. The findings reveal that CSA has multifaceted ramifications on the child's development. The CSA survivors may also tend to suffer from psychological disorders such as Post Traumatic Stress Disorder (PTSD), Dissociative Identity Disorder (DID), sexual and/or substance addiction, hyperactivity, and abnormal neurophysiological issues. The traumatic experience of CSA also lowers the confidence and trust issues of the children which may also ultimately result in poor academic performance and high school dropout rates. With special reference to Indian education policy documents and frameworks, the educational stakeholders, especially educators, are positioned as important adults for recognising concerns, creating safe environments, supporting disclosure, and connecting children with appropriate protection mechanisms. They should be aware of the nature of CSA along with its detrimental impacts on the children. The findings also indicate the central role educators play in enhancing understanding and awareness of CSA among children. Current educational legislation is committed to fostering a safe, secure, inclusive, and joyful learning environment and to strengthening child safety, dignity, and well-being. They play a pivotal role in the inculcation of disclosure skills and imparting age-appropriate personal safety education by eradicating social stigma and myths related to CSA. Ultimately, safeguarding the most vulnerable segment of the population is a moral obligation not only for educational stakeholders but also for every citizen of the world to protect future citizens by creating a truly inclusive, protective, and child-centred community. This study enhances the educational policy discourse by integrating findings on the developmental impacts of CSA with the expectations outlined for schools and educators by NCF-SE 2023. It also highlights the need to link policy commitments to educator training, school protocols, appropriate reporting systems, and child-focused support.

India’s multiple classrooms of diversity are witnessing the rise of growing debates around the concept of Culturally Responsive Pedagogy, otherwise known as CRP, as a central theme in the discourse on inclusive and equitable schooling in the country. A major concern of this paper is to examine the actual implementation of CRP in practice; that is, to look at what specific capacities and dispositions are required and to explore whether current teacher education policies and teacher education frameworks foster teacher development of these capacities. The study’s qualitative secondary data design analyzes the various policy documents and curriculum frameworks, such as the NEP 2020, NPST 2023 and NCFFS 2022, NCFSE 2023, and the Samagra Shiksha 2018 guidelines. This also examines professional development initiatives such as NISHTHA, DIKSHA and relevant research articles on CRP in an Indian context. This paper offers a novel contribution by integrating a competency-focused evaluation of culturally responsive teaching with a methodical review of Indian teacher education policies and initiatives. Instead of analysing CRP competencies and policy alignment in isolation, the research formulates a cohesive analytical framework and use thematic coding to discern the alignment or disjunction between policy expectations and the competencies necessary for culturally responsive practice. The findings highlight a set of teacher attributes that are important, including reflective practice with a social justice and equity lens, flexible multimodal pedagogies and assessment, and a sociocultural awareness and affirmation of other identities and languages. It appears that the recent policy reports in India are conceptually and rhetorically in sync with CRP principles, but it might be more of a coincidence or the pre-service curriculum materials, and in-service trainings are more collective or truncated and have inadequate contextual linkage with classroom context. There are systemic issues as well – large class sizes, a very rigid curriculum, and a lack of support and mentor teachers make it difficult for teachers to implement CRP consistently. The enduring nature of these gaps indicates that alignment of policies at a theoretical level does not inherently lead to equivalent transformations in teacher training or classroom methodologies. The paper argues that ensuring culturally responsive competencies are embedded throughout the four phases of teacher education from basic to secondary and by bolstering place-based learning which is community engaging is critical. Another important step is to strengthen the connection between policy, programme and practice to make CRP a norm in classrooms in India. The study thus provides an elucidative viewpoint on the institutional, political, budgetary, and administrative factors that affect the implementation of CRP concepts from policy texts into educational settings.

As technology advances, chatbots are likely to play a larger role in streamlining consumer interactions and building positive relationships between e-commerce platforms and their customers. This study investigates the influence of Artificial Intelligence (AI)-based chatbots on customer support on e-commerce websites. This topic has received relatively limited attention in the Sri Lankan e-commerce context. Recognising the need for more empirical research on the role of AI-driven chatbots in customer care, this study examines their relationship with customer service experiences in the e-commerce industry. A rigorously developed questionnaire was presented to a sample size of 201 respondents to collect primary data for this investigation. The questionnaire was designed to elucidate the perceived role of AI-based chatbot capabilities in customer service on e-commerce platforms. As prediction models, an array of classification technologies, including Naive Bayes, SVM, MLP, J48 and random forest, were used. The sample's demographic distribution showed a Sri Lankan client base, with 48% male and 52% female respondents. Most participants were between the ages of 25 and 33, while respondents aged 52 years represented the smallest age group. Notably, the J48 decision tree algorithm achieved the highest classification accuracy among the evaluated models, at 100%. These findings are significant for refining and enhancing customer service on e-commerce platforms through the strategic integration of AI-based chatbots. Nevertheless, approach the reported predictive efficacy with caution, given the limited sample size and the need for additional validation with larger, more varied datasets.