Background: AI-based coding assistants such as GitHub Copilot, ChatGPT, and Amazon CodeWhisperer are transforming software development by automating tasks, generating code, and supporting prototyping. While these tools enhance productivity, they also pose ethical risks, including copyright violations, insecure code, and ambiguous accountability. Such risks may remain hidden during development but emerge later as legal, social, or technical liabilities. Existing constructs, such as technical debt, are insufficient to capture these challenges. Aims: This paper introduces and formalizes the concept of ethical debt—the accumulation of unresolved ethical risks in AI assisted software development. The objective is to conceptualize ethical debt as a distinct construct, identify its causes and consequences, and establish a research agenda for addressing it. Method: Inspired by the metaphor of technical debt, the paper develops a framework for ethical debt that defines its sources, manifestations, and outcomes. The proposed research program involves theorizing its dimensions, mapping accountability across developers, AI systems, and organizations, and designing empirical approaches for its detection and mitigation. Results: Illustrative cases and a structured research agenda demonstrate how ethical risks, typically invisible in early development, can be systematically surfaced and addressed. Conclusions: By framing hidden ethical risks as a form of debt, this work provides both a theoretical foundation and a practical pathway for responsible AI-enhanced software engineering. Ethical debt makes intangible risks visible and actionable, offering guidance for researchers, practitioners, and organizations to integrate ethical responsibility into modern software development.

Blockchain is perceived as a revolutionary technology offering considerable impact on a vast magnitude of sectors including healthcare, supply chain, Internet of Things (IoT), finance, voting systems, property and real-estate management, e-government, higher education, etc. This paper examines the results of an empirical study that conducted ten in-depth, one-to-one semi-structured interviews with Human Resources Management (HRM) experts in order to identify the potential opportunities related to blockchain technology utilization in the HRM domain as well as the anticipated adoption challenges that may hinder its utilization. The study is of significance to both blockchain and HRM researchers who can utilize the proposed opportunities as a future research agenda and work towards mitigating the anticipated adoption challenges.

Agile development processes and User Centred Design (UCD) integration have been gaining increased interest, in part due to the complementarity of the techniques, the benefits each can apply to the other, and the challenges associated with their combination. This paper describes a Systematic Literature Review (SLR) that was conducted on Agile and UCD integration. The aim of this SLR was to identify various challenging factors that restrict Agile and User Centred Design Integration (AUCDI) and explore the proposed practices to deal with them. The study included a total of 71 papers and excluded 80 papers published from the year 2000 till 2012. AUCDI challenges and their respective proposed practices and success factors were synthesized. A description and taxonomy of AUCDI challenges and its respective success factors and practices were reported. Practitioners can utilise the results in identifying potential AUCDI challenges and practices or success factors to deal with them.

Agile and user centered design integration (AUCDI) is of significant interest to researchers who want to achieve synergy and eliminate limitations of each. Currently, there are no clear principles or guidelines for practitioners to achieve successful integration. In addition, substantial differences exist between agile and UCD approaches which pose challenges to integration attempts. As a result, practitioners developed individual integration strategies. However, success evaluation of current AUCDI attempts has been anecdotal. Moreover, AUCDI attempts cannot be generalized to provide guidance and assistance to other projects or organizations with different needs.