Ida Skubis – författare

This book systematically investigates the linguistic strategies employed in beauty product advertising to assess their persuasive and manipulative effects. The work is divided into two sections: a review of relevant literature and an empirical analysis of advertisements. The analysis initially focuses on the linguistic features of advertisements created by humans prior to the introduction of ChatGPT, examining the linguistic measures used and their methods of persuasion and manipulation. Subsequent sections provide a detailed examination of advertisements generated by ChatGPT versions 3.5 and 4.0, analysing the artificial intelligence’s use of linguistic techniques. This includes a meta-analysis where ChatGPT itself discusses the linguistic strategies it employs. The ultimate goal is to compare and contrast the effectiveness and linguistic devices used in advertisements crafted by humans and those by ChatGPT, analysing how AI influences the language of advertising and its impact on consumer behaviour.

The book explores how technology is transforming business operations and organizational management. To thrive in the digital world, companies need to be flexible, forward-thinking, and above all, human-centered. The book examines four key areas for attaining these goals: Traditional management approaches are insufficient in today’s digital landscape. Companies must adopt innovative management models incorporating artificial intelligence, big data, and digital platforms to maintain competitiveness. These technologies enable process automation and data-driven decision-making, though implementation faces challenges including high costs and resistance to change.Sustainable innovation is a strategic necessity rather than a voluntary action. This dual-externality innovation type requires balancing environmental protection with enterprise competitiveness, demanding both internal management changes and external stakeholder engagement.Corporate finance should evolve beyond traditional profit optimization, incorporating digitization, sustainability, and decision psychology. Modern financial management requires adaptability to dynamic market conditions while considering broader strategic implications.Humanoid robots are a growing presence in enterprises. There should be a focus on human-centric, ethical implementation approaches that augment rather than replace human capabilities while addressing privacy, bias, and accountability concerns.Business management today is as much about understanding technology as it is about making thoughtful and ethically sound choices. This book shows a way for organizations to remain effective by building strategies based on clarity, responsibility, and respect for the people involved, both within and outside the organization.

Human–AI Collaboration in Research: Practical Applications, Ethical Frameworks, and Future Directions positions human–AI collaboration (HAIC) as a defining feature of contemporary research ecosystems. The book examines the incorporation of AI across the research lifecycle, including research design, literature work, data collection and processing, analysis, interpretation, academic writing, and dissemination. It highlights the opportunities created by automation and generative systems, alongside the challenges raised for research integrity, accountability, transparency, privacy, and epistemic authority. Ethical and regulatory foundations are addressed through established frameworks such as the Belmont Report and the Declaration of Helsinki, as well as European governance instruments including the Ethics Guidelines for Trustworthy AI, the General Data Protection Regulation, and the EU Artificial Intelligence Act. By combining interdisciplinary perspectives from robotics, management research, and education, the volume translates abstract ethical principles into concrete research-relevant practices, offering a coherent and human-centred approach to trustworthy AI-supported inquiry.The book offers original, research-ready frameworks and applied guidance for responsible HAIC, combining real-world case studies with practical strategies for trustworthy AI use. It equips researchers, educators, and management scholars with tools for human oversight, transparency, bias mitigation, and accountable AI-supported workflows, ensuring scientific rigour alongside innovation.