Building Trustworthy Mobile Apps: Security and Ethical AI Considerations

Abstract

Mobile applications have become fundamental features incorporating artificial intelligence features that present opportunities and responsibilities to developers. The article explores the delicate nexus between creative functionality and ethical application and deals with the natural conflicts between individualization and privacy protection. Detailed models of reliable mobile applications are introduced, discussing authentication schemes in biometric validation and contextual security and privacy-conserving schemes such as on-device processing and federated learning. The reading outlines mitigation methods of bias, explainable interfaces, and audit tools that would be critical in fair ways of deploying AI. Examples of industries in financial services, healthcare, retail and education provide examples of implementation strategies. Security-oriented development guidelines, ethical policies, diverse population testing, and open documentation give practical ways to take responsibility in development. The development of new privacy technology, regulation, standardization, and trust measurement procedures suggests the way forward in ensuring that users are confident in more advanced mobile AI ecosystems.