9th International Conference on ICT for Sustainable Development

Authors - Amita Verma, Simran Sankhyayan, Karan Jawanda, Sasha Tandon
Abstract - Generative AI, with its wide range of advantages, has not only transformed the workings of the world but also proved itself as a hallmark of the digital revolution. Generative AI has found applications across various domains, from image and text generation to drug discovery and music composition. However, along with its potential benefits, generative AI also poses significant ethical concerns, including the potential for misuse and the perpetuation of biases present in the training data. Therefore, it is crucial to consider the risks and benefits of this technology. The intersection of generative AI and cybersecurity presents a complex landscape fraught with legal issues and technical challenges. The generation of synthetic data by AI models may inadvertently violate privacy laws, facilitate new ways of cyberattacks, raise questions about consent, anonymization, and data ownership. Detecting and mitigating threats stemming from AI-based content present formidable technical challenges for cybersecurity professionals. Traditional methods of threat detection may prove ineffective against sophisticated AI-generative attacks. Effectively navigating these challenges requires collaboration among policymakers, legal experts, technologists, and other stakeholders to develop comprehensive frameworks that promote innovation, protect individual rights, and safeguard against emerging cyber threats. Ethical development and deployment of generative AI systems requires a holistic approach that prioritizes transparency, accountability, and societal well-being. By addressing these issues proactively, we can harness the transformative potential of generative AI while ensuring a secure and resilient cyber landscape for the future.