2024-12-14 –, Rookie track 2
As IoT devices increasingly rely on real-time decision-making, generative AI offers immense potential to enhance these processes by predicting complex data patterns. However, this raises important questions about trust: Can AI be relied upon to make autonomous decisions, and how can we ensure its transparency and ethical integrity? This talk will explore the trustworthiness of generative AI in real-time IoT, covering technical challenges, best practices for ensuring accuracy and reliability, and the role of explainable AI (XAI). We will also address ethical and privacy concerns, providing insights on balancing innovation with responsible AI development.
As IoT devices become increasingly autonomous, the need for reliable, real-time decision-making is more critical than ever. Generative AI has the potential to transform these systems by analyzing complex data and enabling smart devices to predict outcomes and respond efficiently. However, with greater AI autonomy comes the pressing question of trust. Can we trust AI to make decisions accurately and responsibly in real-time? This talk will address the technical challenges in ensuring the reliability of AI-driven IoT devices and explore the role of explainable AI (XAI) in fostering transparency and user confidence.
We will also dive into the ethical and privacy concerns surrounding AI decision-making in IoT, particularly in sensitive or high-risk environments. Through practical examples and best practices, this session will offer insights on how to design AI-powered IoT systems that are not only innovative but also trustworthy, transparent, and ethically sound. Attendees will leave with a deeper understanding of the critical balance between leveraging generative AI for real-time decision-making and maintaining trust in these technologies.
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Currently an Google Developer Group Academy Ambassador at Anglia Ruskin University, Cambridge , I am immersed in a role that aligns with my Bachelor of Technology studies in Computer Science at Anglia Ruskin University. My engagement with the Google Developer Group London sharpens my AI proficiency, reflected in my victory at a TTP plc hackathon where we created 'Co-Pilot', an educational AI tool.
My technical foundation is bolstered by certifications in AWS and Google Cloud, complementing my hands-on experience as an Undergraduate Research Assistant. These experiences underscore my commitment to leveraging AI and neural networks in educational contexts, aiming to elevate learning through innovation and technology.
Final-year BEng Computer Science student specializing in embedded systems. I have developed practical skills through projects involving IoT, systems engineering, and data processing. My experience includes working with generative AI, network management, and information security, as well as pitching innovative ideas like an educational AI system during hackathons. These projects have given me a solid foundation in addressing real-world technological challenges, and I am actively working on embedded systems, further refining my ability to tackle complex issues in the field.