About DeW 10.0
The 10th annual Flagship event of IIITDM Jabalpur, Design Workshop (DeW 10.0), will be organised by the Institute in collaboration with the Ministry of Foreign Affairs (MOFA), Japan from February 12-14, 2026. The primary focus of this year's DeW 10.0 is Symbiotic AI in industry 5.0, with a sub-theme of Integrating LLMs for decision support and co-creation in next-generation manufacturing. The aim of DeW 10.0 is to explore methods, cases, and co-creating tools, in which AI systems and humans work as teams in order to jointly solve problems and achieve goals that were unreachable by either humans or machines alone.
The integration of AI into the manufacturing, services, and healthcare is transforming the industry by advancing predictive maintenance, quality control, and supply chain optimisation. Towards a more human-centric and sustainable vision, Industry 5.0, places the workforce at the centre of the production process with emphasis on resilience, ethical innovation, and the symbiosis between humans and intelligent systems. Human-centered AI (HCAI) focuses on creating systems designed and developed by augmenting human intelligence with machine intelligence.
The workshop will emphasize on the concepts related to AI as a computational system that can perform tasks typically requiring human intelligence. With humans in the loop, and the current development in generative AI such as large language models (LLMs) and agentic AI, organisations are performing intelligent data acquisition, management, and processing to analyse large datasets, extract meaningful insights, that support informed decision-making. The workshop aims to bring together people from industry, startups, product developers, research and academics, to share their expertise and technical know-how on related areas including challenges presently are faced for widespread implementation.
However, every new technology comes with challenges. Challenges such as the “black box” nature of AI models, data biases, ethical concerns, and the lack of regulatory frameworks hinder its widespread adoption. Adopting LLM presents challenges like limited algorithmic transparency leading to distrust, data security especially where the information processed is sensitive in nature. Eminent experts from Japan and India, including academicians, product developers, researchers/scientists and industry experts will share their expertise and knowledge. Participants attending this workshop would get first-hand experience of this cutting-edge technology and build confidence in handling related projects in their chosen domain in future. Each participant would be awarded a certificate after they attend all the workshop sessions. The certificate would be a testimony of their newly acquired skill at DeW 10.0.
Scope
AI-Driven Industrial Transformation: Critically examine the role of AI and in particular, LLMs in the transition from Industry 4.0 to Industry 5.0, with a focus on the technical and organisational challenges.
Co-creation for Context-Aware Decisions: Balancing AI's strengths for organizations with human oversight. Co-creation to ensure that decisions are made responsibly with full consideration of context, culture, and organizational values.
AI trustworthiness: The degree to which AI systems can be relied upon to operate transparently, fairly, robustly, and accountably within manufacturing environments. Effectiveness and limitations of existing toolkits for transparency, fairness, robustness, and accountability.
Evaluation and Performance Metrics of HCAI: Cases and lessons learned from HCAI industrial experiments or large-scale rollouts, and advancements with the integration of LLMs based interaction and support.
Design issues for multimodal-AI interactions in the industrial environment: Advancements in multimodal-AI based industrial environment and challenges in designing effective multimodal AI interactions with respect to robustness, and human cognitive load for safe and efficient collaboration.
Security, privacy, and ethical issues in AI deployments: Addressing the issues related to data security, user privacy, and ethical use as AI systems are increasingly deployed in real-world applications.