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What is the role of humans and AI in collaborative intelligence teams for Industry 5.0?

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Collaborative Intelligence (CI) is a human-machine partnership that combines the strengths of both humans and AI to achieve better results than either could on their own. CI systems are designed to be co-creative, meaning humans and AI work together to solve problems and make decisions. On the other hand, Industry 5.0 is a new industrial revolution focused on human-centric manufacturing. In this new era, AI can augment human capabilities rather than replace them. CI is essential for Industry 5.0 because it allows humans and AI to work together effectively.

 

Traditional interactions that took place between the human operator (often a data scientist) and AI/ML until now, include:

  • Data labelling: People often label data for ML models. This is especially important for tasks that are difficult or time-consuming for machines, such as identifying objects in images or extracting text from documents.

  • Model training: People can help to train ML models. This can be done by providing feedback to the model during training or by manually adjusting the model's parameters.

  • Model deployment: People can also deploy ML models in the real world. This can involve monitoring the model's performance and adjusting as needed.


The above can be considered as basic forms of CI. But going one step further towards Industry 5.0,  the collaboration between the human and the machine should become more advanced and result in the formulation of actual human-machine teams, where both sides complement each other with their inherent capacities and skills. 

 

In such settings, collaboration can go further than labeling and monitoring:

  • Machine learning with human feedback: This is a type of CI where humans provide feedback to AI systems to help them learn and improve. For example, humans might be asked to label data or correct errors in the AI system's output. The clearest example of this category is the HITL solution.

  • Co-creation: This type of collaborative intelligence is where humans and AI systems work together to create new products or services. For example, humans might provide AI systems with their ideas and feedback, while AI systems provide humans with access to new data and insights. The clearest example of this category would be the emerging Large Language Models (LLMs)

  •  Augmented intelligence: This type of CI uses AI systems to augment human capabilities. For example, AI systems might provide real-time assistance to doctors, help pilots fly planes or any other related activity.


This was just a sneak peek from deliverable D5.1. Inside the deliverable you can read more about Collaborative Intelligence, AI/MLOps Lifecycle, Open Hardware Solutions for Edge AI, and how all these will be part of the AI REDGIO 5.0 project.

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