Why explainable AI is essential for the growth of industry 4.0

Why explainable AI is essential for the growth of industry 4.0

Researchers from Incheon National University have performed of review of Artificial Intelligence (AI) and explainable AI (XAI) systems and how they will be essential for boosting the growth of industry 4.0

The first industrial revolution witnessed the birth of steam- and water-powered technology, and now, almost two centuries later, humanity has come a long way and is now experiencing its fourth industrial revolution, otherwise known as industry 4.0. To ramp up the speed of the revolution, experts believe that AI and XAI will play an essential role.

What is industry 4.0?

Industry 4.0 is centre around enhancing industrial efficiency, utilising technologies such as the internet of things (IoT), cloud computing, cyber-physical systems, and AI. AI is the predominant driver of industry 4.0, automating intelligent systems to self-monitor, interpret, diagnose, and analyse by themselves.

AI systems such as machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision (CV) will enable industries to estimate their maintenance needs and become more efficient.

To facilitate a seamless deployment and integration of AI systems, the actions and results of these systems must be comprehensible, or ‘explainable’, to experts. The implementation of XAI will be essential for facilitating this, as XAI develops algorithms that produce human-understandable results from AI-based systems.

Assistant Professor Gwanggil Jeon from Incheon National University commented: “Though AI technologies like DL can solve many social problems due to their excellent performance and resolution, it is difficult to explain how and why such good performance is obtained. Therefore, there is a necessity to develop XAI so that DL, like the current black box, can be modelled more efficiently. It will also be easier to make an application.”

The role of XAI

XAI-based methods are classified due to specific AI tasks, for example, the feature explanations, decision-making, or visualisation of the model. The amalgamation of AI and XAI-based methods with industry 4.0 technologies leads to a plethora of precise and high-quality applications.

One of these applications is an XAI model developed using visualisation and ML to explain a customer’s purchasing decision for non-life insurance. XAI can allow humans to interpret and communicate how AI models determine conclusions and take action.

There is a multitude of benefits of using AI in industry 4.0, but obstacles persist. The most notable is the power required for AI systems, the increasing requirement for more cores and GPUs, and the need for refining and hyperparameter optimisation.

The main obstacle is that this data collected and generated from millions of sources, devices, and users introduce biases that impact AI performance. However, this can be managed by XAI methods to explain why the bias was introduced.

Professor Jeon explained: “AI is the principal component of industrial transformation that empowers smart machines to execute tasks autonomously, while XAI develops a set of mechanisms that can produce human-understandable explanations.”

Advancing XAI methods will propel industry 4.0 significantly, and take us one step closer to smart cities, factories, healthcare, and cyber-security.


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