Q: What is your organization’s role in XMANAI?

A: Knowledgebiz is the dissemination leader of the project and one of the main technical developers of the core Artificial Intelligence bundles for algorithm lifecycle management, responsible for the implementation of the module for industrial asset and Knowledge graphs modeling. In the first half of the project, Knowledgebiz has also been responsible for the elicitation of platform requirements and the definition of AI scenarios.

Q: How does XMANAI relate to your or your team’s background and interests?

A: During this decade, Knowledgebiz has been extending its domains of intervention and specializes in the application state of the art technologies for digital transformation. Knowledgebiz has had in data management one of its major business revenue lines, providing consultancy for industry 4.0 adoption and data analytics solutions. We strive to create opportunities that support the modernization of the different sectors and strongly believe in the need to embrace and exploit the new opportunities provided by the digital era, where many of the technologies addressed in XMANAI play a key role. Our current services offering includes big data analytics solutions for improved businesses, digital transformation solutions for industry 4.0, gamification solutions and personalized engagement strategies, risk management and compliance solutions, performance measurement solutions, and multi-criteria analysis.

Q: What is the novelty of XMANAI and the main benefits envisaged for your organization?

A: Despite the indisputable benefits that Artificial Intelligence can bring in society and in any industrial activity, humans typically have little insight into AI itself and even less concerning knowledge of how AI systems make any decisions or predictions due to the so-called “black-box effect”. Many of the traditional machine learning/deep learning algorithms are opaque and not possible to be examined after their execution to understand how and why a decision has been made. In this context, and with a specific application to the manufacturing sector, XMANAI introduces Explainable Artificial Intelligence through a platform that is capable to increase trust in AI systems by providing humans (especially business experts from the manufacturing domain) the ability of fully understand how decisions have been reached and what has influenced them. Knowledgebiz is a technology innovation company that aims to transfer the most advanced technologies to the markets where we operate and achieve the highest standards of customer satisfaction. We target to capitalize on the experience acquired in XMANAI explainable techniques to improve the spectrum and quality of digital transformation services we are providing to our customers. Artificial Intelligence combined with knowledge representation and reasoning techniques is key to providing valuable business opportunities.

Q: Which target groups can benefit from XMANAI?

A: XMANAI has a trustful ”human-centric” approach that is respectful of European values and principles, adopting the mentality that “our AI is only as good as we are”. The aim is to transform the manufacturing value chain with ‘glass box’ models that are explainable to a ‘human in the loop’ and produce value-based explanations for:

• Data scientists – to understand the problem at hand, create AI models, and derive actionable insights from data in different application domains.
• Data engineers – to build the necessary underlying infrastructure to collect and prepare data, and to deploy AI models in a scalable manner.
• Business experts – to understand the results of an analysis in a tangible manner and take more informed decisions depending on the pilot case.

Q: As a Dissemination leader, how do you envision the XMANAI progress beyond the state of the art?

A: XMANAI aspires to become one of the flagships and reference Industrial Explainable AI Platforms in manufacturing with a user-driven, industry-led mentality and a market-oriented approach to address the inherent AI-related hurdles in a realistic and tangible manner.
The project will deliver “glass box” AI models that are explainable to a “human-in-the-loop”, without greatly sacrificing AI performance. With appropriate methods and techniques such as lifecycle management, security, and trusted sharing of complex AI assets (including data and AI models), XMANAI provides the tools to navigate the AI’s “transparency paradox” and therefore: (a) accelerates business adoption addressing the problem that “if manufacturers do not understand why/how a decision/prediction is reached, they will not adopt or enforce it”, and (b) fosters improved human/machine intelligence collaboration in manufacturing decision-making while ensuring regulatory compliance. Manufacturers will be able to develop a robust AI capability that is less artificial and more intelligent at human and corporate levels in a win-win manner.