fXAI Research:
Unlocking the Black Box of AI

Explore the frontier of artificial intelligence with our Functional Explainable AI (fXAI) project, where we unlock the mysteries of AI decision-making. By drawing inspiration from human cognition and social interaction theories, fXAI aims to design AI systems that not only perform tasks but also explain their decisions in ways we can all understand. This initiative bridges the gap between complex AI technologies and everyday usability, enhancing transparency, fostering trust, and ensuring AI accountability. Join us in shaping a future where AI and human collaboration thrive.

Background

In an age where artificial intelligence influences everything from healthcare to personal finance, understanding how these AI systems make decisions is crucial. Explainable AI (XAI) seeks to peel back the layers of complex AI models, providing clarity on how decisions are made. This transparency is essential not only for trust but also for accountability, ensuring that AI decisions can be evaluated and understood by everyone. Our project, focusing on Functional Explainable AI (fXAI), aims to advance this goal by developing AI systems that offer clear, understandable explanations for their operations, making them as interpretable as they are powerful.

Vision Statement

Our vision for fXAI is to transform AI interactions into experiences that mirror human-to-human communication in their clarity and intuitiveness. By integrating insights from cognitive sciences and social interaction theories, fXAI aspires to create a new breed of AI systems. These systems will not just perform tasks but will also explain their reasoning in a manner that is accessible to all, regardless of their technical background. This human-centric approach will enable users to make more informed decisions, fostering a collaborative environment where humans and AI work together to solve complex problems.

Proof of Concept

Through rigorous testing and creative experimentation, we've explored how modifying machine learning architectures can enhance AI communication and decision-making processes. Our experiments have shown that even slight adjustments can significantly improve how these systems interact and explain their decisions. This proof of concept underscores the potential of fXAI to transform AI into a tool that is both powerful and comprehensible, paving the way for innovations that could revolutionize various sectors.

Real-World Applications

fXAI is poised to make significant impacts across multiple fields, demonstrating the versatility and necessity of explainable AI. In biomedical informatics, fXAI could revolutionize how medical data is interpreted, leading to faster and more accurate diagnoses. In the realm of data visualization, fXAI aims to transform complex data sets into clear, understandable visual formats that assist decision-making and insights. These applications show just a glimpse of fXAI’s potential to enhance how professionals and everyday users interact with AI, making advanced technology an accessible ally in diverse disciplines. End products of these project includes XAI models for applications across disciplines, a game from which an AI can learn from, an educational app and animation to teach AI to the next generation.

Interested in contributing or learning more? If you want to check whether you are a good fit for the project, then you are encouraged to reach out and explore the possibilities with us. Discover Your Fit on our website to see how your expertise aligns with our needs. We are excited to welcome diverse perspectives and skills to enrich our project and look forward to discovering how your unique abilities can contribute to advancing our goals. Join us in shaping the future of AI!

For speaking requests and inquiries, please contact:

Rittika Shamsuddin ileadlabml@gmail.com