Fuzzy Logic-based Explainable AI
Project Background: According to Price Waterhouse Coopers, the global economic impact of Artificial Intelligence (AI) is a mind boggling $15 Trillion, "making it the biggest commercial opportunity in today's fast changing economy" by bringing about the transformation of productivity resulting in GDP growth. To realize this immense economic potential for the safety and mission critical arena such as Health Care, Transportation, Aerospace, Cybersecurity, and Manufacturing existing vulnerabilities need to be clearly identified, and addressed. The end user of such applications as well as the taxpaying public will need assurances that the fielded systems can be trusted to deliver as tasked. Moreover, recent developments evaluating the trustworthiness of high performing black-box” AI has classified them using the term "Brittle AI". These developments coupled with a growing belief in the need for "Explainable AI" has led major policy makers in the US and Europe to underscore the importance of "Responsible AI". Over the past three decades, Dr. Kelly Cohen’s research has been focused on developing fuzzy logic-based AI solutions that are explainable and responsible. Figure 1 illustrates the key principles of Responsible AI.
Research Tasks Proposed:
- Understanding the need for responsible AI and main challenges
- Learning basics of Fuzzy Logic AI programming using MATLAB
- Application of Fuzzy Logic AI to an impactful engineering use case
- Cross-discipline collaboration skills: presentation, writing skills;
- Potential for research publications and presentations at the local and national levels.
Research Location: This research project will be completed in the AI Bio Lab at Digital Futures (third floor, Suite #300)
Professor, CEAS - Aerospace Eng & Eng Mechanics
745 Baldwin Hall