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The Professional Engineer’s Role in Artificial Intelligence and Technology

The Professional Engineer’s Role in Artificial Intelligence and Technology

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$129.00 - Professional Engineer’s Role in Artificial Intelligence and Technology

$99.00 - Professional Engineer’s Role in Artificial Intelligence and Technology

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Digital transformation is affecting manufacturing and engineering industries across global markets. Institutions, companies and professionals are adopting Artificial Intelligence (AI) at a rapid rate to create efficiencies, new products & services and respond to market dynamics. AI technologies hold the promise of creating smarter, safer, efficient, and more secure systems. AI is being developed on quantum computers and on multiple distributed edge nodes, while systems are becoming more responsive in thinking, perceiving and acting within time performance constraints. Like the software systems that run an autonomous vehicle, we are seeing AI improve our production lines, streamline our logistics, enhance geological explorations, render dynamic pricing, and deliver better health, safety, security and environmental protection (HSSE). Solutions and applications like customer care, cognitive visual inspection, cognitive auditory inspection, production optimization, and equipment  maintenance advisor is growing rapidly. Success will depend on experienced professionals who are responsible, accountable, and liable for the deployment, monitoring, and management of the system’s performance, nurturing it as an intelligent workflow, that delivers business outcomes just as a human would, but at much faster speed and unprecedented scale. Designers are becoming increasingly confident at applying multi-technology advancements to solve large, complex, uncertain, and often ambiguous challenges. As the AI technologies become more prevalent and accessible, an interdisciplinary set of skills and professionals are collaborating to transform industries. Can we use AI to empower other technologies and processes including the Internet of Things, robotic process automation, and additive manufacturing for accurate data acquisition and analysis, with real- time model development and prediction? To do so, we must utilize an open, resilient and robust platform that is enterprise ready with policies set by professionals concerned with the overall effectiveness and efficiencies. Principles and discipline cannot be minimized to reduce risks, support mitigation strategies and enhance sustainability and reliability. Many institutions and collaborative groups are using or building platforms to prepare, clean, deploy and govern models that eliminate non-value add activities. Engineers, business users and data scientists are focusing on the analysis and model to produce answers and options for these emerging AI technologies that drive enterprise intelligent workflows. The presentation describes the key drivers, constraints and disciplines used for the implementation and impact of AI technology when applied to solve precise and measurable problems, often problems the industry doesn’t even know it has. Now with enough implementation data and experience, the community can move beyond trial by design innovation and into adoption to rapidly realize results with measurable outcomes. However, for the executives, project managers, engineers, developers, statisticians, and operators to adopt these AI infused intelligent workflows, each must understand the role they play. We recognize that in order to truly maximize the efforts with these technologies, the solutions must be used within the ethics of our communities, monitored to remove bias, and safeguard the public’s health, safety, security and environment with a minimum standard of care governed by people collaborating in a constantly evolving network. No longer is this an emerging technology held captive in pilot “proof of concept” purgatory. Much like historical transitions from Agriculture to the Industrial Revolution, and then Industrial to the Information Age, the transition to the Cognitive Era has arrived. With proper oversight, discipline, accountability and engineering on a secure platform and architecture, we will see AI make a significant and measurable difference.
 
 
 
Presenter: Dr. Ben Amaba , P.E., LEED AP, CPIM, BD+C
Dr. Ben Amaba is IBM's Global Chief Technology Officer (CTO), Data Analytics and AI Elite Team, Industrial Manufacturing. His focus and research is in applying engineering analytical skills in solving business, operations and technology challenges on a global level.  Dr. Ben A. Amaba holds a PhD. degree in Industrial & Systems Engineering from the University of Miami in Coral Gables, Florida, a M.S. degree in Engineering Management, and a B.S. degree in Electrical Engineering.
 
Publications include “Process Activity Flow Framework: The Management of Information Technology in an Extended Software Development Environment”, “Financial Decision Making in Information Technology Capital and Expense Budgeting”,  “Requirements Management and Business Driven Development in the Software Industry”, “Financial Analysis and Information Uncertainty in New Product Development”, “Usability Engineering” and “New Product Development in Private Marketplaces.” Dr. Amaba is a registered Professional Engineer in the State of Florida, certified in Production and Inventory Management by APICS ©. Dr. Amaba holds positions as a Director on the International Association of Management of Technology (IAMOT), Executive Advisory Board Member to the University of Miami and University of Central Florida, and Advisory Board Member to the Graduate Business School at Florida International University. Dr. Amaba has been awarded Excellence in Graduate Studies. Dr. Ben Amaba is on the staff of the Department of Industrial Engineering at the University of Miami and is an IBM Global Executive. 
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