Graduate Story: Chris Steel '90
Image created by Chris Steel '90 with assistance from AI.
Dickinson major: Physics
Current positions
- Artificial intelligence (AI) and machine-learning practice lead, AlphaSix
- CEO/CTO of Syntheticore Inc.
- AI and data analytics consultant, board of directors, University of North Carolina at Charlotte
Overview
Chris Steel ’90 evaluates AI and machine-learning technologies and develops customized plans to use them effectively and safely in areas such as cybersecurity. He also leads a team of more than 30 tech consultants and he advises the University of North Carolina at Charlotte on the use of generative AI, machine learning and data analytics in education.
A textbook Steel coauthored, Core Security Patterns (Prentice Hall, 2005), is used at several universities, and he has a patent pending for an AI-based synthetic-data generator.
How he got there
Dickinson’s physics program was one of the first in the nation to adopt a hands-on approach to computer education. And as an undergrad, Steel seized the opportunity to learn to code—and help others do the same—as a student worker in the computer lab. That paved the way to a computer programming job at the defense contractor SAIC. After a few years, Steel broadened his skillset, taking courses in object-oriented programming, design and C++.
As he progressed through his career, Steel continued to update his skills and to learn all he could about emerging technologies. He applied that knowledge in a variety of senior-management and tech-focused roles, including leading the D.C.-area Java Center for Sun Microsystems, while launching a successful consultancy in enterprise software development.
In 2016, Steel formalized his AI knowledge by taking online classes. His AI certification led to a leadership role at IQVIA the following year, where Steel evaluated and developed strategies for emerging technologies, built customized models and led a global team of data scientists, machine-learning engineers and business leaders. Seven years in, he transitioned to his current position.
What it takes
Lifelong learning, technical skills, clear communication and strategic, forward-looking thinking are essential to Steel’s success.
Steel devotes a good deal of time to learning about new technologies, reading and attending conferences, analyzing tools and processes, and determining how best to harness technology to improve efficiency and accuracy in ethical, safe and secure ways. This includes analyses of new and existing AI tools and customizations of those tools as well as recommendations to harness big data to solve specific problems and address challenges. To build new and customized models, Steel must also keep his coding skills relevant.
Communicating effectively with both technical and nontechnical stakeholders is critical, as Steel explains how and why learning a specific technology or process is a wise use of time and effort.
Career advice
Students and alumni interested in developing AI tools should begin with a solid foundation in math, Steel advises; he says that linear algebra and statistics are particularly helpful. He also sees a need for professionals who are skilled in global languages to help guide AI translation and communication development. Those interested in such a career path might consider learning coding, such as Python, as they deepen their language and cultural knowledge.
“There are a lot of directions you can go and a lot of areas you can work in. But honestly, don’t ask me for advice,” he says. “Ask GPT.”
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Published July 1, 2024