Unlocking Careers in AI with Human Language Technology: Q&A with Gus Hahn-Powell
In today's rapidly evolving technological landscape, artificial intelligence has become not only a popular and trending topic but an increasingly inextricable part of culture and business. Currently, AI is used in fields such as healthcare for diagnostics, finance for fraud detection, and customer service for chatbots — enhancing efficiency and accuracy. In the future, AI is expected to advance further in areas like autonomous vehicles, personalized medicine, and advanced robotics, potentially revolutionizing industries and daily life.
Gus Hahn-Powell — an assistant professor of linguistics and director of the Online MS in Human Language Technology (HLT) and Graduate Certificate Program in Natural Language Processing (NLP) in the Department of Linguistics in the College of Social and Behavioral Sciences — recently talked about how the online graduate HLT program at the University of Arizona prepare students interested in AI-related fields for a quickly changing future.
Please talk about your background. How did you transition from pre-AI to being right in the middle of it and equipping students to navigate this innovative, high-pressure, and fast-paced field?
I found HLT through a passion for language. I majored in Japanese as an undergraduate and my first master’s was actually in applied linguistics (second language acquisition). As part of that M.A. degree, I was introduced to corpus linguistics and gained some exposure to using neural networks (which were not fashionable at the time) to model how second language learners develop an understanding of synonyms. Before my master's degree, I was more interested in writing plays and short stories. Math was something I'd avoided, but the experience opened my eyes to the incredible power of programming and machine learning. After completing my M.A., I moved to Japan to teach English.
In 2010, I became convinced that artificial intelligence had the potential to change the world in the coming decades, so I began spending all my nights learning Python and the basics of computational linguistics to prepare myself to pursue an M.S. in HLT/NLP. In 2012, I enrolled in the in-person HLT master's program at the University of Arizona. My intention was to complete the M.S. and go straight into industry, but my curiosity got the better of me and I ended up staying for a Ph.D. I somehow never left! While a Ph.D. student, I started a company with a few colleagues, patented some research, and had the opportunity to work with organizations like the Bill and Melinda Gates Foundation to build an NLP system to help understand the factors surrounding child and maternal health.
Gus Hahn-Powell
What specific technical and soft skills are most crucial for students to master to succeed in this rapidly evolving industry?
The state of the art in our field is endlessly shifting. Students who want to be successful in this world must learn to 1) understand the problem they're trying to solve, 2) communicate the proposed solution, 3) identify the limitations of existing techniques, 4) experiment quickly to "fail fast” and 5) get comfortable reading and summarizing research findings. Many HLT graduates become solution developers embedded within some organizations. Solution developers are tasked with aligning and balancing user needs, resource constraints, and what is technically feasible.
How does the program integrate the teaching of security protocols and ethical considerations into the AI curriculum to ensure graduates are equipped to handle the potential risks and responsibilities associated with its development?
Security and ethical considerations require ongoing conversations and reassessments within an organization. Our curriculum and assignments are designed to help our students identify potential risks (e.g., model bias) and mitigation strategies so that they can make better recommendations to their teams.
Given the interdisciplinary nature of AI, how does HLT encourage student knowledge and experience in peripheral fields such as data science, machine learning, cybersecurity, and ethics?
Since most of the courses in our program are cross-listed with several departments, HLT students will meet and interact with many classmates who are specializing in related fields. To help meet individual goals, HLT students often take courses in neighboring departments to fulfill some of their electives.
What initiatives or projects do you have in place to inspire students to develop AI solutions that address social, environmental, and economic challenges?
HLT students are required to complete six units of internship. The internship is something the student selects with their advisor's approval. Some of our students complete their internships with NGOs or government branches. The internship provides hands-on experience working on a problem that matters to the student.
In the constantly evolving field of AI, how do you ensure the program/curriculum stays current with the latest advancements in research and technology? How do you ensure it stays forward-focused to prepare students for change?
We regularly review and update our curriculum to address major advances and trends in the field, but our emphasis is more on scaffolding foundational concepts. Rather than trying to teach something that is likely to be outdated in six months, we are more interested in helping our students cultivate a problem-solving mindset.
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Register by July 20, 2024, for the Online MS in Human Language Technology (HLT) here.