ARTICLE
An Interview With Lisa Becker, Machine Learning Engineer and Educator
Lisa Becker is a Machine Learning Engineer at Pure App and an O'Reilly Educator on Natural Language Processing (NLP). We caught ask Lisa about her career and why she's excited to join us as a speaker at AI for the rest of us.
Tell us your story? When did you start working in AI?
My AI journey began in 2018 when I was applying for a Master’s program. Originally, I was aiming for a career in academia, specifically in neuroscience, given my Bachelor’s degree in linguistics with a focus on neuro- and psycholinguistics, complemented by a minor in ethics. However, the competitive nature of admissions in Germany meant that I didn’t get into my desired program. This setback led me to explore alternative paths, and I discovered computational linguistics and natural language processing (NLP) at my alma mater. Although I was initially intimidated by the idea of programming, I was intrigued by the description of NLP as “trying to imitate the brain’s capabilities to produce and understand language.” Encouraged by friends, I took a leap of faith, did a crash course in Python, and enrolled in the program.
The Master’s program was challenging, especially given my unconventional background, but I made it and eventually landed my first job as a machine learning engineer. Today, my work is far removed from my original academic interests—except, perhaps, for the concept of neural networks, which are inspired by brain cells. Nonetheless, I absolutely love what I do. I’m at the forefront of a fast-paced, ever-evolving field, and I wouldn’t trade this experience for anything. And conferences like AI for the rest of us allow me to indulge in one of my greatest passions: sharing knowledge and making it accessible to all.
Why is AI fluency so important?
AI fluency is crucial for a couple of reasons. First, AI is becoming an integral part of our daily lives. From using facial recognition to unlock your phone to AI-driven recommendations on streaming platforms, it’s all around us. Understanding how these systems work, even at a basic level, empowers people to use them more effectively and safely, and to be more discerning about their impacts.
Second, AI fluency enables individuals and organizations to make informed decisions about adopting AI technologies. It’s not just about using AI but about understanding its limitations, potential biases, and the ethical considerations that come with it. In a world where AI is increasingly driving business strategies, policymaking, and even personal decisions, having a foundational understanding of AI is no longer optional—it’s essential.
What is one thing you’ve learned recently that changed how you think about AI?
Recently, I’ve been further exploring the concept of AI explainability and its importance in building trust. People often think of AI as a black box—input goes in, output comes out, and the process in between is somewhat of a mystery. However, understanding and explaining how AI models arrive at their decisions is critical, especially as these models are deployed in sensitive areas like healthcare, finance, and criminal justice. The more transparent and interpretable we can make AI, the more we can trust it and ensure it’s being used fairly and responsibly. This shift in thinking has made me even more committed to not just developing powerful AI solutions but also making sure they are understandable and trustworthy to everyone who uses them.
Lisa Becker
Machine Learning Engineer
"I’m incredibly excited to attend AI for the rest of us because it embodies my passion for making complex topics accessible to everyone."
Why are you excited to attend AI for the rest of us?
I’m incredibly excited to attend AI for the rest of us because it embodies my passion for making complex topics accessible to everyone. In my previous role as an AI consultant, I thrived on the challenge of explaining all sorts of AI concepts to people with varying levels of technical expertise or AI literacy. This conference amplifies that mission on a larger scale—ensuring that everyone, regardless of their background, gains a solid understanding of basic AI concepts. The idea is not just to educate but to empower attendees, helping them feel more confident and secure in using AI tools or making decisions that impact their organizations. It’s about democratizing AI knowledge and making sure no one feels left behind in this quickly evolving field!
What can attendees expect to learn from your session?
Everyone has been talking about LLMs since the advent of ChatGPT. However, there’s a tendency to over-rely on LLMs simply because they seem easy to use—after all, anyone can type a prompt in natural language. The problem is that using LLMs indiscriminately is like trying to remove a tooth with a wrecking ball—it might work, but it’s definitely not the best approach. In my session, I’ll go into why a machine learning engineer is like a skilled dentist, equipped with a range of tools—drills, probes, mirrors—each designed for a specific task. The key is knowing which tool to use for the job at hand, refining that tool as needed, and clearly communicating the process and outcomes to stakeholders—just like a dentist would. While LLMs are powerful, they come with significant limitations, and understanding when and how to use them (or not) is crucial. My talk will demystify this process and provide practical insights into making more informed AI decisions.
What other talks are you excited about attending and why?
I'm really looking forward to a few talks that align with both my professional interests and my background in the humanities. For example, the session on "Anatomy of an AI Hackathon" is particularly exciting to me. I love community-driven events like hackathons, and hearing how Waitrose pulled off an AI Hackathon in just eight weeks is inspiring. It’s practical insights like these that I could see myself applying if I ever decide to organize a similar event in the future.
Another talk that caught my attention is "Never Neutral: AI Development, Past, Present, and Future in Anthropological Research." My background in linguistics and ethics gives me a deep appreciation for understanding AI beyond just the technical aspects. This session explores how AI is shaped by human values and cultural dynamics, drawing from the work of anthropologist Diane Forsythe. It’s a reminder of the importance of keeping the human element front and center in AI development, which is something I’m passionate about.
Lastly, "AI Transparency, Law, and Policy" is a must-attend for me. As AI continues to grow, understanding its legal and ethical implications is crucial. This session promises to provide practical guidance on navigating the complex landscape of AI governance, which ties directly into my interest in ensuring that AI is developed and deployed responsibly.
These talks resonate with my passion for blending technology with a deep understanding of human and cultural contexts, and I’m excited to bring these insights back to my work. Of course AI for the rest of us has many more exciting talks that I’m excited to be attending!
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