Coffee Chat: Mike Frank

Mike Frank, Associate Professor of Psychology, spoke with us on Friday about his research to do with language learning and social cognition in children, his thoughts on the ongoing debate between language as an innate faculty or one that is acquired via general-purpose learning mechanisms, and his assessment of the nature of the gap between machine learning and human cognition. 

Professor Frank's current research investigates questions of language learning in children, from a variety of perspectives ranging from word learning and its relationship to concept learning to pragmatic development and how children learn to participate in a conversation. In addition, he and his lab are collecting large datasets of children's speech in order to answer these questions. Finally, his research focuses on encouraging replication, reproducibility, and openness in the scientific community.  

He also teaches at the undergraduate level about human biology and developmental psychology, and at the graduate level about experimental methods. 

Before becoming the Principal Investigator of the Stanford Language and Cognition Lab, he was a graduate student at MIT under the tutelage of Edward Gibson. While there, he worked on a variety of problems from the development of the mental abacus in Canadian and Indian students to the native speakers of Piraha (a language with no words for numbers) to word learning as pragmatic inference. In our coffee chat, he explained that while he is glad he delved into a breadth of topics as a graduate student, he now employs a depth-first approach in order to meaningfully contribute to our understanding of the world. 

To learn more about Mike Frank, visit his website at https://web.stanford.edu/~mcfrank/.

Written by Pratyusha Javangula

Humans of SymSys: Maika Isogawa

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Maika Isogawa is a sophomore interested in AI. She was a Symbolic Systems Program Summer Research Intern in 2018.

Where are you from? 

I was born in Tokyo, Japan! I lived there until I was about 5, then my family moved to Minnesota. I spent the next few years traveling back and forth between the two.

You took a break from Stanford for a bit. What were you up to? 

I was a professional circus performer. I worked for a show called "Absinthe" by Spiegelworld, and "TOTEM" by Cirque Du Soleil. Both shows were touring, so I lived and worked in the US, Canada, Australia, Japan, Russia, and Brussels. 

What drew you to SymSys? Why did you pick your current concentration?

When I was younger, I wanted to be an Astrophysicist. Then I came to Stanford thinking I would be a Physics Engineering major. After taking a leave of absence, I came back with a whole new set of interests and goals. Symsys offered the most breadth across all of the domains that I wanted to learn more about. My concentration is Artificial Intelligence. Not only is it a field that is rapidly expanding and innovative, but it also parallels the question of figuring out what we are as human beings, too. 

What’s your favorite SymSys-related class that you’ve taken?

LINGUIST130A - Introduction to Semantics and Pragmatics with Chris Potts. I think a professor can really be the difference between a student loving a class vs. hating it - Chris was incredible. Very personable, he kept the class really organized and all of the expectations were set up-front (a simple thing that we don't appreciate until we don't have it). The material was interesting too; it revealed a lot about natural language that we take for granted. NLP is a big question in AI right now too, so I felt like I was learning something that I would actually use in the future.

What's one piece of advice you'd like to offer to younger students?

Be honest with yourself about what you're interested in. It's easy to pursue a major/field for ulterior reasons - maybe its for the promise of financial stability after graduation, maybe it's familial pressure... all valid reasons to pick one path over another. But your time in college will be so much more enjoyable if you're choosing the classes and the path that you actually want to do. 

What's something cool you've worked on? 

Over the summer,  I interned with the HCI department here at Stanford under Mark Whiting and Michael Bernstein. We were researching how teams fractured, using an online environment. In a group of 5 undergraduates, we really got to take initiative with the project: building the entire front-end/back-end of the platform, integrating it with various APIs, gathering data, and submitting a paper to a conference. The work was cool and interesting, but what stood out to me was the people I got to work with every day. Everyone was driven, smart, and so incredibly kind. It was a wonderful environment, and I am so grateful that I had the opportunity to participate in this project.

What (loosely) SymSys-related topic are you excited about right now?

Bio-inspired AI. There's actually a ton of new approaches and theories floating around the AI-world at the moment. Implementation is the toughest part, but I'm really excited to see what comes from new research.

What other groups or activities are you involved with at Stanford?

ULTIMATE FRISBEE. LETS. GO. I play for Superfly, Stanford Women's Ultimate team. I tried out thinking that it would be a nice form of exercise, but instead it became some of my most cherished memories and closest friends at Stanford. Not only do I get to workout with incredibly talented, badass women, but ultimate has a huge community all over the Bay Area, and even around the world. Check us out at ultimate.stanford.edu

Humans of SymSys: David Shacklette

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David Shacklette is a new master’s student in Symbolic Systems. He previously studied a B.A. in philosophy at Illinois Wesleyan University.

Where are you from?

I’m from Des Plaines, Illinois.

What's something cool you've worked on? 

During my Junior year abroad at Pembroke College, Oxford, a professor that I worked closely with asked me to be an intern for the Ordered Universe Summer Access program, which focused on the interdisciplinary works of the medieval polymath, Robert Grosseteste. During this week-long experience, I was responsible for holding mock-tutorials for gifted high school students who were interested in applying to Oxford in the following year. It was a highly rewarding experience, and it was so cool to see how a group of bright young minds interpreted such an interdisciplinary topic.  

What drew you to the SymSys MS program? 

I have always been interested in the philosophical interpretation of traditionally non-philosophical disciplines, which led to a strong interest in philosophy of neuroscience. What drew me to the SymSys MS program was the unique opportunity to approach the philosophy of neuroscience in a highly interdisciplinary fashion, surrounded by an incredible community of faculty and students. 

What are some of your initial impressions of Stanford? 

I’m from around Chicago, so my initial impression of Stanford has to do mainly with the weather here-- it’s absolutely gorgeous. 

What's one piece of advice you'd like to offer to younger students?

Take advantage of ALL of the resources that are available to you here. Don’t just be buried in your books 24/7. Go to that talk that you’re interested in, go to the beach for a weekend, join a band, do whatever you can do to become the best person you can be, not just the best academic (but also don’t fail out). 

What (loosely) SymSys-related topic are you excited about right now?

The ethical and practical consequences of optogenetics. 

Coffee Chat with Tobias Gerstenberg

Today we hosted a coffee chat with new psychology professor Tobias Gerstenberg, who studies casuality in cognition, as well as counterfactuals and responsibility. Gerstenberg started off by detailing his journey to where he is now. As a native German, he initially attended university in Berlin, but later completed a MS and PhD at University College London. He then spent five years as a postdoc at MIT in a computational cognitive science group. 

Gerstenberg is excited to be at Stanford due to the cross-departmental collaborations that occur here, or, in some sense, the existence of SymSys at the faculty level. He interested in intersecting social psychology and AI with his own research and taking part in Stanford’s new Human-Centered Artificial Intelligence initiative

As the discussion about causality went on, Gerstenberg showed students the Heider-Simmel animation as an example of how humans infer social variables and attribute causality in very simple stimuli. Towards the end he also showed some examples of stimuli from his own research on intuitive physics, where study participants observe a falling ball hitting obstacles in a box. 

Written by Lucy Li

Humans of SymSys: Zach Harned

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“SymSys offered me a chance to gain experience and specialization in a few important cognate disciplines.”

Zach Harned is a new SymSys master’s student who is also a J.D. Candidate at Stanford Law School. He is the founder of the Stanford Artificial Intelligence & Law Society (SAILS).

What drew you to the SymSys MS program as a law student? 

Much of the legal/policy/regulatory work in emerging technology requires a multi-disciplinary perspective. SymSys offered me a chance to gain experience and specialization in a few important cognate disciplines. 

What's something cool you've worked on at Stanford? 

One of my favorite Stanford projects is the Stanford Artificial Intelligence & Law Society (SAILS), which I founded in November of 2017. Running this organization has been incredibly fun. We created a lecture series where we brought in speakers working at the forefront of legal or policy issues related to artificial intelligence. We were lucky to find numerous stakeholders to help fund our organization, including Law, Science, and Technology, CodeX, and SPICE. 

What kind of research are you hoping to do in the MS program?

I've been focusing my research broadly on the legal implications of machine learning and artificial intelligence. This is a large and expanding area, so I've been attempting to circumscribe my interest into two main areas. First is FAT/ML, which stands for Fairness, Accountability, and Transparency in Machine Learning. The second area is machine learning in healthcare. In these two areas, there are a variety of novel issues, technologies, and techniques continually developing, all of which have a high impact on society. I've submitted a few papers for publication in these areas, that hopefully will be released soon. I was very fortunate to have fantastic collaborators from computer science and medicine to co-author these articles with me. 

What SymSys-related topic are you excited about right now?

Right now I'm heavily focused on how machine vision applications in healthcare will impact legal liability and medical malpractice. This is a fascinating problem, with many distinct players, complicated and cutting-edge technology, and little precedent. I am investigating how this technology impacts physicians themselves, hospitals as organizations, and software or medical device manufacturers.