Faculty Interview: Pascal Wallisch

CDS has recently welcomed Pascal Wallisch as a clinical faculty member. He is trained in Psychology with a PhD from the University of Chicago and a postdoctoral Fellowship at NYU’s Center for Neuroscience. He has received the Golden Dozen and Teach/Tech Awards for his teaching at NYU and a Booth Prize for Excellence in Teaching for his teaching at Chicago. His textbook “Neural Data Science” was published by Academic Press. Colton Laferriere, from CDS’s social media team, took a moment to talk with Pascal about his increasing interest in data science, the importance of data in our world and teaching NYU students.

The following has been edited for clarity,

CL: My first question is if you could just give like a brief overview of how your sort of expertise, the cross-section between psychology and data science and how you got into that originally

PW: Where to start. I have always liked numbers and coding since I was a little kid. My memory is that I started coding before I could write but I know that can’t be true. I think realistically I started coding in third grade.

But I’ve always liked coding and numbers, and I was actually a physics and math major in high school in Germany so those have always been interests of mine. One thing I realized, though, when I did that is (in the late 1990s) physics and math were extremely mature fields and Psychology was not, so there are more opportunities to make a contribution. That’s how I got interested in psychology. While studying psychology, I realized that I needed to go deeper and that’s how I got into neuroscience and by going deep into neurophysiology, I realized we don’t really yet have the empirical methods to get the data we need to answer the theoretical questions we are interested in. So that’s why I went back to psychology and got into the recording of high throughput behavioral data. Doing that, I realized that the rate limiting step in all of this is data and data analysis, not so much domain knowledge per se.

CL: What sparked your transition academically towards data science and coming over to CDS.

PW: I do believe we are living in the age of data. I’ve been telling my students this for a while now. I sincerely believe that the most important resource in the 19th century was coal and the most important resource in the 20th century was oil. It seems obvious to me that in the 21st century, this resource is data — structured quantitative information. If you look at all the major companies that now drive our economy, like Amazon, Google, Facebook or Netflix. What do they all have in common? They all have lots of data and they found ways to analyze and monetize it.

In the Psychology Department, I teach quantitative courses involving data analysis or coding and I’ve been telling students that “in the future, there will really only be two kinds of jobs. Either you tell a computer what to do, or a computer will tell you what to do, and both of these will be informed by data. And that’s it. Your only real choice is on which side of the computer you want to be on.”

I really do believe this — that the 21st century will essentially be about data — and it’s going to transform every aspect of our civilization. This is not a bold prediction, because it is already happening. So for our modern graduates, I have just one word: “Data”.

CL: I’ve read multiple times now that you’ve received the Golden Dozen award for teaching. What is your favorite thing about teaching NYU students?

PW: Well, they’re generally smart and intellectually curious. It is also fair to say that — on the whole — the primary interest of the students I’m teaching right now in the Department of Psychology is not data analytics. And that’s fine — that’s not what they signed up for. So I learned how to make challenging materials that students perhaps wouldn’t have sought out otherwise engaging and relevant. But that’s also another reason I’m excited to join CDS. Presumably, CDS students did pick a Data Science major because they are primarily interested in all things data. So maybe I can take things to the next level. I do hope to make a genuine contribution. For some reason that we don’t fully understand, teaching and learning seem to be inherently social activities. As you know, all of the information is out there, online, so people could in principle learn all of this on their own. But most won’t. For instance, MOOCs have a completion rate of between 3 to 5 percent. So in a nutshell, my job is to engage students by making the material as relevant, palatable and exciting as possible.

PW: Another reason why I’m coming to CDS, is I do think we have a bona fide opportunity to create a novel culture here. Data Science is really something new. We have a chance to create a completely new and ultimately civilization changing approach that goes beyond intuition, superstition, prejudice or stereotypes to guide date based decision making under uncertainty. That’s what this is about, hopefully fostering the creation of a more reasonable and rational society. It is probably fair to say that we can really use that right about now.

PW: One thing that I’m very concerned about is that people are getting increasingly good at “lying” with data, but it’s not lying per se. The underlying numbers are probably true, but they found ways to represent (i.e. by processing or normalizing it inappropriately) or present it in a way that pushes a particular agenda and —

CL: Create a narrative that it doesn’t necessarily tell

PW: Exactly. I like the way you put it. Data inspired narratives that are really not justified by the underlying data. So as an educated citizen in the 21st century, you have to know how this is done, otherwise you are liable to be manipulated. That’s why a new R is joining the classical 3R’s of what it means to be educated: “data literacy, in addition to Reading, wRiting and aRithmetic”.

CL: Yeah, and I think when it comes to teaching students who are going to be working with data as their careers, it’s important to, as you said, create a culture where they know how the work they’re doing is going to be used in the real world.

PW: Yes and that is the last thought I’m going to leave you with: How can I, Pascal, make the most impact in the world? And the answer seems to be “by training hundreds if not thousands of students who can handle the data, will use these skills in high stakes real world applications and who have the highest standard of conduct, ethics, and integrity.”