Contact Info

Rick Wash
404 Wilson Rd #402
402 Communication Arts and Sciences
Michigan State University
East Lansing, MI 48824
wash@msu.edu

Cell: (734) 730-1188
Office: (517) 355-2381

I am an Associate Professor at Michgian State University in the Department of Media and Information.

My research focuses on understanding how people think about and reason about their use of technology, with particular focuses on information security, crowdsourcing, and online communities.

Contact Info

Rick Wash
402 Communication Arts and Sciences
404 Wilson Rd, #402 Michigan State Univesity
East Lansing, MI 48824

Email (preferred): wash@msu.edu
Phone: (517) 355-2381 (office)
Twitter: @rickwash
Facebook: Rick Wash

Short Bio

Rick Wash is an Associate Professor at Michigan State University in the Department of Media and Information. His work involves understanding how people think about their interactions with computers, and their interactions with other people through computers, with a particular focus on cyber-security and collaborative systems. His research is supported by multiple grants from the US National Science Foundation including an NSF CAREER award. He completed his PhD at the School of Information at the University of Michigan. Prior to studying information, Rick completed his masters degree in Computer Science from the University of Michigan, and his bachelors degree in Computer Science from Case Western Reserve University.

Longer Life Story

At one time in my past, I wanted to be a programmer. Actually, for most of my teenage years and through college, I dreamed of working somewhere cool like Microsoft (Google wasn’t around yet). I loved building stuff; I still remember writing my first computer program and being amazed that the computer was doing what I told it to. When I got to college I was programming computers on a regular basis as a Computer Science major. But I ran into one small problem: I knew how to make it do stuff, but I didn’t know what to make it do.

So I went to grad school hoping to learn how to come up with great new things for the computer to do. But the longer I was there, the more I realized that computers are really here to serve people, and you need to understand how people use computers to know what to build. Since then I’ve been spending most of my time learning more and more about how people use and interact with computers. In particular, in recent years we’ve seen an explosion of people using computers to interact with other people; social media systems like FaceBook, YouTube, Wikipedia, and Delicious are all seeing enormous growth. And all of these sites are great because they understand how to get people to work together and interact in valuable ways.

My work right now focuses on looking at how computers enable and encourage people to interact with each other in valuable ways. In particular, I focus on strategic interactions: times when how you use the computer affects how I want to use the computer, and my use of the computer affects you. These types of interactions happen all the time right now; you probably already have Facebook open in another window to check if any friends have updated their status. YouTube wouldn’t be very interesting if people didn’t upload videos, but no video creator would upload anything if there wasn’t anyone there to watch it. And Wikipedia is probably the most complex of them all, with authors, readers, editors, administrators, project coordinators, and so on.

When there are complex strategic interactions, designing the software becomes really difficult. How do you design a website where users will collaborate to write encyclopedia entries? What features will encourage that collaboration, and what features will discourage it? This is a hard question and requires both an understanding of people and an understanding of technology. This is where my work comes in. I am trying to identify incentive mechanisms: technology features or design patterns that have predictable behavorial consequences in these complex strategic environments. These design patterns will allow us to build the next generation of social computing systems.