Changing How We Do Science with Brian Nosek [Idea Machines #3]

My guest this week is Brian Nosek, co-Founder and the Executive Director of the Center for Open Science. Brian is also a professor in the Department of Psychology at the University of Virginia doing research on the gap between values and practices, such as when behavior is influenced by factors other than one's intentions and goals.

The topic of this conversation is how incentives in academia lead to problems with how we do science, how we can fix those problems, the center for open science, and how to bring about systemic change in general.

Show Notes

Brian’s Website

Brian on Twitter (@BrianNosek)

Center for Open Science

The Replication Crisis

Preregistration

Article in Nature about preregistration results

The Scientific Method

If you want more, check out Brian on Econtalk

Transcript

Intro

[00:00:00] This podcast I talked to Brian nosek about innovating on the very beginning of the Innovation by one research. I met Brian at the Dartmouth 60th anniversary conference and loved his enthusiasm for changing the way we do science. Here's his official biography. Brian nozik is a co-founder and the executive director for the center for open science cos is a nonprofit dedicated to enabling open and reproducible research practices worldwide.

Brian is also a professor in the department of psychology at the University of Virginia. He's received his PhD from Yale University in 2002 in 2015. He was on Nature's 10 list and the chronicle for higher education influence. Some quick context about Brian's work and the center for open science.

There's a general consensus in academic circles that there are glaring problems in how we do research today. The way research works is generally like this researchers usually based at a university do experiments then when they have a [00:01:00] result they write it up in a paper that paper goes through the peer-review process and then a journal publishes.

The number of Journal papers you've published and their popularity make or break your career. They're the primary consideration for getting a position receiving tenure getting grants and procedure in general that system evolved in the 19th century. When many fewer people did research and grants didn't even exist we get into how things have changed in the podcast.

You may also have heard of what's known as the replication crisis. This is the Fairly alarming name for a recent phenomena in which people have tried and failed to replicate many well-known studies. For example, you may have heard that power posing will make you act Boulder where that self-control is a limited resource.

Both of the studies that originated those ideas failed to replicate. Since replicating findings a core part of the scientific method unreplicated results becoming part of Cannon is a big deal. Brian has been heavily involved in the [00:02:00] crisis and several of the center for open science is initiatives Target replication.

So with that I invite you to join my conversation with Brian idzik.

How does open science accelerate innovation and what got you excited about it?

Ben: So the theme that I'm really interested in is how do we accelerate Innovations? And so just to start off with I love to ask you sort of a really broad question of in your mind. How does having a more open science framework help us accelerate Innovations? And I guess parallel to that. Why what got you excited about it first place.

Brian: Yeah, yeah, so that this is really a core of why we started the center for open science is to figure out how can we maximize the progress of science given that we see a number of different barriers to or number of different friction points to the PACE and progress of [00:03:00] Science.

And so there are a few things. I think that how. Openness accelerates Innovation, and I guess you can think of it as sort of multiple stages at the opening stage openness in terms of planning pre-registering what your study is about why you're doing this study that the study exists in the first place has a mechanism of helping to improve Innovation by increasing The credibility of the outputs.

Particularly in making a clear distinction between the things that we planned in advance that we're testing hypotheses of ideas that we have and we're acquiring data in order to test those ideas from the exploratory results the things that we learn once we've observed the data and we get insights bu...