About CSS Lab
CSS develops and applies computational methods to large-scale data in order to gain novel and replicable insights into human behavior. In exchanges with colleagues from around the world, we seek to articulate and implement a few guiding principles for our emerging field.
We launch studies that address important social problems — saving lives; improving security; enhancing economic prosperity; nurturing inclusion, diversity, equity, and access; bolstering democracy; etc. Beyond generating results that are meaningful outside of academia, this approach may also lead to more replicable, cumulative, and coherent science.
We value both prediction and explanation which are two interdependent sides of any project. At the same time, we recognize the limits to our ability to predict and explain human behavior.
We seek projects open to tens and hundreds of researchers who come together to test their competing arguments using the same large-scale data under the same conditions.
We promote transparent research protocols, data sharing, and replication studies. Any study should assess and report the limits of its predictive and explanatory powers.
We design innovative research platforms that support mass collaboration on projects with large-scale data. In collaboration with industry partners, we develop secure data centers supplemented by an administrative infrastructure for granting access, monitoring outputs, and enforcing privacy and ethics rules.