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Philosophy and Cognitive Science for Improved Reasoning (EXPIRED)

Postdoc(s) will be based in the Department of Philosophy at Carnegie Mellon University, funded by IC Postdoc Fellowship(s)

Job category Postdoc or similar / Fixed term
AOS Open
AOC Each of the following is desirable but not necessary. (1) Reasoning (normative and empirical approaches), especially improving reasoning. (2) Cognitive science. (3) Formal epistemology. (4) Decision theory. (5) Programming for behavioral experiments. (6) Basic stats.
AOC categories Metaphysics and Epistemology
Philosophy of Science
Workload Full time
Vacancies 2
Organization's reference number ICPD-2020-13/ICPD-2020-14
Location Pittsburgh, Pennsylvania, United States
Start date 1 September 2020.
Job description

The Intelligence Community Postdoctoral Research Fellowship Program (https://orise.orau.gov/icpostdoc/) has announced two opportunities aiming to promote research on improving human reasoning:

  1. Reducing Belief-Driven Thinking (ICPD-2020-13)
  2. Accurate Answers to Challenging Factual Questions (ICPD-2020-14)

Prof. Simon Cullen (Carnegie Mellon University) is intrerested in supervising this research at CMU. The postdoc(s) will be provided with offices in the Department of Philosophy.

Award Details

*Appointments are for 24 months. The Program has the discretion to fund a third year.

* Annual stipend (which include funds for health insurance) is between $75,000 - $79,000

* Annual travel budget of $6,000

Postdoc Eligibility

* U.S. citizenship required

* PhD. received within 5 years of the application deadline

The postdoc cannot directly conduct human subjects experimentation under the postdoc. But the postdoc will collaborate with others who do related human subjects experimentation.

Details about each position follow. For further information about applying to these CMU-based positions, contact Prof. Simon Cullen as soon as possible. His website is https://www.simoncullen.org/

Postdoc 1: Reducing Belief-Driven Thinking


A person with strongly held beliefs may overestimate the degree to which his evidence supports his beliefs. He may avoid seeking or considering contrary evidence, and he may misinterpret the evidence that is considered. This tendency, called “belief-driven thinking,” affects even intelligent, well-informed people.

Psychologists (and other theorists) have investigated several types of belief-driven thinking, including selectively searching for supporting evidence (confirmation bias), selective recall (myside bias), and evaluating an argument based on how plausible its conclusion seems rather than on the strength of its premises and inferences themselves. Psychologists have also studied the double standards that scientists often use when evaluating experimental results (evaluation bias) and the tendency of even highly numerate people to misinterpret simple statistical data so that it aligns with their beliefs (motivated innumeracy). Cognitive scientists have theorized about the origins of belief-driven thinking, but there has been little research on effective interventions.

Currently, there is no easy, attractive procedure for organizations to adopt to counter belief-driven thinking. The postdoc will conduct research at CMU to develop and test effective, easy-to-use techniques for reducing belief-driven thinking. Such techniques will enable people to reason more rigorously about a wide range of issues.

Postdoc 2: Accurate Answers to Challenging Factual Question

Recent research has found two rapid, reliable ways to increase the accuracy of answers to challenging factual questions, particularly when experts disagree:

  1. Aggregation of answers from individuals working independently. One study (Kosinski, 2012) began with answers to an IQ test taken by individuals with an average IQ of 120. Mechanically selecting the most common answer to each question produced a “group IQ” of about 150.
  2. Brief discussion between two people who disagree on the answer. In one study by Chen (2019) used this method to increase the rate of correct answers from 67% to 98.8%.

Research is needed to develop an effective technique for combining aggregation techniques with small-group discussion. Effective techniques apply to a wide range of complex, factual question types, including predictions. They should be easy and natural for people to use on the job. They should not require formal training or technical knowledge to use.

How to apply
Application type Email
Email your CV to Simon Cullen along with a paragraph or two explaining your suitability for either or both positions. If you have done relevant work, please include it as an attachment. Use the subject line "IC Postdoc". While these positions are funded by the Intelligence Community Postdoctoral Research Fellowship Program, security clearance is not necessary. However, all applicants must be US citizens.
Email to apply
Deadline for full consideration: February 17, 2020, 11:59pm EST

(applications under review)

Hard deadline February 24, 2020, 11:59pm EST
Web address for more information https://orise.orau.gov/icpostdoc/
Contact name Simon Cullen
Contact email
Time created February 11, 2020, 9:06am EST
Scheduled expiry date February 24, 2020, 11:59pm EST
Expired on February 26, 2020, 12:46am EST
Last updated April 27, 2020, 3:00pm EST
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The postdoc(s) will be funded by the Intelligence Community Postdoctoral Research Fellowship Program: https://orise.orau.gov/icpostdoc/