Seminars of Interest at Columbia

Tuesday February 21st 

12:30pm to 2:00pm - Uris 330
Management Seminar - Joel Brockner (Columbia Business School) 
Title Not Available 

Wednesday February 22nd 

2:15pm to 3:45pm - 1101 IAB 
International Economics Workshop - Pablo Fajgelbaum (UCLA)
Title Not Available 

4:15pm to 5:45pm - 1101 IAB 
Applied Microeconomics: Environment, Health, Labor and Public Finance Seminar - Till van Watcher (UCLA) 
Title Not Available 

Thursday February 23rd

12:30pm to 1:30pm - Uris 331
Finance Free Lunch (Faculty Only) - Tano Santos
Title Not Available

2:15pm to 3:45pm - Uris 140 
Finance Seminar - Pietro Veronesi (University of Chicago)
Habits and Leverage (with Tano Santos) 

4:00pm to 5:00pm - Faculty House
Language & Cognition Seminar - Gerry Altmann (University of Connecticut)
The Challenges of Event Cognition: Object Representation at the Interface of Episodic and Semantic Theory

Seminars of Interest at NYU

Thursday February 23rd

12:30pm to 1:30pm - Psychology Room 551
Cognition & Perception Colloquia - Jason Fischer (Johns Hopkins)
Title Not Available

Friday February 24th

11:00am to 12:15pm - KMC 7-191
Industrial Organization Seminar (joint with Columbia IO and Strategy Seminar) - Frank Verboven (University of Leuven)
Subsidies and myopia in technology adoption: evidence from solar photovoltaic systems

Article of the Week
Why Humans Distrust Algorithms – and How That Can Change
In new research studying "algorithm aversion" - which is the tendency for people to not want to follow specific evidence-based rules when they make decisions - professors Cade Massey and Joseph Simmons of Wharton and Berkeley J. Dietvorst of the University of Chicago found that introducing an element of control increases reliance on algorithm outcomes. The researchers show that algorithms are commonly used in hiring, performance evaluation and fields like hedge fund management, but managers, i.e. the final decision makers, remain reluctant to use them exclusively. Incorporating a small degree of manager discretion over the model - as small as 5% -  they posit, is likely to help.