All posts tagged: machine learning

Choice Engineering Competition

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An interesting competition on choice engineering is being held here. The goal is to compare qualitative (choice architecture) and quantitative (new field of choice engineering) models of choice and determine which one works best in influencing human decisions. The competition was recently described in Nature Communications [1]. Choice architecture uses qualitative psychological principles in choice design. The recent development of quantitative models of choice can revolutionize this discipline. To launch this field, which we term […]

Assorted links for 07/29/2019

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Blockchain 1. BetterHash: Decentralizing Bitcoin Mining With New Hashing Protocols 2. A Bayesian approach to identify Bitcoin users Abstract When a user initiates a Bitcoin transaction, his Bitcoin client program relays messages to other clients through the Bitcoin network. Monitoring the propagation of these messages and analyzing them carefully reveal hidden relations. In this paper, we develop a mathematical model using a probabilistic approach to link Bitcoin addresses and transactions to the originator IP address. […]

Papers (1)

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There are fascinating and scary consequences of the application of AI in human decision making. Some of the pitfalls should be carefully addressed. My recent working paper on the application of machine learning in behavioral economics to prescribe personalized interventions (nudging) is now on arXiv. I’d be grateful for any comments or suggestions you might have.