A Mechanism Design Approach to Measure Awareness

Diodato Ferraioli, Carmine Ventre, Gabor Aranyi

Research output: Contribution to conferencePaperpeer-review

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Abstract

In this paper, we study protocols that allow to discern conscious
and unconscious decisions of human beings; i.e., protocols
that measure awareness. Consciousness is a central
research theme in Neuroscience and AI, which remains, to
date, an obscure phenomenon of human brains. Our starting
point is a recent experiment, called Post Decision Wagering
(PDW) (Persaud, McLeod, and Cowey 2007), that attempts
to align experimenters’ and subjects’ objectives by leveraging
financial incentives.We note a similarity with mechanism
design, a research area which aims at the design of protocols
that reconcile often divergent objectives through incentivecompatibility.
We look at the issue of measuring awareness
from this perspective. We abstract the setting underlying the
PDW experiment and identify three factors that could make
it ineffective: rationality, risk attitude and bias of subjects.
Using mechanism design tools, we study the barrier between
possibility and impossibility of incentive compatibility with
respect to the aforementioned characteristics of subjects. We
complete this study by showing how to use our mechanisms
to potentially get a better understanding of consciousness.
Original languageEnglish
Publication statusPublished - 25 Jan 2015
Event29th AAAI Conference on Artificial Intelligence - Hyatt Regency, Austin, United States
Duration: 25 Jan 201529 Jan 2015
http://www.aaai.org/Conferences/AAAI/aaai15.php

Conference

Conference29th AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI 15
Country/TerritoryUnited States
CityAustin
Period25/01/1529/01/15
Internet address

Bibliographical note

Authors can post items submitted on their own personal website or their institution or company's website prior to publication. Copyright AAAI 2016 http://www.aaai.org/Organization/organization.php For full details see http://www.aaai.org/ojs/index.php/aimagazine/about/editorialPolicies#authorSelfArchivePolicy [Accessed: 10/05/2016]

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