Changing Simplistic Worldviews
We study a Bayesian persuasion model with two-dimensional states of the world, in which the sender (she) and receiver (he) have heterogeneous prior beliefs and care about different dimensions. The receiver is a naive agent who has a simplistic worldview: he ignores the dependency between the two dimensions of the state. We provide a characterization for the sender's gain from persuasion both when the receiver is naive and when he is rational. We show that the receiver benefits from having a simplistic worldview if and only if it makes him perceive the states in which his interest is aligned with the sender as less likely.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Avoiding Disparity Amplification under Different Worldviews
We mathematically compare four competing definitions of group-level nondiscrimination: demographic parity, equalized odds, predictive parity, and calibration. Using the theoretical framework of Friedler et al., we study …
FairnessAligning Multidimensional Worldviews and Discovering Ideological Differences
The Internet is home to thousands of communities, each with their own unique worldview and associated ideological differences. With new communities constantly emerging and serving as ideological birthplaces, battleground…
A Knowledge-Graph Translation Layer for Mission-Aware Multi-Agent Path Planning in Spatiotemporal Dynamics
The coordination of autonomous agents in dynamic environments is hampered by the semantic gap between high-level mission objectives and low-level planner inputs. To address this, we introduce a framework centered on a Kn…
Coexistence of several currencies in presence of increasing returns to adoption
We present a simplistic model of the competition between different currencies. Each individual is free to choose the currency that minimizes his transaction costs, which arise whenever his exchanging relations have chose…
Diversity and Language Technology: How Techno-Linguistic Bias Can Cause Epistemic Injustice
It is well known that AI-based language technology -- large language models, machine translation systems, multilingual dictionaries, and corpora -- is currently limited to 2 to 3 percent of the world's most widely spoken…
DiversityMachine Translation