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A Distributed Learning Dynamics in Social Groups
TLDR
The answer to this question is yes -- this distributed learning is highly effective at identifying the best option and is close to optimal for the group overall, and is proved by first defining a (stochastic) infinite population version of these distributed learning dynamics and then combining its strong convergence properties along with its relation to the finite population dynamics.
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Defining AI in Policy versus Practice
TLDR
While AI researchers favor definitions of AI that emphasize technical functionality, policy-makers instead use definitions that compare systems to human thinking and behavior, pointing out that definitions adhering closely to the functionality of AI systems are more inclusive of technologies in use today.
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Toward situated interventions for algorithmic equity: lessons from the field
TLDR
The experiences using participatory and co-design methods for algorithmic accountability in a project called the Algorithmic Equity Toolkit found that community-based methods are important inroads to addressing algorithmic harms in their situated contexts.
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An Experimental Study of Cryptocurrency Market Dynamics
TLDR
An online experiment to study how susceptible traders in marketplaces for cryptocurrencies are to peer influence from trading behavior finds that individual "buy" actions led to short-term increases in subsequent buy-side activity hundreds of times the size of the interventions.
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Manifold Alignment
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A Bayesian Cognition Approach to Improve Data Visualization
TLDR
A Bayesian cognitive model for understanding how people interpret visualizations in light of prior beliefs is demonstrated and it is shown how this model provides a guide for improving visualization evaluation.
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Turkers of the World Unite: Multilevel In-Group Bias Among Crowdworkers on Amazon Mechanical Turk
Crowdsourcing has become an indispensable tool in the behavioral sciences. Often, the “crowd” is considered a black box for gathering impersonal but generalizable data. Researchers sometimes seem to…
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Bots as Virtual Confederates: Design and Ethics
TLDR
This work outlines a design space for bots as virtual confederates, and proposes a set of guidelines for meeting the status quo for ethical experimentation.
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Bayesian collective learning emerges from heuristic social learning
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"This Place Does What It Was Built For"
TLDR
To what extent consideration of constitutional layers is met or could be better met in three varied cases of digital institutions: cryptocurrencies, cannabis informatics, and amateur Minecraft server governance is explored.
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