Publications by Naman Goel | EPFL Graph Search

Related publications (9)

Truthful, Transparent and Fair Data Collection Mechanisms

An important prerequisite for developing trustworthy artificial intelligence is high quality data. Crowdsourcing has emerged as a popular method of data collection in the past few years. However, there is always a concern about the quality of the data thus ...

EPFL2020

Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data

Boi Faltings, Naman Goel

Several peer consistency mechanisms have been proposed to incentivize agents for honestly solving crowdsourcing tasks. These game-theoretic mechanisms evaluate the answers provided by an agent based on the correlation with answers provided by other agents ...

JMLR (AUAI)2020

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Naman Goel

Training datasets for machine learning often have some form of missingness. For example, to learn a model for deciding whom to give a loan, the available training data includes individuals who were given a loan in the past, but not those who were not. This ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Boi Faltings, Naman Goel

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

2023

Non-Discriminatory Machine Learning through Convex Fairness Criteria

Boi Faltings, Naman Goel

Biased decision making by machine learning systems is increasingly recognized as an important issue. Recently, techniques have been proposed to learn non-discriminatory classifiers by enforcing constraints in the training phase. Such constraints are either ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2018

Tackling Peer-to-Peer Discrimination in the Sharing Economy

Boi Faltings, Naman Goel

Sharing economy platforms such as Airbnb and Uber face a major challenge in the form of peer-to-peer discrimination based on sensitive personal attributes such as race and gender. As shown by a recent study under controlled settings, reputation systems can ...

ACM2020

Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain

Boi Faltings, Naman Goel, Aris Filos Ratsikas

Blockchain based systems allow various kinds of financial transactions to be executed in a decentralized manner. However, these systems often rely on a trusted third party (oracle) to get correct information about the real-world events, which trigger the f ...

2022

Crowdsourcing with Fairness, Diversity and Budget Constraints

Boi Faltings, Naman Goel

Recent studies have shown that the labels collected from crowdworkers can be discriminatory with respect to sensitive attributes such as gender and race. This raises questions about the suitability of using crowdsourced data for further use, such as for tr ...

ASSOC COMPUTING MACHINERY2019

Peer-Prediction in the Presence of Outcome Dependent Lying Incentives

Boi Faltings, Naman Goel, Aris Filos Ratsikas

We derive conditions under which a peer-consistency mechanism can be used to elicit truthful data from non-trusted rational agents when an aggregate statistic of the collected data affects the amount of their incentives to lie. Furthermore, we discuss the ...

2022