108 citations · 320 across the 24 of their papers we have counts for
6 papers · 1 filter
Antitrust, Amazon, and Algorithmic Auditing
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +4
In digital markets, antitrust law and special regulations aim to ensure that markets remain competitive despite the dominating role that digital platforms play today in everyone's…
Taking Advice from (Dis)Similar Machines: The Impact of Human-Machine Similarity on Machine-Assisted Decision-Making
Nina Grgić-Hlača, Claude Castelluccia, Krishna P. Gummadi
Machine learning algorithms are increasingly used to assist human decision-making. When the goal of machine assistance is to improve the accuracy of human decisions, it might seem…
When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2
Algorithmic recommendations mediate interactions between millions of customers and products (in turn, their producers and sellers) on large e-commerce marketplaces like Amazon. In…
On Fair Selection in the Presence of Implicit Variance
Vitalii Emelianov, Nicolas Gast, Krishna P. Gummadi +1
Quota-based fairness mechanisms like the so-called Rooney rule or four-fifths rule are used in selection problems such as hiring or college admission to reduce inequalities based o…
An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision
Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti +2
The notion of individual fairness requires that similar people receive similar treatment. However, this is hard to achieve in practice since it is difficult to specify the appropri…
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning
Hoda Heidari, Vedant Nanda, Krishna P. Gummadi
Most existing notions of algorithmic fairness are one-shot: they ensure some form of allocative equality at the time of decision making, but do not account for the adverse impact o…