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We discuss results from a few recent papers on how market design affects play between artificial intelligence (AI) algorithms. We describe the results from Banchio and Skrzypacz [2022] where the first-price auction appears more prone to collusion than ...

Problem definition: The loyalty penalty refers to a pricing strategy where companies charge higher prices to loyal customers for exploitation while offering lower prices to nonloyal customers for attraction. To address this unfair business practice, ...

Dream11 takes pride in being a unique platform that enables over 190 million fantasy sports users to demonstrate their skills and connect deeper with their favorite sports. While managing such a scale, one issue we are faced with is duplicate/multiple ...

Due to the rising availability and adoption of Artificial Intelligence in e-commerce, many of the online-prices are not set by humans, but by algorithms. The consequence is an opaque pricing situation that raises the potential of concealed, unfair ...

Federated learning enables a population of distributed clients to jointly train a shared machine learning model with the assistance of a central server. The finance community has shown interest in its potential to allow inter-firm and cross-silo ...

Bitcoin falls dramatically short of the scale provided by banks for payments. Currently, its ledger grows by the addition of blocks of ∼2,000 transactions every 10 minutes. Intuitively, one would expect that increasing the block capacity would solve this ...

Communication is one of the most effective devices in promoting team cooperation. However, asymmetric communication sometimes breeds collusion and hurts team efficiency. Here, we present experimental evidence showing that excluding one member from team ...

To help address programming plagiarism and collusion, students should be informed about acceptable practices and about program similarity, both coincidental and non-coincidental. However, current approaches are usually manual, brief, and delivered well ...

YouTube sells advertisements on the posted videos, which in turn enables the content creators to monetize their videos. As an unintended consequence, this has proliferated various illegal activities such as artificial boosting of views, likes, comments, ...

We study optimal team design. In our model, a principal assigns either heterogeneous agents to a team (a diverse team) or homogenous agents to a team (a specialized team) to perform repeated team production. We assume that specialized teams exhibit a ...

The popularity of Twitter has fostered the emergence of various fraudulent user activities - one such activity is to artificially bolster the social reputation of Twitter profiles by gaining a large number of followers within a short time span. Many ...

It is important to educate students about acceptable practices with regard to programming plagiarism and collusion. However, the current approach is quite demanding since it is manual, relying heavily on instructors. The information is delivered ...

When comparing student programs to check for evidence of plagiarism or collusion, the goal is to identify code segments that are common to two or more programs. Yet some code segments are common for reasons other than plagiarism or collusion, and so ...

Crowdsourcing has been a prompt and cost-effective way of obtaining labels in many machine learning applications. In the literature, a number of algorithms have been developed to infer the ground truth based on the collected labels. However, most existing ...

We show that the long-run prices from independent machine learning algorithms depend on the informational value of price experiments. If low, the long-run prices are consistent with the static Nash equilibrium; however, if high, the long-run prices are ...

Motivated by their increasing prevalence, we study outcomes when competing sellers use machine learning algorithms to run real-time dynamic price experiments. These algorithms are often misspecified, ignoring the effect of factors outside their control, ...

Collusion is widely condemned for its negative effects on consumer welfare and market efficiency. In this paper, I show that collusion may also in some cases facilitate the creation of unexpected new sources of value. I bring this possibility into focus ...

It is well documented that some students either work together on programming assessments when required to work individually (collusion) or make unauthorised use of existing code from external sources (plagiarism). One approach used in the detection of ...

To act with academic integrity in programming, students need to understand the concept of code similarity and the aspects that contribute to it, because undue similarity is often used as a first step in detecting plagiarism or collusion. However, if ...

The transition of the advertising market from traditional media to the internet has induced a proliferation of marketing agencies specialized in bidding in the auctions that are used to sell ad space on the web. We analyze how collusive bidding can emerge ...

When student programs are compared for similarity as a step in the detection of academic misconduct, certain segments of code are always sure to be similar but are no cause for suspicion. Some of these segments are boilerplate code (e.g. public static ...