We proceed to show the sparsistency510 of the estimated parameters. First, suppose that Θ t;ij 6= 0 for some time tand index (i,j). Due to 0 < γ < 1, the above inequality implies that bΘt;ij = 0521 for every t and (i,j) 6 St, and bΘt;ij bΘt 1;ij = 0 for every t > 0 and (i,j) 6 Dt. The proof is inspired527 by Corollary 1 in [47]. First, we present the following key lemmas.528

Although the fairness community has recognized the importance of data, re-searchers in the area primarily rely on UCIAdult when it comes to tabular data. Derived from a 1994 USCensus survey, this dataset has appeared in hundreds of research papers where it served as the basis for the development and comparison of many algorithmic fairness interventions. We reconstruct a superset of the UCI Adult data from available USCensus sources and reveal idiosyncrasies of the UCIAdult dataset that limit its external validity. Our primary contribution is asuite of new datasets derived from USCensus surveys that extend the existing data ecosystem for research on fair machine learning. We create prediction tasks relating to income, employment, health, transportation, and housing. The data span multiple years and all states of the United States, allowing researchers to studytemporal shift and geographic variation. We highlight a broad initial sweep of new empirical insights relating to trade-offs between fairness criteria, performance of algorithmic interventions, and the role of distribution shift based on our new datasets. Our findings inform ongoing debates, challenge some existing narratives, and point to future research directions.

Fans want to reclaim the music and myth of Michael Jackson in the new biopic while critics call for accountability. Still from, which opened April 24. Is truth determined by the size of the audience it reaches? If so, --a new film about the pop singer Michael Jackson that is on track to have the biggest-ever opening for a music biopic, with projected earnings of $70 million at the US box office, despite critics saying it sanitizes the reality of who Jackson actually was--intends to supplant the King of Pop as the apotheosis of artistic virtue. The film's release has sparked a familiar but newly intensified civil war online, between those eager to reclaim the music and myth of Jackson, and those who see any celebration of him as a failure of accountability.

With A.I., Anyone Can Be an Influencer TikTok and Instagram made it easy to monetize the physical self. Now the social-media-savvy can use A.I. to play with their identity, or overhaul it entirely. A few months ago, a forty-five-year-old homemaker living in Georgia, whom I'll call Robin, started playing around with an A.I. image generator. Growing up, Robin had loved reading; she dabbled in writing, too, but after her first child was born, the habit faded. A.I. offered something different--a kind of world-building that allowed her to project herself into places and situations she'd never inhabited.

Two-sided marketplaces are standard business models of many online platforms (e.g., Amazon, Facebook, LinkedIn), wherein the platforms have consumers, buyers or content viewers on one side and producers, sellers or content-creators on the other. Consumer side measurement of the impact of a treatment variant can be done via simple online A/B testing. Producer side measurement is more challenging because the producer experience depends on the treatment assignment of the consumers. Existing approaches for producer side measurement are either based on graph cluster-based randomization or on certain treatment propagation assumptions. The former approach results in low-powered experiments as the producer-consumer network density increases and the latter approach lacks a strict notion of error control. In this paper, we propose (i) a quantification of the quality of a producer side experiment design, and (ii) a new experiment design mechanism that generates high-quality experiments based on this quantification.