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For generations, people have complained that things used to be better in the past. In this paper, we investigate this change by specifically looking at creativity in astronomy. To do this,we explore if older constellations reflected a…

Fairness assumptions are a valuable tool when reasoning about systems. In this paper, we classify several fairness properties found in the literature and argue that most of them are too restrictive for many applications. As an alternative…

Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the issue of fairness remains a concern in high-stakes fields such as healthcare. Despite extensive discussion and efforts in algorithm…

Artificial Intelligence (AI) has demonstrated remarkable capabilities in domains such as recruitment, finance, healthcare, and the judiciary. However, biases in AI systems raise ethical and societal concerns, emphasizing the need for…

We review the relatively new, internet-enabled, and rapidly-evolving field of citizen science, focusing on research projects in stellar, extragalactic and solar system astronomy that have benefited from the participation of members of the…

While both society and astronomy have evolved greatly over the past fifty years, the academic institutions and incentives that shape our field have remained largely stagnant. As a result, the astronomical community is faced with several…

In the distant past, telescopes were known, first and foremost, for the sizes of their apertures. Advances in technology are now enabling astronomers to build extremely powerful instruments to the extent that instruments have now achieved…

The theory of algorithmic fair allocation is within the center of multi-agent systems and economics in the last decade due to its industrial and social importance. At a high level, the problem is to assign a set of items that are either…

The allocation of resources among multiple agents is a fundamental problem in both economics and computer science. In these settings, fairness plays a crucial role in ensuring social acceptability and practical implementation of resource…

How can we build recommender systems to take into account fairness? Real-world recommender systems are often composed of multiple models, built by multiple teams. However, most research on fairness focuses on improving fairness in a single…

We study fairness in classification, where individuals are classified, e.g., admitted to a university, and the goal is to prevent discrimination against individuals based on their membership in some group, while maintaining utility for the…

Public and private institutions must often allocate scare resources under uncertainty. Banks, for example, extend credit to loan applicants based in part on their estimated likelihood of repaying a loan. But when the quality of information…

In the scientific community, prizes play a pivotal role in shaping research trajectories by conferring credibility and offering financial incentives to researchers. Yet, we know little about the relationship between academic collaborations…

Spectrum being a very scarce natural resource of a country has to be judicially used for the purpose of nation building and the allocation process to telecom operators should be very transparent and ethical. There are various ways of how…

Statistical algorithms are usually helping in making decisions in many aspects of our lives. But, how do we know if these algorithms are biased and commit unfair discrimination of a particular group of people, typically a minority?…

The applications of personalized recommender systems are rapidly expanding: encompassing social media, online shopping, search engine results, and more. These systems offer a more efficient way to navigate the vast array of items available.…

The use of algorithmic decision making systems in domains which impact the financial, social, and political well-being of people has created a demand for these decision making systems to be "fair" under some accepted notion of equity. This…

Scientific conferences play an important part in every scientists career. Here, I suggest an approach that can mitigate biases and help make scientific conferences more inclusive for everybody by increasing the transparency in speaker…

Equal opportunity is central to the concept of meritocracy. Opportunity and leadership should go to the people most qualified by performance, and not on the basis of arbitrary or irrelevant attributes. This principle is arguably most…

An algorithm that outputs predictions about the state of the world will almost always be designed with the implicit or explicit goal of outputting accurate predictions (i.e., predictions that are likely to be true). In addition, the rise of…