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Many internet applications are powered by machine learned models, which are usually trained on labeled datasets obtained through either implicit / explicit user feedback signals or human judgments. Since societal biases may be present in…
In the big data era, more and more cloud-based data-driven applications are developed that leverage individual data to provide certain valuable services (the utilities). On the other hand, since the same set of individual data could be…
Various data-sharing platforms have emerged with the growing public demand for open data and legislation mandating certain data to remain open. Most of these platforms remain opaque, leading to many questions about data accuracy, provenance…
City governments in the United States are increasingly pressured to adopt emerging technologies. Yet, these systems often risk biased and disparate outcomes. Scholars studying public sector technology design have converged on the need to…
Open data are characterized by a number of economic, technological, innovative and social benefits. They are seen as a significant contributor to the city's transformation into Smart City. This is all the more so when the society is on the…
Data-based decisionmaking must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations. We study a framework in which, due to such manipulation, data becomes less…
The data revolution continues to transform every sector of science, industry and government. Due to the incredible impact of data-driven technology on society, we are becoming increasingly aware of the imperative to use data and algorithms…
As societal challenges grow more complex, access to data for public interest use is paradoxically becoming more constrained. This emerging data winter is not simply a matter of scarcity, but of shrinking legitimate and trusted pathways for…
Machine learning (ML) has become a critical tool in public health, offering the potential to improve population health, diagnosis, treatment selection, and health system efficiency. However, biases in data and model design can result in…
Due to the widespread use of data-powered systems in our everyday lives, concepts like bias and fairness gained significant attention among researchers and practitioners, in both industry and academia. Such issues typically emerge from the…
The digital revolution has led to the digitization of human behavior, creating unprecedented opportunities to understand observable actions on an unmatched scale. Emerging phenomena such as crowdfunding and crowdsourcing have further…
In the current technology environment, users are often in a vulnerable position when it comes to protecting their privacy. Previous efforts to promote privacy protection have largely focused on top-down approaches such as regulation and…
Researchers find weaknesses in current strategies for protecting privacy in large datasets. Many anonymized datasets are reidentifiable, and norms for offering data subjects notice and consent over emphasize individual responsibility. Based…
We live in an age of unprecedented opportunities to use existing data for tasks not anticipated when those data were collected, resulting in widespread data repurposing. This commentary defines and maps the scope of data repurposing to…
Data harvesting and profiling have become a de facto business model for many businesses in the digital economy. The surveillance of individual persons through their use of private sector platforms has a well-understood effect on personal…
The concept of power can be explored at several scales: from physical action and process effectuation, all the way to complex social dynamics. A spectrum-wide analysis of power requires attention to the fundamental principles that constrain…
The recent emergence and adoption of Machine Learning technology, and specifically of Large Language Models, has drawn attention to the need for systematic and transparent management of language data. This work proposes an approach to…
Progress in many domains increasingly benefits from our ability to view the systems through a computational lens, i.e., using computational abstractions of the domains; and our ability to acquire, share, integrate, and analyze disparate…
Converting customer survey feedback data into usable insights has always been a great challenge for large software enterprises. Despite the improvements on this field, a major obstacle often remains when drawing the right conclusions out of…
Recent studies have shown that information disclosed on social network sites (such as Facebook) can be used to predict personal characteristics with surprisingly high accuracy. In this paper we examine a method to give online users…