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The rapid rise of IoT and Big Data has facilitated copious data driven applications to enhance our quality of life. However, the omnipresent and all-encompassing nature of the data collection can generate privacy concerns. Hence, there is a…
Big data analysis poses the dual problem of privacy preservation and utility, i.e., how accurate data analyses remain after transforming original data in order to protect the privacy of the individuals that the data is about - and whether…
Novel technologies in genomics allow creating data in exascale dimension with relatively minor effort of human and laboratory and thus monetary resources compared to capabilities only a decade ago. While the availability of this data…
The Big Data is the most popular paradigm nowadays and it has almost no untouched area. For instance, science, engineering, economics, business, social science, and government. The Big Data are used to boost up the organization performance…
The extensive collection and processing of personal information in big data analytics has given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling, and disclosure of private data. To reap the benefits…
This article appears as chapter 21 of Prince (2023, Understanding Deep Learning); a complete draft of the textbook is available here: http://udlbook.com. This chapter considers potential harms arising from the design and use of AI systems.…
Machine learning heavily relies on data, but real-world applications often encounter various data-related issues. These include data of poor quality, insufficient data points leading to under-fitting of machine learning models, and…
As the capabilities of generative language models continue to advance, the implications of biases ingrained within these models have garnered increasing attention from researchers, practitioners, and the broader public. This article…
Genetic data collection has become ubiquitous, producing genetic information about health, ancestry, and social traits. However, unregulated use, especially amid evolving scientific understanding, poses serious privacy and discrimination…
This paper proposes a dynamic process of portfolio risk measurement to address potential information loss. The proposed model takes advantage of financial big data to incorporate out-of-target-portfolio information that may be missed when…
The integration of artificial intelligence, especially large language models in robotics, has led to rapid advancements in the field. We are now observing an unprecedented surge in the use of robots in our daily lives. The development and…
As artificial intelligence becomes more prevalent in our lives, people are enjoying the convenience it brings, but they are also facing hidden threats, such as data poisoning and adversarial attacks. These threats can have disastrous…
As the world becomes increasingly dependent on technology, researchers in both industry and academia endeavor to understand how technology is used, the impact it has on everyday life, the artifact life-cycle and overall integrations of…
Data-centric technologies provide exciting opportunities, but recent research has shown how lack of representation in datasets, often as a result of systemic inequities and socioeconomic disparities, can produce inequitable outcomes that…
Synthetic data are becoming a critical tool for building artificially intelligent systems. Simulators provide a way of generating data systematically and at scale. These data can then be used either exclusively, or in conjunction with real…
Journalists, public policy analysts, and economists have called attention to the growing importance that high-performance and scientific computing have to national security and industrial leadership. As computing continues to power…
When pieces from an individual's personal information available online are connected over time and across multiple platforms, this more complete digital trace can give unintended insights into their life and opinions. In a data narrative…
Online political microtargeting involves monitoring people's online behaviour, and using the collected data, sometimes enriched with other data, to show people-targeted political advertisements. Online political microtargeting is widely…
A data intermediary acquires signals from individual consumers regarding their preferences. The intermediary resells the information in a product market wherein firms and consumers tailor their choices to the demand data. The social…
Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of…