[HTML][HTML] High school students exploring machine learning and its societal implications: Opportunities and challenges
MH Kaspersen, KEK Bilstrup, M Van Mechelen… - International Journal of …, 2022 - Elsevier
The increased use of AI and machine learning (ML) calls for a general AI literacy, in
particular regarding understanding how ML works, the process behind creating ML models …
particular regarding understanding how ML works, the process behind creating ML models …
Decentralized vs. distributed organization: Blockchain, machine learning and the future of the digital platform
JP Vergne - Organization Theory, 2020 - journals.sagepub.com
The terms decentralized organization and distributed organization are often used
interchangeably, despite describing two distinct phenomena. I propose distinguishing …
interchangeably, despite describing two distinct phenomena. I propose distinguishing …
(Mis) information dissemination in WhatsApp: Gathering, analyzing and countermeasures
WhatsApp has revolutionized the way people communicate and interact. It is not only
cheaper than the traditional Short Message Service (SMS) communication but it also brings …
cheaper than the traditional Short Message Service (SMS) communication but it also brings …
Social media and moral panics: Assessing the effects of technological change on societal reaction
JP Walsh - International Journal of Cultural Studies, 2020 - journals.sagepub.com
Answering calls for deeper consideration of the relationship between moral panics and
emergent media systems, this exploratory article assesses the effects of social media–web …
emergent media systems, this exploratory article assesses the effects of social media–web …
[HTML][HTML] Public attitudes towards algorithmic personalization and use of personal data online: Evidence from Germany, Great Britain, and the United States
People rely on data-driven AI technologies nearly every time they go online, whether they
are shopping, scrolling through news feeds, or looking for entertainment. Yet despite their …
are shopping, scrolling through news feeds, or looking for entertainment. Yet despite their …
Fairness through robustness: Investigating robustness disparity in deep learning
Deep neural networks (DNNs) are increasingly used in real-world applications (eg facial
recognition). This has resulted in concerns about the fairness of decisions made by these …
recognition). This has resulted in concerns about the fairness of decisions made by these …
Cyber-enabled influence operations as a 'center of gravity'in cyberconflict: The example of Russian foreign interference in the 2016 US federal election
Russia's cyber-enabled influence operations (CEIO) have garnered significant public,
academic and policy interest. 126 million Americans were reportedly exposed to Russia's …
academic and policy interest. 126 million Americans were reportedly exposed to Russia's …
How biased is the population of Facebook users? Comparing the demographics of Facebook users with census data to generate correction factors
Censuses and representative sampling surveys around the world are key sources of data to
guide government investments and public policies. However, these sources are very …
guide government investments and public policies. However, these sources are very …
What makes a “bad” ad? user perceptions of problematic online advertising
Online display advertising on websites is widely disliked by users, with many turning to ad
blockers to avoid “bad” ads. Recent evidence suggests that today's ads contain potentially …
blockers to avoid “bad” ads. Recent evidence suggests that today's ads contain potentially …
Ad delivery algorithms: The hidden arbiters of political messaging
Political campaigns are increasingly turning to targeted advertising platforms to inform and
mobilize potential voters. The appeal of these platforms stems from their promise to …
mobilize potential voters. The appeal of these platforms stems from their promise to …