12 résultats
pour « privacy »
This paper examines the rise of algorithmic harms from AI, such as privacy erosion and inequality, exacerbated by accountability gaps and algorithmic opacity. It critiques existing legal frameworks in the US, EU, and Japan as insufficient, and proposes refined impact assessments, individual rights, and disclosure duties to enhance AI governance and mitigate harms.
The increasing complexity of data protection laws, rising compliance costs, and evolving cyber threats make data security a vital business concern.
The article delves into #ethical concerns with #aitools in #legal and #tax research, addressing #output #quality, #bias, #verifiability, #liability, and #privacy #risks. It explores #regulatory, #tech, and professional solutions, offering practical advice for tax professionals to safely navigate AI's challenges with #riskmitigation.
The current global #dataprivacy situation resembles the accountability crisis during the early 2000s US accounting scandals. Lack of oversight, #transparency, and #regulation has led to confusion and distrust. By emulating successful models like the Sarbanes-Oxley Act, companies can regain consumer trust by treating privacy policies like #financialstatements, standardized and audited. The proposal includes #privacy #controls similar to financial internal controls and a Privacy Cube framework for #riskmanagement, ultimately aiming to rebuild #consumertrust in #data handling.
Private sector #ai applications can lead to unfair results and loss of informational #privacy, such as increasing #insurancepremiums. Addressing this involves exploring the philosophical theory of fairness as equality of opportunity.
This article highlights the importance of #cybersecurity in contemporary business models and the need for #legal practitioners and #it professionals to work together to assess the extent to which #privacy and #security measures qualify as "appropriate" in the context of #liability #claims and actions for #damages. The article provides guidance on how to move from technical insight to legal #compliance.
"By employing Big Data and Artificial Intelligence (AI), personal data that is categorized as sensitive data according to the GDPR Art. 9 can often be extracted. Art. 9(1) GDPR initially forbids this kind of processing. Almost no industrial control system functions without AI, even when considering the broad definition of the EU AI Regulation (EU AI Regulation-E)."
"We argue that datafication of insurer processes may fuel excessive data collection in the context of insurance contracts, generating a substantial risk of harm to consumers, especially in terms of discrimination, exclusion, and unaffordability of insurance. "
"... we have performed a detailed study which includes: GDPR-compliance, provided functionality, security and privacy issues, and the cost ... of the different operations to be run on the blockchain."
"The discussion includes both de jure and de facto effects, including China’s explicit laws, recent enforcement actions in the European Union, and proposed privacy legislation in India. The focus is on effects on cybersecurity defense, rather than offensive cyber measures"