A systematic investigation of the integration of machine learning into supply chain risk management

M Schroeder, S Lodemann - Logistics, 2021 - mdpi.com
The main objective of the paper is to analyze and synthesize existing scientific literature
related to supply chain areas where machine learning (ML) has already been implemented …

[HTML][HTML] Machine learning for sperm selection

JB You, C McCallum, Y Wang, J Riordon… - Nature Reviews …, 2021 - nature.com
Infertility rates and the number of couples seeking fertility care have increased worldwide
over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are …

Transparency you can trust: Transparency requirements for artificial intelligence between legal norms and contextual concerns

H Felzmann, EF Villaronga, C Lutz… - Big Data & …, 2019 - journals.sagepub.com
Transparency is now a fundamental principle for data processing under the General Data
Protection Regulation. We explore what this requirement entails for artificial intelligence and …

Towards intelligent regulation of artificial intelligence

MC Buiten - European Journal of Risk Regulation, 2019 - cambridge.org
Artificial intelligence (AI) is becoming a part of our daily lives at a fast pace, offering myriad
benefits for society. At the same time, there is concern about the unpredictability and …

Fit for purpose? The GDPR and the governance of European digital health

L Marelli, E Lievevrouw, I Van Hoyweghen - Policy studies, 2020 - Taylor & Francis
The introduction of the General Data Protection Regulation (GDPR) in 2018 served as the
cornerstone of the new data governance regime of the European Union. Informed by …

The right not to be subject to automated decisions based on profiling

I Mendoza, LA Bygrave - EU internet law: Regulation and enforcement, 2017 - Springer
In this chapter, a critical analysis is undertaken of the provisions of Art. 22 of the European
Union's General Data Protection Regulation of 2016, with lines of comparison drawn to the …

[HTML][HTML] Artificial intelligence for anti-money laundering: a review and extension

J Han, Y Huang, S Liu, K Towey - Digital Finance, 2020 - Springer
This paper surveys the existing academic literature on artificial intelligence (AI) technologies
for anti-money laundering (AML). We review the state-of-the-art AI methods for AML and …

Big data governance of personal health information and challenges to contextual integrity

JS Winter, E Davidson - The Information Society, 2019 - Taylor & Francis
Pervasive digitization and aggregation of personal health information (PHI), along with
artificial intelligence (AI) and other advanced analytical techniques, hold promise of …

Ethically responsible machine learning in fintech

M Rizinski, H Peshov, K Mishev, LT Chitkushev… - IEEE …, 2022 - ieeexplore.ieee.org
Rapid technological developments in the last decade have contributed to using machine
learning (ML) in various economic sectors. Financial institutions have embraced technology …

Governance of artificial intelligence and personal health information

JS Winter, E Davidson - Digital policy, regulation and governance, 2019 - emerald.com
Purpose This paper aims to assess the increasing challenges to governing the personal
health information (PHI) essential for advancing artificial intelligence (AI) machine learning …