AI governance: themes, knowledge gaps and future agendas

T Birkstedt, M Minkkinen, A Tandon, M Mäntymäki - Internet Research, 2023 - emerald.com
Purpose Following the surge of documents laying out organizations' ethical principles for
their use of artificial intelligence (AI), there is a growing demand for translating ethical …

A meta-summary of challenges in building products with ml components–collecting experiences from 4758+ practitioners

N Nahar, H Zhang, G Lewis, S Zhou… - 2023 IEEE/ACM 2nd …, 2023 - ieeexplore.ieee.org
Incorporating machine learning (ML) components into software products raises new
software-engineering challenges and exacerbates existing ones. Many researchers have …

Continuous auditing of artificial intelligence: A conceptualization and assessment of tools and frameworks

M Minkkinen, J Laine, M Mäntymäki - Digital Society, 2022 - Springer
Artificial intelligence (AI), which refers to both a research field and a set of technologies, is
rapidly growing and has already spread to application areas ranging from policing to …

Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK

N Stogiannos, R Malik, A Kumar… - The British Journal of …, 2023 - academic.oup.com
Technological advancements in computer science have started to bring artificial intelligence
(AI) from the bench closer to the bedside. While there is still lots to do and improve, AI …

Putting AI ethics into practice: The hourglass model of organizational AI governance

M Mäntymäki, M Minkkinen, T Birkstedt… - arXiv preprint arXiv …, 2022 - arxiv.org
The organizational use of artificial intelligence (AI) has rapidly spread across various
sectors. Alongside the awareness of the benefits brought by AI, there is a growing …

Large language models as subpopulation representative models: A review

G Simmons, C Hare - arXiv preprint arXiv:2310.17888, 2023 - arxiv.org
Of the many commercial and scientific opportunities provided by large language models
(LLMs; including Open AI's ChatGPT, Meta's LLaMA, and Anthropic's Claude), one of the …

Discerning between the “easy” and “hard” problems of AI governance

M Minkkinen, M Mäntymäki - IEEE Transactions on Technology …, 2023 - ieeexplore.ieee.org
While there is widespread consensus that artificial intelligence (AI) needs to be governed
owing to its rapid diffusion and societal implications, the current scholarly discussion on AI …

[PDF][PDF] Designing an AI governance framework: From research-based premises to meta-requirements.

M Mäntymäki, M Minkkinen, MP Zimmer, T Birkstedt… - ECIS, 2023 - researchgate.net
The development and increasing use of artificial intelligence (AI), particularly in high-risk
application areas, calls for attention to the governance of AI systems. Organizations and …

Quality assurance strategies for machine learning applications in big data analytics: an overview

M Ogrizović, D Drašković, D Bojić - Journal of Big Data, 2024 - Springer
Abstract Machine learning (ML) models have gained significant attention in a variety of
applications, from computer vision to natural language processing, and are almost always …

MLOps as enabler of trustworthy AI

Y Billeter, P Denzel, R Chavarriaga… - 2024 11th IEEE …, 2024 - ieeexplore.ieee.org
As Artificial Intelligence (AI) systems are becoming ever more capable of performing
complex tasks, their prevalence in industry, as well as society, is increasing rapidly …