Recent studies have proposed the use of experiments to guide software development in order to build features that the user really wants. Some authors argue that this approach represents a new way to develop software that is different from the traditional requirement-driven one. In this position paper, we propose the di...
A key finding from the study indicates that simply the presence of an ethical tool has an effect on ethical consideration, creating more responsibility even in instances where the use of the tool is not intrinsically motivated.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 17 citations· ⚡2
This paper begins to address the focal problem of implementing ethics into AI system design and development in practice by providing elements needed for producing a baseline for ethics in AI based software development by means of an industrial multiple case study on AI systems development in the healthcare sector.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· International Conference on...· 18 citations· ⚡3
The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.
P. Abrahamsson, Goetz Botterweck, Hadi Ghanbari et al.· International Journal of Sys...· 14 citations
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The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
In this chapter, the results of a multivocal literature review are presented to offer 118 metrics practitioner experts think software startups should measure that can give you ideas for what your startup should measure.
Kai-Kristian Kemell, Xiaofeng Wang, Anh Nguyen-Duc et al.· Fundamentals of Software Sta...· 8 citations· ⚡1
This investigation revealed different types of AI systems and different AI development approaches, but it is common that business opportunities involving with AI systems are not validated and there is lack of business-driven metrics that guide the development ofAI systems.
Anh Nguyen-Duc, Ingrid Sundbø, E. Nascimento et al.· International Conference on...· 20 citations· ⚡1
This paper study software development in startups from the point of view of practices to better understand how startups develop software, and devise a list of practices which are categorized using the Essence Theory of Software Engineering (Essence).
Kai-Kristian Kemell, Ville Ravaska, Anh Nguyen-Duc et al.· International Conference on...· 5 citations
This study investigates the tactics behind software engineering (SE) activities by analyzing key engineering events during startup journeys and explores how entrepreneurial mindsets may be associated with SE knowledge areas and with each startup case.
Anh Nguyen-Duc, Kai-Kristian Kemell, P. Abrahamsson· Empirical Software Engineeri...· 23 citations· ⚡1
The first published version of StartCards is presented, which is considered useful for early-stage startups and can also be used as a pedagogical tool in startup education.
Kai-Kristian Kemell, Anh Nguyen-Duc, Mari Suoranta et al.· Information and Software Tec...· 25 citations· ⚡1
The Second International Workshop on Requirement Engineering for Software startups and Emerging Technologies (RESET) brought together requirements engineering researchers and practitioners to discuss the need for adapting conventional requirement engineering artifacts in developing and operating emerging technologies.
Anh Nguyen-Duc, Chetan Arora, P. Abrahamsson· 2023 IEEE 31st International...· 1 citation
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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