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1,707 papers
A holistic view of an iterative, continuous approach to develop industrial AI software basing on business goals, requirements and Minimum Viable Products is described and a research agenda with seven questions for future studies is proposed.
It is argued that AI software is still software and needs to be approached from the software development perspective, and whether the focus should be on AI ethics or the quality of an AI system, called a maturity model for the development of AI systems is discussed.
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The 6 week development journey towards a fully functional proof of concept prototype, reflections on the process as well as the technical details of the prototype are described.
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Common misconceptions of affects when dealing with job satisfaction, motivation, commitment, well-being, and happiness are provided; validated measurement instruments for affect measurement; and recommendations when measuring the affects of software developers are provided.
This paper conducts a qualitative interpretive study based on face-to-face open-ended interviews, in-field observations, and e-mail exchanges to construct a novel explanatory theory of the impact of affects on development performance.
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
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.
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
A Blog post by H company on Hugging Face
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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