Scaling trustworthy AI: A framework for responsible system design

AI technology is becoming more fluid and has impacted the society across a range of domains in a positive as well as in a negative manner. AI reliability is critical to society’s acceptance and preventing the risks connected to it hence the importance of the following measures. The purpose of this work is to synthesize a multifaceted approach to the further scaled implementation of trustworthy AI with a focus on responsible AI design. The framework is applied in theory as well as in two empirical cases, where the research combines theoretical and practical approaches. Main outcomes point to the importance of transparency management, accountability and ethical aspects in the effectiveness of AI applications. The discussed framework provides practical recommendations regarding how AI can be implemented responsibly at a large scale in an organization as an integrated system. The findings of this study must be viewed as significant for future development of AI technologies from both reliability and ethical perspectives with a view to ensuring the growth of public confidence in the application of reliable artificial intelligence technologies in the various sectors of our society.