%0 Conference Paper %1 schaschek2023measuring %A Schaschek, Myriam %A Engel, Sarah %B International Conference on Information Systems 2023 %D 2023 %I AIS %K AI Trustworthy %T Measuring Trustworthiness of AI Systems: A Holistic Maturity Model %U https://www.researchgate.net/publication/377982917_Measuring_Trustworthiness_of_AI_Systems_A_Holistic_Maturity_Model %X Artificial intelligence (AI) has an impact on business and society at large while posing challenges and risks. For AI adoption, trustworthiness is paramount, yet there appears to be a gap between theory and practice. Organizations need guidance in quantitatively assessing and improving the trustworthiness of AI systems. To address such challenges, maturity models have shown to be a valuable instrument. However, recent AI maturity models address trustworthiness only at the maturest level. As a response, we propose a model to integrate the concept of trustworthiness across the AI lifecycle management. In doing so, we follow Design Science Research to develop a holistic model highlighting the importance of trustworthiness throughout the AI adoption journey to realize the real value potential. This research-in-progress contributes to the emerging research on human-AI systems and managing AI. Our objective is to use the model for assessing, evaluating, and improving trustworthy AI on an organizational level.

@inproceedings{schaschek2023measuring, abstract = {Artificial intelligence (AI) has an impact on business and society at large while posing challenges and risks. For AI adoption, trustworthiness is paramount, yet there appears to be a gap between theory and practice. Organizations need guidance in quantitatively assessing and improving the trustworthiness of AI systems. To address such challenges, maturity models have shown to be a valuable instrument. However, recent AI maturity models address trustworthiness only at the maturest level. As a response, we propose a model to integrate the concept of trustworthiness across the AI lifecycle management. In doing so, we follow Design Science Research to develop a holistic model highlighting the importance of trustworthiness throughout the AI adoption journey to realize the real value potential. This research-in-progress contributes to the emerging research on human-AI systems and managing AI. Our objective is to use the model for assessing, evaluating, and improving trustworthy AI on an organizational level.}, added-at = {2023-10-04T15:19:49.000+0200}, author = {Schaschek, Myriam and Engel, Sarah}, biburl = {https://www.bibsonomy.org/bibtex/287035aba79ee0ed3277b19ea86200df5/winkelmann}, booktitle = {International Conference on Information Systems 2023}, interhash = {ac7b6b7e25fe0c6a1a3fc693be588a34}, intrahash = {87035aba79ee0ed3277b19ea86200df5}, keywords = {AI Trustworthy}, publisher = {AIS}, timestamp = {2024-04-16T08:08:59.000+0200}, title = {Measuring Trustworthiness of AI Systems: A Holistic Maturity Model}, url = {https://www.researchgate.net/publication/377982917_Measuring_Trustworthiness_of_AI_Systems_A_Holistic_Maturity_Model}, venue = {Hyderabad, India}, year = 2023 }