Human-centered Artificial Intelligence: A Multidimensional Approach towards Real World Evidence

Bettina Schneider, Petra Asprion, Frank Grimberg

2019

Abstract

This study indicates the significance of a human-centered perspective in the analysis and interpretation of Real World Data. As an exemplary use-case, the construct of perceived ‘Health-related Quality of Life’ is chosen to show, firstly, the significance of Real World Data and, secondly, the associated ‘Real World Evidence’. We settled on an iterative methodology and used hermeneutics for a detailed literature analysis to outline the relevance and the need for a forward-thinking approach to deal with Real World Evidence in the life science and health care industry. The novelty of the study is its focus on a human-centered artificial intelligence, which can be achieved by using ‘System Dynamics’ modelling techniques. The outcome – a human-centered ‘Indicator Set’ can be combined with results from data-driven, AI-based analytics. With this multidimensional approach, human intelligence and artificial intelligence can be intertwined towards an enriched Real World Evidence. The developed approach considers three perspectives – the elementary, the algorithmic and – as novelty – the human-centered evidence. As conclusion, we claim that Real World Data are more valuable and applicable to achieve patient-centricity and personalization if the human-centered perspective is considered ‘by design’.

Paper Citation

in Harvard Style

Schneider B., Asprion P. and Grimberg F. (2019). Human-centered Artificial Intelligence: A Multidimensional Approach towards Real World Evidence.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 381-390. DOI: 10.5220/0007715503810390

in Bibtex Style

@conference{iceis19,
author={Bettina Schneider and Petra Asprion and Frank Grimberg},
title={Human-centered Artificial Intelligence: A Multidimensional Approach towards Real World Evidence},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={381-390},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007715503810390},
isbn={978-989-758-372-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Human-centered Artificial Intelligence: A Multidimensional Approach towards Real World Evidence
SN - 978-989-758-372-8
AU - Schneider B.
AU - Asprion P.
AU - Grimberg F.
PY - 2019
SP - 381
EP - 390
DO - 10.5220/0007715503810390