Ethical Decision Making in Iot Data Driven Research: A Case Study of a Large-Scale Pilot.
Sofia SegkouliGiuseppe FicoCecilia Vera-MuñozMario LecumberriAntonis VoulgaridisAndreas K TriantafyllidisPilar SalaStefano NunziataNadia CampaniniEnrico MontanariSuzanne MortonAlexandre DuclosFrancesca CocchiMario Diaz NavaTrinidad de LorenzoEleni ChalkiaMatina LoukeaJuan Bautista Montalvá ColomerGeorge E DafoulasSergio GuillénMaría Teresa Arredondo WaldmeyerKonstantinos VotisPublished in: Healthcare (Basel, Switzerland) (2022)
IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions. The main objective of the current article is to present the successful completion of a collaborative multiscale research work, which addressed the complicated exercise of ethical decision making in IoT smart ecosystems for older adults. Our results reveal that among the strong enablers of the proposed ethical decision support model were the participatory and deliberative procedures complemented by a set of regulatory and non-regulatory tools to operationalize core ethical values such as transparency, trust, and fairness in real care settings for older adults and their caregivers.
Keyphrases
- decision making
- big data
- physical activity
- healthcare
- palliative care
- artificial intelligence
- transcription factor
- machine learning
- clinical trial
- climate change
- randomized controlled trial
- study protocol
- health information
- genome wide
- electronic health record
- gene expression
- multiple sclerosis
- social media
- deep learning
- body composition
- data analysis