Abstract
In recent years, the use of Artificial Intelligence agents to augment and enhance the operational decision making of human agents has increased. This has delivered real benefits in terms of improved service quality, delivery of more personalised services, reduction in processing time, and more efficient allocation of resources, amongst others. However, it has also raised issues which have real-world ethical implications such as recommending different credit outcomes for individuals who have an identical financial profile but different characteristics (e.g., gender, race). The popular press has highlighted several high-profile cases of algorithmic discrimination and the issue has gained traction. While both the fields of ethical decision making and Explainable AI (XAI) have been extensively researched, as yet we are not aware of any studies which have examined the process of ethical decision making with Intelligence augmentation (IA). We aim to address that gap with this study. We amalgamate the literature in both fields of research and propose, but not attempt to validate empirically, propositions and belief statements based on the synthesis of the existing literature, observation, logic, and empirical analogy. We aim to test these propositions in future studies.
Highlights
The use of Artificial Intelligence (AI) agents has gained widespread attention in the last few years (Science and Technology Committee 2018)
“clinicians work more efficiently and better handle complex information”. It has been utilised in the criminal justice system to detect crime hotspots and decide whether a suspect could be eligible for deferred prosecution (Oxford Internet Institute 2017), and by financial services providers to determine the outcome of a credit application
This paper aims to contribute to the literature base by synthesising the fields of ethical decision making and Explainable AI (XAI)
Summary
The use of Artificial Intelligence (AI) agents has gained widespread attention in the last few years (Science and Technology Committee 2018). As highlighted by the Academy of Medical Science (2017), Intelligence augmentation has been used in healthcare to enable “clinicians work more efficiently and better handle complex information”. It has been utilised in the criminal justice system to detect crime hotspots and decide whether a suspect could be eligible for deferred prosecution (Oxford Internet Institute 2017), and by financial services providers to determine the outcome of a credit application The issue has gained such attention that the UK Parliament Select Committee on Science and Technology commissioned an enquiry to investigate accountability and transparency in algorithmic decision making Martin et al (2019) argue that “ethical biases in technology might take the form of [ . . . ] biases or values accidentally or purposely built into a product’s design assumptions”
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