Aleisa, Monirah, Alshahrani, Mona, Beloff, Natalia and White, Martin (2022) TAIRA-BSC - trusting AI in recruitment applications through blockchain smart contracts. IEEE Blockchain 2022, Espoo, Finland, August 22-25 2022. Published in: Blockchain 2022. 376-382. IEEE ISBN 9781665461047

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Abstract

Artificial Intelligence (AI) and Blockchain Technology (BCT) are considered two of the most trending and disruptive technologies. BCT, although commonly associated with cryptocurrencies, has shown a tremendous impact among many other distributed applications domains. BCT characteristics, such as the distribution of data storage among independent nodes and the use of consensus algorithms offering immutability and transparency, remove the need for a central authority making BCT a trustful technology. However, currently decision-makers and stakeholders lack the confidence to overcome the perception of risk and uncertainty related to AI technology. This lack of trust is crucial in accepting the deployment of AI Technology in wider application domains, such as the recruitment process. Further, current research literature does not adequately investigate the role of trust and how it can be implemented as an integral part of a AI recruitment based application. Therefore, the aim of this paper is to investigate how emerging BCT and AI technologies can improve decision making and stakeholder trust in a job recruitment system that is traditionally focused on human expert decision making. In this paper we propose the design of a new solution for trusting AI in recruitment applications through the use of Blockchain Smart Contracts (TAIRA-BSC). TAIRA-BSC integrates Blockchain Smart Contracts (BSC) with the Data Lake (DL), Machine Learning (ML) and AI technologies in our AI Recruitment Model (AIRM) architecture. TAIRA-DSC improves transparency and interoperability in the recruitment process while protecting sensitive job candidate data and ensures data integrity delivery and traceability in the recruiting process through a verifiable decentralised ledger, i.e. the blockchain and associated smart contracts. The research work presented in this paper also provides an architectural proof of concept demonstrating a novel approach to implementing an AI based job recruitment application integrating BCT to provide trust and traceability in the recruitment process for both decision makers (e.g. job recruitment agency) and other stakeholders (e.g. job seekers). The paper presents a state-of-the-art on discussion on integrating AI with BCT focusing on how BCT can be used to bridge trust concerns with AI systems. We also present a conceptual architecture (TAIRA-BSC) developed to serve as a foundation for future studies focused on enhancing trust in AI applications through the integration of BCT.

Item Type:	Conference Proceedings
Keywords:	Artificial intelligence, Blockchain technology, distributed ledger technology, Data Lake, Smart Contracts, Trust
Schools and Departments:	School of Engineering and Informatics > Informatics
Research Centres and Groups:	Creative Technology
SWORD Depositor:	Mx Elements Account
Depositing User:	Mx Elements Account
Date Deposited:	18 Aug 2022 09:17
Last Modified:	23 Sep 2022 13:08
URI:	http://sro.sussex.ac.uk/id/eprint/107449

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