Towards a framework for responsible AI in supply chain management

The supply chain and logistics industry has undergone a rapid transformation due to the constant adoption of cutting-edge technologies to optimize the entire value chain and respond to continuously changing customer expectations (Besinger, Vejnoska and Ansari, 2024) . There is increasing evidence that artificial intelligence (AI) is being integrated into supply chains across multiple subdomains. The concept of AI can be defined as the ability of a system to reproduce human intelligence, ideally rationalizing and taking actions that are likely to achieve a particular objectives (Čerka, Grigienė and Sirbikytė, 2015). In response to the growing concern regarding the impact of AI, the field of artificial intelligence ethics has emerged. This field is emerging as a subset of the broader field of digital ethics, which addresses issues raised by the development and deployment of new digital technologies, such as artificial intelligence, big data analytics, and blockchains (Kazim and Koshiyama, 2021).
Research output and literature indicate that artificial intelligence is increasingly being used in supply chain processes. Several areas of supply chain management can be improved and optimised through it. It is evident that the use of AI in supply chain shape current and future trends due to the perceived benefits mainly related to data driven-decision-making which in turn impact performance and competition (Riahi, Saikouk, Gunasekaran and Badraoui, 2021). However, the current literature reveals less attention to the ethical considerations of the AI implementation that shows a clear theory practice gap (Bleher and Braun, 2023). The unethical or irresponsible AI practices can be due to misuse of technology such as facial recognition surveillance and mass data collection without appropriate consent and they can be also due to technology design flaws resulting in data bias, security concerns and unfair decisions(Kazim and Koshiyama, 2021). AI systems may embed biases, contribute to climate degradation, threaten human rights, and more (UNESCO, 2021).
This research aims at addressing the research gap through developing a conceptual framework for responsible AI in supply chain context for further empirical investigation. The model is informed by extant literature that discussed responsible AI applications within various industries and guided by ethical frameworks and guidelines, such as the IEEE Ethically Aligned Design framework (IEEE, 2019), the AI Ethics Guidelines developed by organizations such as the European Commission (Madiega, 2019), The UNESCO recommendations on the ethics of AI (UNESCO, 2021) and the UAE AI Ethics guidelines (MOAI, 2022). The paper provides a deliberate discussion of the main responsible AI dimensions within the supply chain context that should covers the design, development, and the implementation phases of an AI system. The supply chain AI ethics framework is theoretically underpinned by a refined approach of three AI ethics theories including embedded ethics, ethically aligned approach, and Value Sensitive Design. The proposed framework integrates the stakeholder view across all the AI phases. The main dimensions of the developed supply chain AI ethics framework include human-centricity, transparency, explainability, accountability, equity & fairness, sustainability, data governance & privacy, stakeholders’ engagement, risk management & resilience and finally continuous improvement and ethical review.
The proposed model was developed for further empirical investigation to address the identified AI ethics implementation theory-practice gap within supply chain context that should have theoretical and managerial implications to inform decision-making.