Empathetic, interpretable, and explainable Artificial Intelligence

The overarching aim of this research is to examine the impact of empathetic artificial intelligence (AI) on human-AI teaming in high-stakes contexts. Findings from this research could assist in understanding how human-AI interactions can be optimised for better outcomes in various high-stakes sectors, including military operations, aviation, healthcare, and law, among others. A specific use case pertinent to the collaborative partner of this project, Thales, is the high-pressure operations aboard submarines, where sonar operators face the challenge of analysing vast and complex data sets. This project aims to explore how integrating empathetic AI in such scenarios could alleviate the stress experienced by sonar operators while also improving the performance of the team.

The primary hypothesis is that an empathetic AI, attuned to the stressors and needs of human operators, will foster a stronger human-AI relationship, thereby enhancing the overall efficacy of the team. Moreover, this empathetic relationship will not only condition humans to build rapport with the AI but will also foster a reciprocal understanding where the human operator recognises and respects the limitations and needs of the AI. This bidirectional empathy, it is hypothesised, will lead to improved team performance and a reduction in the cognitive load of the human operator.

The research will utilise a serious game environment to test the proposed hypotheses. This controlled, yet ecologically valid, setting will allow for a thorough investigation of the psychological impacts of empathetic AI on human operators. The experiment will be designed to assess operator performance and stress levels in three distinct scenarios:

1. Operation without any AI assistance,
2. Operation with a regular, non-empathetic AI, and
3. Operation with an empathetic AI.

The comparative analysis of these scenarios will provide valuable insights into the specific role of empathy in enhancing human-AI team performance.

The findings of this research directly align with the UKRI's mission, as the integration of empathetic AI in human-AI teams is poised to contribute to prosperity by optimising team performance, as well as to the public good by reducing operator stress and cultivating better operational practices. These ideals are further echoed by the Centre for Doctoral Training (CDT) underpinning this project, ART-AI (Accountable, Responsible, and Transparent AI), which is committed to developing AI systems that uphold these values.