Conceptual operationalizations of empathy in NLP are varied, with some having specific behaviors and properties, while others are more abstract. How these variations relate to one another and capture properties of empathy observable in text remains unclear. To provide insight into this, we analyze the transfer performance of empathy models adapted to empathy tasks with different theoretical groundings. We study (1) the dimensionality of empathy definitions, (2) the correspondence between the defined dimensions and measured/observed properties, and (3) the conduciveness of the data to represent them, finding they have a significant impact to performance compared to other transfer setting features. Characterizing the theoretical grounding of empathy tasks as direct, abstract, or adjacent further indicates that tasks that directly predict specified empathy components have higher transferability. Our work provides empirical evidence for the need for precise and multidimensional empathy operationalizations.

The first Managing Mental Health & Wellbeing in the Workplace online course will be launched in December. In the Industrial Revolution 4.0, it is no longer about if companies should integrate artificial intelligence (AI) into their organisation, but about when and how. While it is natural to worry about AI replacing humans, thankfully, a recent whitepaper by Live with AI noted that jobs brought by the AI revolution won't be only reserved to computer specialists, enhanced human roles will emerge as well. The whitepaper noted that this is due to AI disrupting jobs task by task and not by entire job roles – something HR leaders can leverage on to disrupt disruption. Think about using tasks to better track technology impact, chart clearer pathways between jobs, and improve work prospects for people.

In the Industrial Revolution 4.0, it is no longer about if companies should integrate artificial intelligence (AI) into their organisation, but about when and how. While it is natural to worry about AI replacing humans, thankfully, a recent whitepaper by Live with AI noted that jobs brought by the AI revolution won't be only reserved to computer specialists, enhanced human roles will emerge as well. The whitepaper noted that this is due to AI disrupting jobs task by task and not by entire job roles – something HR leaders can leverage on to disrupt disruption. Think about using tasks to better track technology impact, chart clearer pathways between jobs, and improve work prospects for people. With human roles still being very relevant in the age of AI and automation, it is important to take into account the "human cause" in an automation journey, augmenting a task that satisfies the worker, not replacing it. This effectively places humans at the heart of the transformation process.