# Hybrid Intelligence for Digital Humanities

arXiv: https://arxiv.org/abs/2406.15374 · HTML: https://mlsanity.com/paper/2406.15374/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 49 references that are in the map.
- First posted on arXiv 15 Apr 2024.

## Builds on (most cited first, 2 of 2)

- [If the Sources Could Talk: Evaluating Large Language Models for Research Assistance in History](https://mlsanity.com/paper/2310.10808/) (2023)
- [How Contentious Terms About People and Cultures are Used in Linked Open Data](https://mlsanity.com/paper/2311.10757/) (2023)

## Built on by (most cited first, 1 of 1)

- [From Historical Tabular Image to Knowledge Graphs: A Provenance-Aware Modular Pipeline](https://mlsanity.com/paper/2605.08222/) (2026)

## Abstract (arXiv)

In this paper, we explore the synergies between Digital Humanities (DH) as a discipline and Hybrid Intelligence (HI) as a research paradigm. In DH research, the use of digital methods and specifically that of Artificial Intelligence is subject to a set of requirements and constraints. We argue that these are well-supported by the capabilities and goals of HI. Our contribution includes the identification of five such DH requirements: Successful AI systems need to be able to 1) collaborate with the (human) scholar; 2) support data criticism; 3) support tool criticism; 4) be aware of and cater to various perspectives and 5) support distant and close reading. We take the CARE principles of Hybrid Intelligence (collaborative, adaptive, responsible and explainable) as theoretical framework and map these to the DH requirements. In this mapping, we include example research projects. We finally address how insights from DH can be applied to HI and discuss open challenges for the combination of the two disciplines.