Hybrid Intelligence for Digital Humanities

TL;DR

This paper examines how Hybrid Intelligence can meet the specific needs of Digital Humanities, proposing a framework that aligns HI principles with DH requirements to enhance digital research methods.

Contribution

It identifies five key DH requirements and maps them to CARE principles of HI, providing a structured approach for integrating AI in digital humanities research.

Findings

Mapping of DH requirements to HI principles

Examples of research projects applying this mapping

Discussion of open challenges in combining DH and HI

Abstract

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.