Will Artificial Intelligence Affect How Cultural Heritage Will Be Managed in the Future? Responses Generated by Four genAI Models

Author:

Spennemann Dirk H. R.1ORCID

Affiliation:

1. Gulbali Institute, Charles Sturt University, P.O. Box 789, Albury, NSW 2640, Australia

Abstract

Generative artificial intelligence (genAI) language models have become firmly embedded in public consciousness. Their abilities to extract and summarise information from a wide range of sources in their training data have attracted the attention of many scholars. This paper examines how four genAI large language models (ChatGPT, GPT4, DeepAI, and Google Bard) responded to prompts, asking (i) whether artificial intelligence would affect how cultural heritage will be managed in the future (with examples requested) and (ii) what dangers might emerge when relying heavily on genAI to guide cultural heritage professionals in their actions. The genAI systems provided a range of examples, commonly drawing on and extending the status quo. Without a doubt, AI tools will revolutionise the execution of repetitive and mundane tasks, such as the classification of some classes of artifacts, or allow for the predictive modelling of the decay of objects. Important examples were used to assess the purported power of genAI tools to extract, aggregate, and synthesize large volumes of data from multiple sources, as well as their ability to recognise patterns and connections that people may miss. An inherent risk in the ‘results’ presented by genAI systems is that the presented connections are ‘artifacts’ of the system rather than being genuine. Since present genAI tools are unable to purposively generate creative or innovative thoughts, it is left to the reader to determine whether any text that is provided by genAI that is out of the ordinary is meaningful or nonsensical. Additional risks identified by the genAI systems were that some cultural heritage professionals might use AI systems without the required level of AI literacy and that overreliance on genAI systems might lead to a deskilling of general heritage practitioners.

Publisher

MDPI AG

Reference106 articles.

1. Spennemann, D.H.R. (2023). Will the age of generative Artificial Intelligence become an age of public ignorance?. Preprint, 1–12.

2. Markov, T., Zhang, C., Agarwal, S., Eloundou, T., Lee, T., Adler, S., Jiang, A., and Weng, L. (2023, June 28). New and Improved Content Moderation Tooling. Available online: https://openai.com/blog/new-and-improved-content-moderation-tooling/.

3. Collins, E., and Ghahramani, Z. (2023, September 01). LaMDA: Our Breakthrough Conversation Technology. Available online: https://web.archive.org/web/20230130233845mp_/https://openai.com/blog/new-and-improved-content-moderation-tooling/.

4. Frąckiewicz, M. (2023, June 29). ChatGPT-4 for Digital Archaeology: AI-Powered Artifact Discovery and Analysis. Available online: https://ts2.space/en/chatgpt-4-for-digital-archaeology-ai-powered-artifact-discovery-and-analysis/.

5. Spennemann, D.H.R. (2023). What has ChatGPT read? References and referencing of archaeological literature by a generative artificial intelligence application. arXiv.

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