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Enhancing the knowledge management in societally sensitive domains with Generative AI

Year: 2024

Type: article

Abstract: Generative AI models can greatly enhance the knowledge management, by automatising the process of knowledge discovery, extraction, organisation and sharing. In the best-case scenario, the GPT based tools will help us to make better sense of the ever-growing piles of data and enhance the decision making at all levels – from short-term and personal decisions to long-term strategic planning. In the worst case, the Generative AI tools could, however, add a fuel to heated discussions on societally sensitive topics, by misinforming the service users. Careless application of this technology in crisis and disaster management and related domains, such as climate change adaptation and mitigation, resilient and sustainable development can lead to expensive and potentially disastrous decisions at all levels of responsibility and further aggravate already alarming loss of trust in authorities. This talk will discuss (1) the underlying reasons why Generative AI technology cannot and shouldn’t be blindly used as a knowledge base, (2) commonly used methods for minimising the underlying risks and enhancing the usability of generative AI in knowledge management applications, and (3) real world experiences of the author with use of generative AI models in extraction and synthesis of data in the climate change adaptation and mitigation domain.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.13768628

Authors: Havlik, Denis, Chettakattu, Aradina

Institution: AIT Austrian Institute of Technology GmbH

Language: English

Topic: Knowledge Management and Technology

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Climate action

Open Access status: green

Funder: European Commission