Enhancing the knowledge management in societally sensitive domains with Generative AI

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-13
DOI
https://doi.org/10.5281/zenodo.13768629
Primary Topic
Advanced Statistical Methods and Models
Type
article
Field-Weighted Citation Impact
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article

Enhancing the knowledge management in societally sensitive domains with Generative AI

Zenodo (CERN European Organization for Nuclear Research)
Advanced Statistical Methods and Models
article

Enhancing the knowledge management in societally sensitive domains with Generative AI

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
AIT Austrian Institute of Technology GmbH (AT)
Climate action
Openalex Percentile: Top 52%
Advanced Statistical Methods and Models
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