Publicação
The role of artificial intelligence in achieving environmental sustainability for the health and technological industry
| Resumo: | Artificial Intelligence (AI) represents a fundamental technology that is shaping various sectors globally. This work explores the complex and multifaceted landscape of AI, including its core concepts, evolution, transformative applications, and its relationship with the Sustainable Development Goals (SDGs). The analysis of AI's role in the health and technology sectors, based on empirical evidence, validates its applicability and transformative potential, as well as AI-based solutions designed to address environmental challenges. The literature review also reveals the relevance of regulatory frameworks currently governing AI at a national, European, and international levels. Through a mixed-methods approach, including the creation of an online survey directed at sector professionals, this study identified patterns in the implementation of AI-based environmental sustainability solutions in the health and technology industries. Survey results revealed that 57% of organizations use Machine Learning (ML) as their primary AI capability, and 70% of respondents apply these technologies for environmental data collection and analysis. Carbon footprint analysis and Greenhouse Gases (GHGs) emission reduction strategies emerged as the most offered service, representing approximately 61% of responses. However, the study also identified several present-day challenges, with 43% of respondents indicating data quality and integrity as the main obstacle to AI implementation in this sector. Regarding the impact of AI-based solutions, results demonstrate an average success rate of 37% in community engagement adding to significant variations in GHGs emissions reduction, obtaining results between 8% and 70%. Future perspectives appear highly promising, with approximately 66% of respondents predicting a significant impact of AI on sustainability practices within a 1-to-5-year horizon. The main development focuses identified include addressing emerging environmental risks (35%), improving the efficiency of sustainability practices (27%), and progressively scaling existing solutions (24%). This research thus aims to contribute to advancing knowledge about AI's transformative role in implementing and improving environmental sustainability practices, offering empirical evidence and practical perspectives for key decision-makers, government entities, researchers, and to all professionals operating at the intersection of technology, sustainability, and health. |
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| Autores principais: | Ribeiro, João Pedro Silva |
| Assunto: | Inteligência artificial -- Artificial intelligence Sustentabilidade ambiental -- Environmental sustainability Health industry Technological industry Indústria da saúde Indústria tecnológica |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | ISCTE |
| Idioma: | inglês |
| Origem: | Repositório ISCTE |
| Resumo: | Artificial Intelligence (AI) represents a fundamental technology that is shaping various sectors globally. This work explores the complex and multifaceted landscape of AI, including its core concepts, evolution, transformative applications, and its relationship with the Sustainable Development Goals (SDGs). The analysis of AI's role in the health and technology sectors, based on empirical evidence, validates its applicability and transformative potential, as well as AI-based solutions designed to address environmental challenges. The literature review also reveals the relevance of regulatory frameworks currently governing AI at a national, European, and international levels. Through a mixed-methods approach, including the creation of an online survey directed at sector professionals, this study identified patterns in the implementation of AI-based environmental sustainability solutions in the health and technology industries. Survey results revealed that 57% of organizations use Machine Learning (ML) as their primary AI capability, and 70% of respondents apply these technologies for environmental data collection and analysis. Carbon footprint analysis and Greenhouse Gases (GHGs) emission reduction strategies emerged as the most offered service, representing approximately 61% of responses. However, the study also identified several present-day challenges, with 43% of respondents indicating data quality and integrity as the main obstacle to AI implementation in this sector. Regarding the impact of AI-based solutions, results demonstrate an average success rate of 37% in community engagement adding to significant variations in GHGs emissions reduction, obtaining results between 8% and 70%. Future perspectives appear highly promising, with approximately 66% of respondents predicting a significant impact of AI on sustainability practices within a 1-to-5-year horizon. The main development focuses identified include addressing emerging environmental risks (35%), improving the efficiency of sustainability practices (27%), and progressively scaling existing solutions (24%). This research thus aims to contribute to advancing knowledge about AI's transformative role in implementing and improving environmental sustainability practices, offering empirical evidence and practical perspectives for key decision-makers, government entities, researchers, and to all professionals operating at the intersection of technology, sustainability, and health. |
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