8 Sustainability with artificial intelligence: obstacles, opportunities, and research agenda
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Ekta Dixit
Abstract
Artificial intelligence (AI) has the capacity to address critical global challenges, including sustainability, and is poised to transform business practices and entire sectors. Tackling the climate crisis and environmental degradation requires forward-thinking and innovative solutions. AIAI is seen as a tool that can help reshape organizational strategies and individual actions in ways that align with cultural norms, ultimately leading to optimized energy consumptionenergy consumption and less depletion of natural resourcesnatural resources. The objective is to promote innovative researchinnovative research and tangible AI solutions that advance ecological sustainabilityecological sustainability. The real advantage of AI lies not just in optimizing the use of energyenergy, water, and land but in enhancing environmental governanceenvironmental governance on a larger scale. A review of existing studies uncovers several challenges such as the heavy reliance on historical data in machine learningmachine learning models, unpredictable human reactions to AI-driven interventions, elevated cybersecurity risks, adverse effects of AI uses, and complexities in assessing the effectiveness of interventions. To address these issues, it is suggested that future research focus on integrating systems thinking, incorporating a wide range of perspectives, design approaches, as well as examining sociological, psychological, and economic factors. This comprehensive approach would ensure that AI offers immediate solutions while safeguarding the long-term viability of the environment.
Abstract
Artificial intelligence (AI) has the capacity to address critical global challenges, including sustainability, and is poised to transform business practices and entire sectors. Tackling the climate crisis and environmental degradation requires forward-thinking and innovative solutions. AIAI is seen as a tool that can help reshape organizational strategies and individual actions in ways that align with cultural norms, ultimately leading to optimized energy consumptionenergy consumption and less depletion of natural resourcesnatural resources. The objective is to promote innovative researchinnovative research and tangible AI solutions that advance ecological sustainabilityecological sustainability. The real advantage of AI lies not just in optimizing the use of energyenergy, water, and land but in enhancing environmental governanceenvironmental governance on a larger scale. A review of existing studies uncovers several challenges such as the heavy reliance on historical data in machine learningmachine learning models, unpredictable human reactions to AI-driven interventions, elevated cybersecurity risks, adverse effects of AI uses, and complexities in assessing the effectiveness of interventions. To address these issues, it is suggested that future research focus on integrating systems thinking, incorporating a wide range of perspectives, design approaches, as well as examining sociological, psychological, and economic factors. This comprehensive approach would ensure that AI offers immediate solutions while safeguarding the long-term viability of the environment.
Kapitel in diesem Buch
- Frontmatter I
- Preface V
- Contents VII
- List of contributors IX
- 1 Leveraging computational intelligence and mathematical modeling for sustainable future in agriculture: a unified paradigm for recognizing tomato leaf diseases 1
- 2 Digital dawn: how immersive technologies are shaping a sustainable future 37
- 3 Sustainable intelligence: ethical issues in the evolution of intelligent systems 57
- 4 Energy sustainability and computational intelligence based routing protocols in WSN: an analytical survey 75
- 5 Harnessing the metaverse for healthcare innovation: exploring predictive analytics and AI-driven personalization 91
- 6 Toward a sustainable future: a computational intelligence fusion framework of color and darknet features for the classification of crop leaf diseases 109
- 7 Sustainable computing approaches for complex medical image analysis: a neurodiagnostic perspective 139
- 8 Sustainability with artificial intelligence: obstacles, opportunities, and research agenda 161
- 9 Smart solutions to a sustainable future 177
- 10 Ethical issues in intelligent systems for sustainability 195
- 11 CPS: cyber-physical system security for the Industrial Internet of Things in smart grid 215
- 12 Integrating mathematical computing and deep learning for efficient monkeypox skin lesion detection: A pathway to sustainable health solutions 253
- 13 Leveraging heuristics based on CK Metrics Suite for quality enhancement in sustainable quantum software development 271
- 14 Intelligent systems for fire management and sustainability 297
- 15 Transparent and sustainable AI for brain tumor detection: from conventional to hybrid models in predictive healthcare 323
- Index 349
- Mathematical Methods in the Digital Age
Kapitel in diesem Buch
- Frontmatter I
- Preface V
- Contents VII
- List of contributors IX
- 1 Leveraging computational intelligence and mathematical modeling for sustainable future in agriculture: a unified paradigm for recognizing tomato leaf diseases 1
- 2 Digital dawn: how immersive technologies are shaping a sustainable future 37
- 3 Sustainable intelligence: ethical issues in the evolution of intelligent systems 57
- 4 Energy sustainability and computational intelligence based routing protocols in WSN: an analytical survey 75
- 5 Harnessing the metaverse for healthcare innovation: exploring predictive analytics and AI-driven personalization 91
- 6 Toward a sustainable future: a computational intelligence fusion framework of color and darknet features for the classification of crop leaf diseases 109
- 7 Sustainable computing approaches for complex medical image analysis: a neurodiagnostic perspective 139
- 8 Sustainability with artificial intelligence: obstacles, opportunities, and research agenda 161
- 9 Smart solutions to a sustainable future 177
- 10 Ethical issues in intelligent systems for sustainability 195
- 11 CPS: cyber-physical system security for the Industrial Internet of Things in smart grid 215
- 12 Integrating mathematical computing and deep learning for efficient monkeypox skin lesion detection: A pathway to sustainable health solutions 253
- 13 Leveraging heuristics based on CK Metrics Suite for quality enhancement in sustainable quantum software development 271
- 14 Intelligent systems for fire management and sustainability 297
- 15 Transparent and sustainable AI for brain tumor detection: from conventional to hybrid models in predictive healthcare 323
- Index 349
- Mathematical Methods in the Digital Age
