3 Sustainable intelligence: ethical issues in the evolution of intelligent systems
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Anshika Sharma
Abstract
Intelligent systems (IS), which include technologies like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), are revolutionizing sustainability initiatives by improving decision-making, automating procedures, and optimizing resource use in a variety of industries. Significant lowering of environmental damage, boosting production, and encouraging effective resource management in industries like agriculture, energy generation, handling waste, and urban planning are all made possible by IS, which processes vast amounts of data to find patterns and predict results. Waste reduction, precision farming, environmental tracking, sustainable water utilization, smart city development, and better energy distribution are all made possible by their real-time monitoring, versatility, and self-sustaining capabilities. But while IS provide creative answers for sustainability, they also bring up important moral issues, such as algorithmic prejudice, data privacy issues, and the effects of their computing demands on the environment. For IS developments to actually serve sustainable development goals, these ethical concerns must be addressed. This chapter examines the revolutionary potential of IS in fostering social responsibility and environmental stewardship, talks about important applications and real-world examples, draws attention to related ethical issues, and offers solutions for creating just, moral, and energy-efficient intelligent systems for a sustainable future.
Abstract
Intelligent systems (IS), which include technologies like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), are revolutionizing sustainability initiatives by improving decision-making, automating procedures, and optimizing resource use in a variety of industries. Significant lowering of environmental damage, boosting production, and encouraging effective resource management in industries like agriculture, energy generation, handling waste, and urban planning are all made possible by IS, which processes vast amounts of data to find patterns and predict results. Waste reduction, precision farming, environmental tracking, sustainable water utilization, smart city development, and better energy distribution are all made possible by their real-time monitoring, versatility, and self-sustaining capabilities. But while IS provide creative answers for sustainability, they also bring up important moral issues, such as algorithmic prejudice, data privacy issues, and the effects of their computing demands on the environment. For IS developments to actually serve sustainable development goals, these ethical concerns must be addressed. This chapter examines the revolutionary potential of IS in fostering social responsibility and environmental stewardship, talks about important applications and real-world examples, draws attention to related ethical issues, and offers solutions for creating just, moral, and energy-efficient intelligent systems for a sustainable future.
Chapters in this book
- 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
Chapters in this book
- 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
