Short answer
Adopt a dual perspective: design AI to solve sustainability challenges and design AI systems to be sustainable.
- Field
- Sustainability
- Source
- Preprints.org (2023)
- Method
- Systematic Mapping Study
- Evidence
- Strong effect
Artificial Intelligence can be leveraged as a powerful tool to advance sustainability goals across economic, social, and environmental dimensions, while simultaneously requiring a focus on the sustainability of AI systems themselves. This sustainability research insight is drawn from a 2023 study published in Preprints.org. Using Systematic mapping study, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Adopt a dual perspective: design AI to solve sustainability challenges and design AI systems to be sustainable.
AI Integration for Holistic Sustainability: Balancing Tool and System
Artificial Intelligence can be leveraged as a powerful tool to advance sustainability goals across economic, social, and environmental dimensions, while simultaneously requiring a focus on the sustainability of AI systems themselves.
Preprints.org · 2023
Key Findings
- 01Research on AI and sustainability has evolved from fragmented approaches to a more holistic understanding.
- 02There is an increasing integration of both 'AI as a tool for sustainability' and 'Sustainability of AI' perspectives.
- 03AI's impact spans economic, social, and environmental dimensions.
Application
Design takeaway
Adopt a dual perspective: design AI to solve sustainability challenges and design AI systems to be sustainable.
How to apply
When developing new products or systems, investigate how AI can enhance their sustainability performance and assess the environmental and social impact of the AI components themselves.
Project actions
- 01Investigate how AI can be used to optimize material usage in your design project.
- 02Consider the energy footprint of any AI features you propose.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Comprehensive review of a broad research area.
- +Identification of evolving trends in AI and sustainability research.
Limitations
The rapid pace of AI development means research findings can quickly become outdated.
Reliability & validity
The reliability of the systematic mapping study depends on the rigor of the search strategy and inclusion criteria. Validity is enhanced by the broad scope across multiple dimensions.
Think critically
To what extent does the 'sustainability of AI' outweigh the benefits of 'AI as a tool for sustainability' in certain applications?
Design Principles
"Embrace AI as a catalyst for sustainable innovation, ensuring that the technology's own lifecycle aligns with ecological and social responsibility."
Designers and engineers must consider the dual role of AI in sustainability initiatives. This involves not only developing AI solutions that promote environmental protection, social equity, and economic viability but also ensuring that the development, deployment, and lifecycle of AI technologies are themselves sustainable.
What This Means for Your Design
AI can help make things more sustainable (like reducing waste), but we also need to make sure the AI itself doesn't use too much energy or create problems.
How to use in your project
- 1.Reference this study when discussing the potential of AI in your design project's sustainability strategy.
- 2.Use the findings to justify the inclusion of AI-driven features aimed at improving environmental or social outcomes.
Add to My Project
Quick Cite
Paragraph starter
The integration of Artificial Intelligence presents a dual opportunity for advancing sustainability: it can serve as a powerful tool to address environmental, social, and economic challenges, while simultaneously necessitating a critical examination of the sustainability of AI technologies themselves. As research indicates a shift towards a more holistic understanding, designers should consider both the application of AI for eco-innovation and the lifecycle impact of AI systems.
Source
Questions About This Research
- What does the research say about ai integration for holistic sustainability: balancing tool and system?
- Adopt a dual perspective: design AI to solve sustainability challenges and design AI systems to be sustainable. Evidence: Preprints.org (2023).
- Why does "AI Integration for Holistic Sustainability: Balancing Tool and System" matter for design?
- Designers and engineers must consider the dual role of AI in sustainability initiatives. This involves not only developing AI solutions that promote environmental protection, social equity, and economic viability but also ensuring that the development, deployment, and lifecycle of AI technologies are themselves sustainable.
- How can designers apply this research?
- Adopt a dual perspective: design AI to solve sustainability challenges and design AI systems to be sustainable.
- What were the main findings?
- Research on AI and sustainability has evolved from fragmented approaches to a more holistic understanding.. There is an increasing integration of both 'AI as a tool for sustainability' and 'Sustainability of AI' perspectives.. AI's impact spans economic, social, and environmental dimensions.
- What research method was used?
- Systematic Mapping Study.
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2023 journal from Preprints.org.
- What should I do differently in my next project?
- When developing new products or systems, investigate how AI can enhance their sustainability performance and assess the environmental and social impact of the AI components themselves.
- What are the limitations?
- The review's scope and the potential for bias in the selection of studies.