Sustainability in a Nutshell (Weekly Update September 28, 2023)

How 4 startups are using AI to solve climate change challenges

?? Refiberd: Tackling Textile Waste with AI

• 186 Million pounds of textile waste annually, <1% recycled.
• AI sorts textiles by material & color and removes contaminants.
• Goal: Preserve most of the material in recycling.

?? Mortar IO: Decarbonizing Buildings

• Buildings = 40% of global carbon emissions.
• AI plans carbon reduction for buildings in minutes.
• Future: AI chatbot for tailored energy audits.

?? AgroScout: Sustainable Crop Monitoring

• Climate change threatens crop yields.
• AI detects pests & diseases early and reduces agrochemical use by 85%.
• 2.4M images across 145,000 acres & 20 countries.

?? Eugenie.ai: Reducing Manufacturing Emissions

• Targets metal, mining, oil, and gas industries.
• AI analyzes satellite & machine data to reduce emissions by 20-30%.
• Vision: Greener, sustainable future for generations.

In a Nutshell:?

Startups are leveraging AI to address climate change challenges across various sectors, from textile recycling to building decarbonization, crop monitoring, and manufacturing emissions reduction. Collaborative efforts and innovative solutions are crucial for a sustainable future.?

?? Video of the week

?? Sustainable Farming

How AI is improving agriculture sustainability in India

?? AI boosts agriculture sustainability in India

• Half of India's population relies on farming
• Challenges: Climate change, unsustainable practices
• India's role: Key global producer (rice, wheat, etc.)

??? Google's AI-driven "landscape understanding"

• Uses satellite imagery for field boundaries
• Determines acreage, forest areas, irrigation structures
• Aids in drought preparedness with water data

?? Detailed "landscape monitoring" models

• Provides field performance & future needs
• Data: Crop type, field size, water distance, sow/harvest dates
• In-depth info on farm ponds for water security

?? Collaborative research for impactful insights

• Partnerships: State governments, academics, communities
• Field visits for farmer feedback & needs
• Benefits: Improved loans, state support, tech growth

In a nutshell:?

Leveraging AI, Google is enhancing agricultural sustainability in India, addressing challenges like climate change and inefficient practices. Collaborative research provides insights that benefit individual farmers, the broader agricultural ecosystem, and the global food supply.

?? Water Conservation?

The power of data: how Artificial Intelligence is transforming water

?? AI Transforms Water Management

• 'Digital water' systems optimize water use
• Smart water management reduces inefficiencies
• Pilot projects like Silo.AI show potential for human-AI collaboration

?? AI Tackles Water Waste

• AI detects leaks and anomalies in real-time
• The US wastes 7 billion gallons of water daily
• Immediate system responses prevent wastage

?? Smart Farming with AI

• Agriculture uses 70% of global water, 60% wasted
• AI analytics suggest optimal crop management
• 'Smart irrigation' systems ensure precise water use

?? AI's Future Impact on Water

• AI could contribute $5.2 trillion to the global economy
• Potential 4% GHG reduction by 2030
• Aims for sustainable water supply even in stressed regions

In a nutshell:?

AI's integration into water management can revolutionize the way we conserve and use water. This has the potential to address global challenges like water scarcity, wastage, and inefficiencies, leading to both environmental and economic benefits.?

?? Circularity

ARTIFICIAL INTELLIGENCE AND THE CIRCULAR ECONOMY

?? AI & Circular Economy

• AI can accelerate the transition to a circular economy
• Design out waste, optimize business models, streamline infrastructure

?? What is AI?

• Machines solving specific problems
• Differentiates from conventional software by learning
• Not necessarily human-like consciousness

?? General vs. Specialised AI

• General AI mimics full human cognitive abilities
• Specialized AI excels in specific tasks like image recognition

?? Debunking AI Myths

• Artificial Intelligence (AI) is not a recent development; it originated in 1956.
• AI is not the same as robotics.
• AI is distinct from machine learning.

?? Design Powered by AI

• AI informs designers’ choices for circular economy
• Analyzes data for better designs faster

?? Circular Business Models

• AI optimizes circular business models
• Techniques similar to the linear economy but more sustainable

??? Infrastructure & AI

• AI streamlines the circulation of materials
• Recognizes and identifies objects for sorting and recycling

?? Limitations of AI

• Fairness, privacy, security concerns
• AI should align with human values and principles

?? Potential of AI

• AI is integral for redesigning sustainable systems
• Predictive analytics, dynamic pricing, system redesign

In a nutshell:?

AI has the potential to significantly accelerate the transition to a circular economy by optimizing designs, business models, and infrastructure. However, while it offers vast opportunities, it's essential to address its limitations and ensure it aligns with human values.

?? ?? ?? Clean Energy?

How Artificial Intelligence is Driving the Renewable Energy Revolution

?? AI & Renewable Energy Revolution

• AI transforms the renewable energy sector
• Enhances solar, wind, and hydroenergy efficiency

?? Integration into Existing Systems

• AI optimizes renewable energy system performance
• Predicts wind patterns, adjusts wind turbine blades

?? Solar Energy Optimization

• Analyzes solar radiation data
• Adjusts solar panels for maximum energy capture

?? Energy Storage & Efficiency

• AI predicts energy demand and supply
• Optimizes energy storage systems and usage

?? Smart Building Systems

• AI optimizes heating, cooling, and lighting
• Monitors energy use for efficiency improvements

? Challenges & Limitations

• Data availability and quality concerns
• Need for specialized expertise in AI and renewables

?? Data Privacy & Cybersecurity

• Concerns over sensitive data collection
• Risk of cyberattacks on advanced systems

?? Collaboration is Key

• Industry professionals, policymakers, and academics unite
• Address challenges for AI's full potential in renewables

?? Conclusion & Future

• AI's benefits in renewables are significant
• Aims for a sustainable energy future, benefiting all

In a nutshell:?

AI is revolutionizing the renewable energy sector, optimizing energy production, storage, and efficiency. Despite challenges like data quality and cybersecurity, the potential benefits of AI in achieving a sustainable energy future are immense.

?? Plastic Pollution?

How AI is helping us become a plastic-free Earth

?? AI's role in a plastic-free Earth ??

• AI enhances waste management and recycling
• Designs sustainable, low-plastic packaging?
• Identifies new pollution sources & alternative materials?
• Robotic systems & drones for cleanup?

?? Innovative AI solutions against plastic pollution:

• Plastic Bank: AI tracks & monetizes recycling in developing nations?
• The Ocean Cleanup: AI-driven robots for oceanic cleanup?
• Loop: Reusable packaging delivery system?

?? Plastic's uncertain future:

• Plastic production rising alarmingly?
• Movement for sustainable alternatives grows
• AI can shape plastic pollution's future, offering innovative solutions?

?? What can you do?

• Minimize single-use plastics usage?
• Prioritize recycling & composting?
• Support eco-friendly businesses?
• Engage in community initiatives?

In a Nutshell:?

AI offers powerful tools to combat the global challenge of plastic pollution. From enhancing waste management to designing sustainable packaging and cleaning up existing pollution, AI-driven innovations are at the forefront of efforts to create a plastic-free Earth. Individual actions, combined with these technological advancements, can make a significant difference.

?? ?? Sustainable Business?

THE SECRET WEAPON FOR SUSTAINABLE BUSINESS? AI.

?? AI: The Future of Sustainable Business

• Companies use AI to understand the environmental footprint?
• One Vanderbilt: A green skyscraper in Manhattan?
• Data challenges: Turning sustainability data into actionable insights?

?? Complexity of Sustainability Data

• SL Green faces a 10x increase in environmental compliance data requests?
• 44% of CEOs can't translate sustainability data into actionable insights?
• AI operationalizes sustainability, making sense of vast data?

?? AI in Infrastructure: The Great Belt Link Case

• Climate change challenges the longevity of infrastructure?
• AI analyzes 12,000-14,000 data points for real-time health checks?
• The lifespan of the Great Belt Link was extended, saving 750,000 tons of carbon emissions?

?? SL Green's Vision for a Greener Future

• Goal: Carbon neutrality for buildings like One Vanderbilt?
• The transition from spreadsheets to IBM's Envizi for ESG metrics?
• ESG data investment is growing, with the potential for more?

In a nutshell:

AI is revolutionizing the way businesses approach sustainability, turning vast amounts of environmental data into actionable insights. This not only aids in meeting regulatory demands but also extends the lifespan of infrastructure, reducing carbon footprints and driving a more sustainable future.?

?? ?? ?? ?? ?? ?? ?? ?? ?? ?? Biodiversity

Mapping Species From Crowdsourced Data Using Machine Learning

?? Mapping Species with AI and crowdsourced Data

• Community platforms like iNaturalist provide millions of species photos?
• AI helps identify species, but visual similarities pose challenges?

?? Geographical Range Predictions Enhance Accuracy

• Location data helps determine species in an image?
• Combining image classifiers with location boosts accuracy from 75% to 82%?

?? Global Scale Species Range Estimation

• Models predict species' global ranges using crowdsourced data?
• Achieved 75-80% agreement with expert-derived ranges, but challenges remain?

?? Key Findings & Future Directions

• Compact models predict 47,000 species' ranges?
• More data & addressing biases will improve models?
• Conservation decisions need caution with current models?

?? Research & Further Info

• Paper: “Spatial Implicit Neural Representations for Global-Scale Species Mapping”?
• Presented at ICML 2023, details on arxiv.org?

In a nutshell:

Utilizing machine learning and crowdsourced data from platforms like iNaturalist, researchers have developed models to predict the geographical ranges of species. This enhances species identification accuracy in images. While promising, there are challenges to address, especially biases in data. The research aims to improve species conservation efforts globally.

?? ?? ??? Sustainable Lifestyle?

HOW CHARITIES ARE FIGHTING POVERTY WITH AI

?? AI's Role in Charities & Poverty Alleviation

• AI becoming accessible for small organizations
• Charities leveraging AI for fundraising and philanthropy

?? AI's Impact on Global Poverty

• AI helps identify and solve previously unsolvable issues
• Technology combined with education and resources can combat poverty

??? Tracking Poverty with AI

• Stanford researchers use AI & satellite imagery
• Predict poverty in African villages with 81%-99% accuracy

?? AI in Agriculture to Combat Poverty

• 65% of adults in poverty rely on agriculture
• FarmView uses AI to improve yields, focusing on drought-tolerant sorghum

?? Charities Adopting AI Techniques

• Targeted outreach to identify those most in need
• Virtual assistants, predictive modeling, fraud detection, and automation

?? AI's Potential for Charities

• AI chatbots streamline operations and answer queries
• Predictive analytics help plan for future challenges

In a nutshell:

AI is revolutionizing the way charities operate and address global poverty. By leveraging AI in areas like agriculture and targeted outreach, charities can more effectively combat poverty and enhance their operations.?

?? Research

Artificial-Intelligence-Supported Reduction of Employees’ Workload to Increase the Company’s Performance in Today’s VUCA Environment

?? AI in Today's VUCA Environment

• AI can boost company performance in volatile settings
• Focus: AI-supported HR aspects like training, leadership, and culture

?? Research Insights

• 317 medium & large Slovenian companies surveyed
• AI-supported culture, leadership, & training positively affect workload reduction

???? Employee Workload & Engagement

• Reduced workload by AI boosts employee engagement
• Engagement directly enhances company performance

?? AI's Broad Applications

• Enhances sectors like agriculture, healthcare, & tourism
• Optimizes sales, and customer service, & reduces costs

?? AI in Marketing & Logistics

• Deep analytics for customer behavior & preferences
• Improves storage, demand forecasting, & order planning

??AI's Future Role

• AI crucial for adaptive market strategies
• Reduces employee workload, increases engagement & performance

In a nutshell:

AI's integration into organizational culture, leadership, and training can significantly reduce employee workload, leading to increased engagement and enhanced company performance in today's unpredictable VUCA environment.?

* VUCA" stands for:

• Volatile: The nature and dynamics of change, and the speed and turbulence with which it happens.
• Uncertain: The lack of predictability and the prospects for surprise in the future.
• Complex: The multiple forces, confounding issues, and chaos that surround an organization or situation.
• Ambiguous: The haziness of reality and the potential for misreads of situations.

A "VUCA environment" refers to situations or contexts characterized by these four elements. It's a term that originated from the U.S. Army War College to describe the more volatile, uncertain, complex, and ambiguous world that emerged after the Cold War. In the business context, it's used to describe the challenging, fast-changing, and unpredictable nature of the modern business landscape.

?? ?? ?? ?? Remote Green Jobs

My GROUP:

?? https://www.dhirubhai.net/groups/12845122/?

Remote Green Jobs (Week 39):

1. Sustainability Analyst @Greenomy ( BRUSSELS · FULLY REMOTE)

?? https://lnkd.in/ergHBQqb

2. Senior Manager of Customer Success @Regrow AG (REMOTE - US)

?? https://lnkd.in/e_mRgj4k

3. Director of Innovation (Industry & Water) at Elemental Excelerator (Remote (Anywhere in the U.S.))

?? https://lnkd.in/e3xFjgsZ

4. Director of Innovation (Renewable Energy) at Elemental Excelerator (Remote (Anywhere in the U.S.))

?? https://lnkd.in/e9Pcb8Qh

5. Senior Investment Manager at Elemental Excelerator (Remote (Anywhere in the U.S.))

?? https://lnkd.in/e8jtYbTB

6. Senior Environmental Specialist @NextEra Energy (TX-ERCOT (remote)

?? https://lnkd.in/euZjuNqb

7. Sr Software Engineer - Energy Optimization @NextEra Energy (Remote)

?? https://lnkd.in/eaweKW2c

8. Climate Change Analyst @Governance & Accountability (G&A) Institute (New York, NY, USA. Fully remote working position)

?? https://lnkd.in/ecT8D6NZ

9. 2024/2025 Sustainability Reports Research Analyst Internship @Governance & Accountability (G&A) Institute (Virtual Location: Work is done remotely)

?? https://lnkd.in/egSb-SnG

10. ESG / Sustainability Corporate Consulting Analyst @Governance & Accountability (G&A) Institute (Remote, based in the U.S)

#greenjobs #remotejobs #climatejobs

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