How AI Can Address Global Challenges

How AI Is Making a Real Difference (The real power of AI isn’t efficiency - it’s impact.) AI often gets framed as a shortcut for productivity - but its real potential goes far beyond that. It’s helping solve some of the world’s most pressing challenges. Here are 5 ways AI is creating meaningful change: 1. Healthcare: Diagnosing Earlier, Treating Smarter ↳ AI is transforming early detection. ↳ McKinsey estimates AI tools could cut medical errors by up to 40% and boost treatment outcomes by up to 30%. ↳ Google’s DeepMind can now identify more than 50 eye conditions with the accuracy of top specialists—helping prevent blindness through faster diagnosis. 2. Climate Action: Forecasting Disasters Before They Happen ↳ AI is improving how we predict and respond to extreme weather. ↳ According to the World Economic Forum, AI-enhanced climate models are 40% better at forecasting major events. ↳ IBM’s Geospatial AI is already in use to anticipate floods and wildfires weeks in advance - giving communities time to prepare. 3. Education: Adapting to Every Learner ↳ AI makes personalized education scalable. ↳ UNESCO found AI tools can increase student retention by 30% by adapting lessons to individual learning patterns. ↳ Duolingo, used by over 500 million people, tailors language lessons in real time to make learning more effective for each user. 4. Disaster Relief: Acting Before Crises Escalate ↳ AI helps aid organizations get ahead of emergencies. ↳ The UN’s World Food Programme used AI to forecast a 70% rise in food insecurity in East Africa - enabling earlier, targeted intervention. ↳ With access to satellite imagery and trend data, AI guides relief efforts before situations become critical. 5. Sustainability: Cutting Waste and Emissions ↳ AI is also driving environmental gains. ↳ BCG reports that AI-enabled supply chains help grocers reduce food waste by 20–50%. ↳ Companies like Winnow use AI in kitchens to monitor waste and save millions of meals from ending up in the trash. AI isn’t just a tool for business - it’s a tool for progress. And the more it evolves, the more ways we find to apply it for good. Is your organization using AI to make a positive impact? __________________________ AI Consultant, Course Creator & Keynote Speaker   Follow Ashley Gross for more about AI

Since 2000, the number of humans worldwide without access to electricity has dropped by half -- nearly 1 billion more people have electricity today. Several factors contributed to this improvement, but a key driver is technology. Rapid technology development has transformed energy systems over the last two decades. And today, AI is poised to accelerate this trend in unprecedented ways. Recent insights from Reuters highlight several uses of AI to advance and improve our power systems. Let's take mini-grids as an example. Mini-grids (similar to micro-grids) harness local storage and generation, creating decentralized networks that empower communities, particularly rural ones. Imagine a small community in the mountains installing solar panels and batteries, forming a local energy generation and storage facility to power their needs. This shift from centralized authorities to local innovators accelerates electrification, sidestepping the prolonged process of waiting for regulatory approvals and building new power plants. A key challenge micro-grids face is managing supply & demand for users. But now, predictive AI is enabling innovators like Husk Power Systems to forecast supply and demand, delivering electricity at the cheapest point at any given time. Similarly, installing and managing generation assets can be a challenge especially in rural environments. Here, AI-based models can optimize site selection & improve predictive maintenance for wind turbines and solar panels. By making mini-grids more efficient, AI is accelerating rural electrification -- just one example of how such technologies can enable cheaper, cleaner, and more reliable power for millions around the world. 🌍 #AI #aiforgood #energysystems #sustainability #minigrids #microgrids #cleanenergy #energytransition #cleantech #climatetech

AI holds incredible promise and potential, but something I find especially inspiring is how it can help us solve some of the biggest environmental challenges we face today, such as the global wildfires.    In Canada, Microsoft is working with the Government of Alberta and AltaML on a new AI tool which leverages machine learning to predict the risk of new wildfires by region and even by hour. Capable of analyzing tens of thousands of data points, it provides insights that help firefighting agencies plan ahead, allocate resources efficiently, and prevent fires from spreading out of control – and it’s showing great promise for other wildfire-prone regions around the world.     Learn more here: https://aka.ms/AAmlsim 

Energy is the key. Over the weekend I got a lot of messages about articles and stories talking about the links between the energy hungry AI models and the path to net zero. On one hand, the computational power required to train and run AI models is soaring, placing increasing demands on our energy grids. On the other, AI itself holds remarkable potential to drive innovations in climate technology, potentially aiding our quest for net zero emissions. This dichotomy presents both a formidable challenge and a beacon of hope in our journey toward a sustainable future. Advanced AI models, particularly those involved in machine learning and deep learning, require substantial computational resources. Training a single AI model can consume as much electricity as several hundred homes use in a month. As AI becomes more integrated into our daily lives, from autonomous vehicles to personalized medicine, the demand on energy grids will inevitably rise. This surge complicates our path to achieving net zero emissions, as increased energy demand generally translates to higher carbon footprints unless met entirely by renewable sources. However, the same technology that poses such a challenge also harbors solutions to some of the most pressing environmental issues. AI can optimize energy consumption in industries and homes, create more efficient renewable energy systems, and improve waste management practices. For example, AI algorithms can predict energy demand more accurately, enabling smarter grid management and reducing reliance on fossil fuel-powered peaker plants. In renewable energy, AI can enhance the efficiency of solar panels and wind turbines by optimizing their placement and operation based on weather predictions. Moreover, AI-driven innovations in materials science are paving the way for more efficient batteries and renewable energy storage solutions, addressing one of the significant hurdles in the transition to green energy. AI also plays a crucial role in monitoring and combating climate change. Through the analysis of satellite imagery and environmental data, AI can track deforestation, ocean health, and the melting of polar ice caps with unprecedented precision and speed. This capability not only informs better policy and conservation efforts but also helps in quantifying the impact of climate action, making it a potent tool in the global effort to mitigate climate change. The dual role of AI as both a contributor to and a solver of the energy and climate crises underscores the need for a balanced approach in its development and deployment. By prioritizing energy-efficient AI models and leveraging AI to accelerate the transition to renewable energy, we can harness the power of AI to move closer to our net zero goals, turning a formidable challenge into a formidable ally in the fight against climate change. At Nadia Partners we are building companies on both sides to help achieve both goals. Anybody who can help us please tag or share!

In the early days of COVID-19, we published a review in The Lancet on the transformative potential of #artificialintelligence in #globalhealth. We also raised some challenges, including ethical, regulatory, data privacy, and algorithmic bias. Fast forward to 2024 - incredible strides and new concerns.   AI holds promise in addressing global health challenges, from tuberculosis diagnosis in India to optimizing immunization programs in Mali. However, the enthusiasm for these tools must be informed by lessons from past experiences that inadvertently exacerbated inequities.   Community participation and integration into existing health systems should be at the forefront, ensuring AI's benefits reach all populations.From research to deployment and evaluation, global health demands end-to-end guidance and a cohesive framework. AI's evolution, including tools like ChatGPT, brings forth challenges, especially in reinforcing hidden biases from training data. Access to critical datasets, especially in the global South, remains a barrier. Newly released guidance by the World Health Organization offers a significant and welcome step forward in the development of standards and reporting guidelines like TRIPOD-ML, SPIRIT-AI, STARD-AI, and CONSORT-AI, a foundation for harmonizing AI terminologies. There is also room to double down on implementation-related issues and adherence to the Principles for Digital Development, including early engagement from end users.   Silicon Valley's "move fast and break things" ethos doesn't align with the nuanced landscape of global health and can be harmful. Let's build guardrails to harness AI's power responsibly.   Read more in my paper with Brian W.. #johnshopkinsuniversity #columbiauniversity   https://lnkd.in/eDnK5M9n

AI runs on data centers. But as we scale AI, we face a growing dilemma: heat. Data centers are the backbone of artificial intelligence, but they are also incredibly energy-intensive. As the Scientific American article puts it, “extreme heat is emerging as a major threat to AI infrastructure,” particularly as climate change drives more frequent and severe heat waves across the globe. Cooling these facilities is no small feat. Many data centers rely on enormous volumes of water and electricity to keep hardware from overheating. In some regions, this demand is colliding with already strained local resources—and raising urgent questions about long-term viability. If we want AI to scale responsibly and equitably, we must make sustainability a design principle—not an afterthought. Innovative solutions such as advanced liquid cooling, shared or co-located infrastructure, centralized processing, and renewable energy integration are all part of the puzzle. So is policy. So is collaboration. By investing in smarter infrastructure today, we can build AI systems that serve people and the planet, systems designed not just for speed, but for stewardship. What ideas or solutions are you seeing for a more sustainable AI future? #AI #DataCenters #Sustainability #AIForGood #AIEthics #ClimateTech

2014: Global AI market is valued at $419.7 million 2024: Global AI market is valued at $305.90 billion with a B That’s a 72,000% increase in the last decade. It’s pretty clear at this point that AI can’t be ignored. But the real question for me is: How can AI be leveraged to positively impact environmental sustainability? Because AI has the potential to revolutionise how we approach sustainability issues. Whether it be through the: - Waste reduction. - Wastewater treatment. - Identification of patterns. - Using materials precisely. - Analysis of large data sets. - Creation of efficient supply chains. - Creation of forecasts and predictions. - Design of long-lasting product life cycles. - Comparison & identification of the best options. The advantages are endless. Here are a few critical areas I’m excited about AI impacting: 1️⃣ Renewables - Shifting from fossil fuels to renewables cuts greenhouse gas emissions. - AI optimizes energy use through forecasting, smart grids, and resource allocation. - It's also key in energy exploration, storage, and trading. 2️⃣ Agriculture - AI can enhance farming viability using sensors for soil and water data, combined with weather insights. - Improves farm management with AI-driven cost optimization, yield predictions, and waste reduction. - Also aiding in reshaping production to reduce the environmental impact of food production. Those are my thoughts, but what are yours? Where would you like to see AI drive sustainable solutions?

In 2024, can AI contribute to resolving environmental issues in the fashion industry? Happy New Year, everyone! In my latest collaboration with Kevin Shahbazi and the incredible team at Board of Innovation, we delve into this pressing question. Last month, Board of Innovation hosted the Autonomous Innovation Summit, where Sylwia Szymczyk and I explored various areas within the fashion industry where AI could offer solutions. As we kick off the new year, I find it fitting to take a closer look at how GenAI could play a pivotal role in making fashion more environmentally and socially sustainable. Here's what you'll discover in our article: 1) Optimizing Supply Chains with AI: Explore how AI can analyze all factors involved in bringing a product to market. Sourcing goes beyond material and production costs; it's about fine-tuning every aspect of the supply chain. 2) Making Sustainable Raw Material Choices: Learn how AI can guide us in making the right raw material choices that are best for the planet while keeping our supply chain efficient. 3) AI's Role in Managing Overproduction: Discover how AI can help manage overproduction while enhancing our ability to respond to demand effectively. I hope you enjoy reading this article. As always, please share your thoughts in the comments. Certain parts of this conversation might be controversial; discussing topics such as water use, hemp, and cotton inevitably raises some eyebrows, and that's perfectly fine. We shouldn't shy away from tough conversations, but let's aim for positive and constructive comments. After all, we're collectively working towards solving these problems, and I appreciate your perspective. (For your information, I'm no longer with VF Corp. This article was written before I left the company. I'm currently available and eager to embark on my next challenge.) Read the full article here: https://lnkd.in/gUeAvhrp #GenAi #fashion #sustainability #dpc #3dfashion #boardofinnovation #2024goals #ai

As we combat climate change more urgently than ever, Artificial Intelligence (AI) could be a potential ally - particularly through its capabilities in predictive analytics and smart, automated systems. AI's prowess in analyzing vast datasets enables precise forecasting of climate phenomena, that can guide timely interventions to mitigate adverse effects. This predictive power extends to optimizing energy and resource use, where AI-driven systems ensure operations across various sectors are both efficient and sustainable, significantly reducing waste and enhancing resilience. Moreover, these intelligent systems, if harnessed well, can contribute to health and well-being by monitoring and improving environmental conditions, from air quality to water usage - ensuring a healthier living environment for all. By smartly allocating resources and predicting environmental challenges, AI can potentially not only help conserve the planet's vital resources but also fortify communities against climate-related disruptions, paving the way for a sustainable, resilient future. However, with such great power comes great responsibility. A recent report by Boston Consulting Group (BCG), commissioned by and co-authored with Google, delves into AI's ability to revolutionize climate action, potentially reducing global emissions by 5% to 10% by 2030. Here’s the link to the report: https://lnkd.in/gH6j-_XY   The question I am beginning to reflect on and would seek your inputs as well is, “How can we leverage AI for equitable solutions that foster global cooperation?” For me, it’s really important that our efforts champion climate equity that respects and empowers all communities, particularly those most vulnerable to climate impacts. Responsible AI development plays a crucial role here, ensuring inclusivity and avoiding biases.   I am actively looking to build a blueprint for harnessing AI as a tool for inclusive climate action. A future where responsible technology and sustainability go hand in hand, benefiting everyone, everywhere.   What innovative approaches do you think can bridge the gap between technological advancements, climate resilience, sustainability, and equity principles guided by responsible AI development? The comment section awaits!   #AIForGood #ClimateAction #SustainableFuture #InclusiveInnovation Note: Keeping with the theme of AI, I asked Adobe Firefly to help me generate an image that speaks of the impact of AI in climate action, and this is the resulting image.

ARC Strategy Report: AI, Energy Transition, and Industrial Sustainability. Industrial organizations that have already begun leveraging AI are seeing transformational improvements, not simply in operational use cases from a systems viewpoint but also from a People and Process perspective, across internal cultures and external ecosystems. AI is becoming central to how industrial companies can address and react to a host of disruptive market conditions. Foremost among these is the issue of energy transition and industrial sustainability (ETIS), consistently cited by industrial executives as one of their top two business challenges. To improve, decision-makers need a strategic approach to understand the value of AI in meeting ETIS challenges, particularly from an operational perspective. This ARC Strategy Report builds upon ETIS-specific use cases identified in ARC's Industrial AI Impact Assessment Model. This model offers a structured approach to assessing and planning for AI impacts in product design, supply chain, production, sales and service, and workforce management. Looking at the desirability of such transformation, it is important for leaders to recognize the role AI can play to achieve ETIS transitional improvement and, more importantly, transformational changes. ARC Advisory Group clients can view the complete report at the ARC Client Portal. Please Contact Peter Manos if you would like to speak with the author about ETIS topics. Or contact Colin Masson about Industrial AI and Industrial Data Fabrics for broader use cases. https://lnkd.in/gJtDaB9H #ETIS #Sustainability #EnergyTransition #ESG #AI #Industrial AI #IndustrialDataFabric