France Reaffirms Its Commitment to the SDGs in the Context of the HLPF
Ambassador Nicolas de Rivière
The Covid-19 crisis has illustrated in a most dramatic fashion the insufficient resilience of our societies. With its far-reaching impact, affecting the three dimensions of sustainable development, this pandemic exacerbates vulnerabilities and threatens our collective pledge to leave no one behind. It shows there is still a long way ahead for the realization of the 2030 Agenda for Sustainable Development.
For the first time since 2015 and the adoption of the Agenda, we are experiencing serious setbacks in its implementation. The pandemic has pushed more than 120 million people worldwide into extreme poverty; it has worsened food insecurity and widened pre-existing inequalities of all kinds at the expense of our most fragile populations. Forced school closures have also had a devastating impact on 1.5 billion children’s education and well-being, while diverse lockdown measures have seen growing unpunished violence towards women and girls.
The High Level Political Forum on Sustainable Development (HLPF) of the United Nations, which took place from 6 to 15 July 2021, and in which France participated actively, enabled Member States and various stakeholders to discuss the ways to ensure a sustainable and resilient recovery from Covid-19, putting us on track to realize the 2030 Agenda.
In order to achieve the Sustainable Development Goals (SDGs) by 2030, we first need to address this crisis with a sense of urgency.
- To put an end to this pandemic, the only reliable solution at our disposal is to ensure universal access to vaccines. The Access to Covid-19 Tools Accelerator (ACT-A), and more specifically its vaccines pillar, the Covax facility, are key to realizing this goal. Out of 3.2 billion jabs administered worldwide, only 60 million have gone to people in Africa. Tangible action is needed: as announced at the G7 Summit in Carbis Bay last month, France will double its original commitment and deliver 60 million doses by the end of the year.
- The Covid-19 crisis is not only a health crisis, but also a socio-economic one. As a result, numerous countries have experienced severe public debt distress. As early as May 2020, the G20 and the Paris Club agreed upon the Debt Service Suspension Initiative (DSSI), enabling more than 70 countries to regain budgetary flexibility and engage in more substantive emergency recovery plans. In order to answer any forthcoming issue about debt sustainability, they also adopted the Common Framework for Debt Treatments beyond the DSSI, which enables creditor countries, in the Paris Club and beyond, to coordinate and cooperate on debt treatments for low-income countries.
As we enter the Decade of Action to deliver the SDGs, the clock is ticking, and States should not use the unprecedented acuteness of the pandemic to shirk their responsibilities. Even before the Covid-19 outbreak, our development trajectories were structurally incompatible with the achievement of the SDGs. We should therefore use this pandemic as an opportunity to put ourselves back on track, with more resilient, just, and sustainable trajectories.
One of our major issues to do so is to address the SDGs’ financing deficit:
- France urges all countries to respect their Official Development Aid (ODA) commitments. Through a new programming bill on inclusive development and combating global inequalities, currently being adopted in France's Parliament, France is strengthening the means and tools of its development policy. This bill targets a growing trajectory for ODA, reaching 0.55% of France’s Gross National Income (GNI) by 2022 and a final aim of 0.7%. It sets clear objectives to concentrate aid in the form of grants to the benefit of the most vulnerable countries.
- Building back better after the Covid-19 crisis requires mobilizing all sources of financing. One of the messages put forth in the Paris Summit on Financing African Economies in May is that reinforcing internal public resources and fighting against illegal financial flows are paramount to adequate funding for sustainable development.
- Furthermore, the private sector should also contribute, and clear standards ought to be set to avoid SDG-washing. The Framework for SDG Aligned Finance launched by the OECD and UNDP answers this urgent need, and we should now work towards its operationalization.
More than ever, the 2030 Agenda must remain our collective roadmap:
- The integrated and crosscutting nature of the 2030 Agenda guides our action. Global public goods are deeply interrelated, and we need to consider them in a comprehensive way if we want to prevent future crises from happening. A good example of that is the Prezode Initiative, an innovative international endeavour that draws on multiple areas of knowledge with the ambition of understanding and assessing the risks of emergence of zoonotic infectious diseases.
- The 2030 Agenda is based on multilateralism: issues related to global public goods do not have any borders. They thus require a coordinated approach at a global level. France will continue to take its full part in the fight against global inequalities and in the protection of global public goods.
These messages are, among others, the ones that France has conveyed throughout the High Level Political Forum on Sustainable Development 2021. France played an active role in most of the sessions of the Forum, which were rich in recommendations, best practices, and knowledge-sharing. The French Mission to the UN also organized, on the side lines of the Forum, a high-level side-event on the role of partnerships between Governments and civil society to build policies and responses for a sustainable, inclusive, and resilient recovery from Covid-19 and for the achievement of the 2030 Agenda. Finally, we co-sponsored several side-events to the HLPF on various themes, all related to the SDGs (such as public health and climate, circular economy, One Health approach for human, animal and environmental health and pollution prevention, agroecology, and food security, etc.). As we move through this Decade of Action, France will continue to work in a multilateral spirit towards the realization of the 2030 Agenda and the Paris Agreement.
Photo: Dikaseva on Unsplash
About the Author:
Ambassador Nicolas de Rivière
Permanent Representative of France to the United Nations
Read perspectives from the ISSP blog
Elizabeth Dinschel, MA, MBA, is the Executive Director of ISSP Earlier this month, we hosted our first global ISSP Town Hall since I stepped into the role of Executive Director. I logged off that call energized, humbled, and deeply grateful for the honesty, generosity, and care that our members brought into the space. This Town Hall was never meant to be a one-way update. It was designed as a listening session — a chance for ISSP leadership and staff to hear directly from sustainability professionals across regions, sectors, and career stages. And you delivered. What follows are a few reflections on what I heard, what we learned, and where we’re headed next together. Why We Called This Town Hall ISSP has gone through a period of transition — new leadership, new staff, and a renewed focus on modernizing how we serve a truly global membership. Change can be energizing, but it can also create moments of uncertainty and disconnection. We knew we needed to pause, gather our community, and listen with intention. The Town Hall brought together members from multiple continents, industries, and disciplines. Sustainability practitioners, consultants, engineers, communicators, policy professionals, and career-transitioners all showed up with thoughtful questions and candid feedback. One thing was immediately clear: this community cares deeply about its work, about each other, and about ISSP’s role in supporting sustainability professionals at a challenging moment for the field.
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Nicole Cacal, MSc, is Executive Director of the TRUE Initiative in Hawaii and serves as Vice President on the Governing Board of ISSP. In our October blog, she challenges the prevailing narrative around AI's environmental impact, arguing that strategic deployment can transform AI from an environmental burden into a driver of recursive sustainability. Drawing on her background in strategic design and technology management, she presents emerging pathways for responsible AI adoption that balance societal benefit against environmental risk. Toward Appropriate and Responsible AI: Pathways to Sustainable Adoption and Infrastructure Nicole Cacal · October 27, 2025 Whenever I give an AI presentation or offer advice on AI adoption, whether to business owners, C-level executives, or sustainability professionals, one concern surfaces time and time again, especially here in Hawaii: the environmental tension. People want to explore AI's potential, but they're acutely aware of the energy consumption, the water usage, the carbon footprint. It's become almost a reflex: mention AI, and someone immediately raises the environmental cost. I get it. The data centers, the training runs, and the resource demands. They're real and they're significant. But here's what I've come to believe: if we shift the narrative from focusing solely on AI's detriment to the environment and instead ask how much good it can create, what role we can play in driving data centers to go greener, and how we can generate recursive sustainability, we unlock better questions. We start thinking forward rather than just defensively. As sustainability professionals, our job isn't to reject technology wholesale. It's to shape its evolution. And right now, we have an opportunity to influence how AI develops and deploys in ways that align with planetary boundaries and social equity. But to do that, we need to move beyond binary thinking. Right-Sizing AI: Why Bigger Isn't Always Better One of the most overlooked levers we have for sustainable AI is also one of the simplest: choosing the right model for the job. The AI industry has been caught in a "bigger is better" arms race for years now. Every new model release touts more parameters, more capabilities, more everything. And sure, these massive general-purpose models are impressive. But they've created a dangerous assumption: that every task requires maximum firepower. This is where my strategic design training from Parsons kicks in. Good design isn't about having the biggest toolkit. It's about matching the tool to the task. It's about elegance through constraint. The same principle applies to AI deployment. The emerging concept of "Small is Sufficient " is gaining traction for good reason. Research shows that selecting smaller, purpose-fit AI models for specific tasks can achieve nearly the same accuracy as their larger counterparts while reducing global energy demand by up to 28% . Twenty-eight percent. That's not marginal; that's transformational. Think about what your organization actually needs. Are you processing customer service inquiries? Analyzing spreadsheet data? Generating product descriptions? Most of these tasks don't require a frontier model. A fine-tuned, task-specific model will do the job with a fraction of the computational overhead. The shift we need is cultural as much as technical. We need to move from asking "what's the most powerful AI we can deploy?" to "what's the most appropriate AI for this specific use case?" That question changes everything, from procurement decisions to vendor relationships, internal training, and infrastructure planning. AI as Infrastructure Manager: The Self-Optimizing Data Center Here's an irony that doesn't get enough attention: AI might be energy-intensive, but it's also one of our best tools for managing energy systems efficiently. When we only think of AI as a consumer of data center resources, we miss part of the story. AI can also be the conductor of efficiency, orchestrating complex systems in real-time to minimize waste and maximize renewable integration. Consider three optimization domains where AI is already making measurable impact: Cooling systems: Data centers generate enormous heat, and cooling accounts for a massive portion of their energy use. AI can continuously adjust cooling based on workload patterns, outside temperature, humidity, and dozens of other variables, optimizing in ways that static systems simply can't match. Workload scheduling: Not all computing tasks need to happen immediately. AI can intelligently schedule batch processing, model training, and background tasks for times when renewable energy is abundant or when grid demand is lowest. This isn't just theory. Companies are already doing this. Renewable energy integration: This one hits close to home in Hawaii, where we're working toward aggressive renewable energy targets but face unique challenges with grid stability and storage. AI-managed facilities can modulate demand in response to solar and wind availability, essentially turning data centers into flexible grid assets rather than inflexible burdens. When organizations approach their operations as integrated systems rather than collections of independent components, they achieve results that surprise even them. AI-orchestrated data centers represent this systems thinking at its most sophisticated. The technology optimizes itself recursively, reducing the footprint of AI through AI. That's the kind of elegant solution we should be scaling. Measuring What Matters: Beyond Energy to Net Benefit But here's the challenge: if we only measure AI's direct energy consumption, we miss the full picture. We need frameworks that capture both the operational cost and the systemic benefit. This is where life cycle assessment combined with comparative modeling becomes essential. We need to ask: compared to what? And over what timeframe? The sectoral success stories are compelling when you run the numbers: Building automation systems powered by AI are consistently achieving energy savings in the range of 20-30% across diverse building types. One documented case study of a commercial office building in the United States showed a 32% reduction in overall energy consumption with a 2.4-year return on investment (a $2.1 million system investment generating $875,000 in annual savings). In Stockholm, the SISAB school building portfolio achieved similar results with a two-year payback period. In precision agriculture, AI-driven irrigation and fertilizer application systems are cutting water consumption by 20% to as much as 50% and reducing chemical runoff, addressing both resource scarcity and ecosystem health. Waste management optimization is another powerful example. AI-powered sorting systems in recycling facilities dramatically improve material recovery rates while reducing contamination. The resource efficiency gains far exceed the AI system's energy footprint. These aren't marginal improvements. When properly deployed, targeted AI applications produce emissions savings and resource efficiencies that dwarf their own operational costs. That being said, given today's fossil fueled data center expansions, we may find that we have much further to go in making the environmental positives outweigh the negatives. But that's no reason to throw in the towel or to assume that these technologies cannot - over time - deliver more environmental benefits than downsides. It requires companies to demand more of their technology providers and deploy their systems sustainably when greener options become available. But (and this is crucial) these benefits only materialize when we pair the right AI with the right infrastructure and the right deployment strategy. Which brings us to governance. The Path Forward: Governance, Transparency, and Adaptive Thinking The sustainability community, including organizations like ISSP, is actively developing shared frameworks for assessing AI's net impact. These emerging approaches include system-level energy auditing, selective task deployment protocols, and strategies for minimizing "dark data" (the vast amounts of stored data that's never used but still requires energy to maintain). Multi-stakeholder governance initiatives are bringing together technologists, policymakers, environmental scientists, and business leaders to create adaptive standards. 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We need to apply these tools to AI with the same rigor we've applied to supply chains, built environments, and industrial processes. So here's my invitation: What are you seeing in your sector? How is your organization approaching the AI sustainability question? Are you finding innovative ways to ensure deployment is appropriate and responsible? Because ultimately, appropriate AI isn't about choosing between progress and sustainability. It's about insisting that progress is sustainable. It's about right-sizing models, optimizing infrastructure, measuring net benefit, and building governance systems worthy of the challenge. The technology itself is neutral. Our choices determine whether AI becomes a driver of sustainability or another extractive burden. Let's choose wisely.