The panel brought together academic, industry and policy leaders to discuss how AI can support climate goals, financial inclusion and infrastructure development – particularly in underserved regions. But perhaps the strongest message was this: the computing community must now take ethical leadership as seriously as technical innovation.
In an exclusive interview with Computer Weekly, ACM president Yannis Ioannidis, who participated in the panel, explained why this moment marks a turning point for the computing profession’s engagement in global development – and what must happen next. “Historically, ACM hasn’t fully acknowledged the profound impact computing professionals can have on global development,” he said. “But our mindset has shifted – we now want to engage more meaningfully.”
AI has become ubiquitous in corporate strategy, scientific discovery and public infrastructure, but as Ioannidis emphasised, its benefits have not been evenly distributed – and without careful governance, AI could deepen existing inequities.
“Our central message is that technological advancement does not guarantee fair use,” he told Computer Weekly. “AI often inspires either fear or unrealistic optimism. In truth, it can do immense good – but only if we ensure it serves everyone, not just the privileged.”
That means prioritising the underserved when investing in AI. According to Ioannidis, affluent countries deploying AI in lower-income regions must do so based on the needs of those communities, not their own assumptions. It’s not just a question of access to technology, but of relevance and respect. “We’re advocating for investments in AI that prioritise underserved populations,” he said. “This is only the beginning.”
The conversation around AI in sustainable finance is often high-level and speculative. But Ioannidis shared examples that ground the conversation in real-world gaps. One team he worked with found that 87% of climate scientists lack the skills needed to apply AI effectively. For sustainable development goals (SDGs) to be achieved, this skills gap must be addressed first. “If people don’t have the training to use AI, the funding will be misdirected,” he said. “The first investment must be in human capital.”
ESG metrics
Another example lies in the application of AI to environmental, social and governance (ESG) metrics. With the right tools, companies and governments can use AI to assess sustainability performance and hold themselves accountable. “AI, if applied thoughtfully, can help us become genuinely greener and more accountable,” said Ioannidis.
One major theme of the ACM-led panel was governance – not just of AI itself, but of its uses in high-stakes domains like poverty alleviation, infrastructure investment and climate finance. “Governance must remain in public hands,” he said. “While industry has driven many AI innovations, governments must regulate its use to ensure ethical deployment.”
Ioannidis cautioned that ethical AI is not just about eliminating data bias or tweaking algorithms. It also involves engagement between technologists and policymakers, which has been lacking.
“We often get absorbed in our innovations and forget the real-world implications,” he said. “But we can’t afford that anymore. Technology policy must be a collaborative effort.”
Ioannidis urged fellow technologists to “rub shoulders with policymakers” to ensure AI is aligned with societal priorities. The pace of innovation will always outstrip the pace of regulation – but deliberate cooperation can narrow the gap.
Building smart finance with inclusive technology
A particularly urgent focus of the FFD4 session was the deployment of digital infrastructure in underserved regions – areas where the promises of AI risk being offset by energy costs, skills gaps and top-down interventions.
“Most AI development today serves high-level cognitive goals,” said Ioannidis. “That’s fine, but it doesn’t help people struggling with food, water or shelter.”
For AI to serve the Global South, technologists must address basic needs first – such as improving crop yields, reducing food waste or designing better housing. These are not glamorous use cases, but they’re essential. Another challenge is energy consumption. AI systems are notoriously resource-intensive, and deploying them in low-income regions without sustainable power sources can cause more harm than good.
“We need to develop and deploy energy-efficient AI, powered by renewables where possible,” said Ioannidis. “Until we’re truly carbon neutral, we must tread carefully.”
AI inclusion isn’t just about technology access. It’s also about cultural awareness and humility. He warned against a “colonial” mindset, where developers from wealthier nations impose solutions on communities they don’t understand. “Before introducing AI to a farming community, for example, you must understand their needs,” said Ioannidis. “You can’t start with the technology. You have to start with listening.”
He called for a model based on collaborative discovery, where technologists learn from local communities before offering tools that may be helpful. If the community doesn’t see value in a product, it won’t be adopted – no matter how sophisticated the underlying AI.
With traditional development finance models under stress, panelists and speakers at FFD4 agreed it’s time to reimagine global finance – and that AI has a central role to play. “Just as the crane and the car enhanced our physical capabilities, AI augments our cognitive capacity,” said Ioannidis. “The existing financial architecture has reached its limits. We need new models, and AI gives us the tools to build them.”
But this transformation won’t be automatic. It will require deep collaboration between technologists, policymakers and financiers – three groups that often operate in silos. “Each of these groups tends to assume their own perspective is sufficient,” he said. “That has to change.”
According to Ioannidis, computing professionals must take the first step. “The others won’t necessarily come to us, so we must initiate collaboration,” he said. “AI offers a rare opportunity to reimagine systems from the ground up – including financial ones.”
The FFD4 panel demonstrated that there is both enthusiasm and urgency to apply AI to sustainable development – but also that the road ahead is full of risks. If deployed blindly, AI could reinforce inequality and environmental degradation. If developed inclusively, it could drive a fairer, greener financial future.
The ACM’s presence at the event – along with Ioannidis’s call to action – signals a meaningful pivot for the computing profession. “This is only the beginning,” he told Computer Weekly. “We’re taking responsibility, and we’re stepping up.”
