As someone immersed in the intersection of data access and social impact, I’ve seen firsthand how AI is reshaping conversations around data governance and sovereignty.
For organisations working to improve social outcomes—be it governments, non-profits, or community backbone groups, including First Nations organisations—the rise of AI brings both transformative potential and pressing challenges.
AI’s power lies in its ability to analyse vast, complex datasets and generate insights that were previously out of reach. However, this capability demands clear governance frameworks to protect privacy, uphold ethical standards, and preserve the autonomy of communities whose data is being utilised. When data represents not just numbers, but the lives and aspirations of communities, governance must go beyond compliance to centre on equity and cultural respect.
Data Sovereignty, especially in the context of First Nations organisations, isn’t merely a data rights and access issue; it’s about self-determination. Indigenous data should be governed in alignment with the values, protocols, and priorities of First Nations communities. The growing prevalence of AI complicates this, as algorithms trained without cultural context risk marginalising voices or perpetuating biases. To ensure ethical outcomes, AI initiatives must respect First Nations Data Sovereignty, incorporating traditional knowledge and recognising communal rights.
For governments and not-for-profits, robust data governance is essential to gaining and maintaining community trust and delivering social impact. The implications of flawed AI models or inadequate oversight can be serious, potentially perpetuating inequities in resource allocation or service delivery. AI must be accountable to the public and designed with the community’s needs and aspirations in mind.
Our role in the social impact space is to advocate for community-led data governance practices that prioritise transparency, cultural respect, and collaboration. The path forward requires a collective effort to balance AI innovation with rights-based approaches to data—ensuring that technology serves communities.
Seer Data’s technology enables flexible and proven data governance for operationalising different models for the community and the public sector. There are new regulations all organisations need to be across when considering data governance for AI.
Here’s a summary of what you need to know.
Australia’s AI Regulation Landscape
Australia’s AI regulatory landscape is evolving rapidly, focusing on creating safeguards that protect public interests while supporting innovation. In 2024, the government issued an “Interim Response” outlining a risk-based framework that targets high-risk AI applications—those impacting areas like human rights and public safety. For such applications, mandatory guidelines around testing, transparency, and accountability. For lower-risk AI uses, voluntary guidelines will allow companies more flexibility.
These proposals are designed to integrate AI-related considerations with the government’s ongoing regulatory reforms across multiple areas. Key updates include Privacy Act amendments, a review of the 2021 Online Safety Act with new provisions to address misinformation, and enhanced transparency and accountability for automated decision-making, inspired by findings from the Robodebt Royal Commission. While the interim response doesn’t specify the current status of these reviews, any changes will reflect feedback from last year’s consultations. Notably, the temporary expert advisory body’s role does not currently extend to revising existing laws.
Australia is closely observing regulatory developments in Europe, where the EU’s comprehensive AI Act is a focal point, alongside individual national approaches, especially in the UK.
EU AI Act: The European Union has introduced new legislation on artificial intelligence: The EU AI Act. It lays the foundations for the regulation of AI in the EU.The EU’s AI Act introduces a risk-based regulatory framework. It defines “high-risk” and “prohibited” AI applications, emphasizing transparency, accountability, and human oversight for AI systems that could impact safety or fundamental rights. The Act also mandates labeling for generative AI content, including disclosure for deep fakes and other AI-altered media
UK Approach: The UK has opted for a principles-based, sector-agnostic framework that encourages innovation while managing risks. Rather than a single AI regulatory body, existing regulators (e.g., the Information Commissioner’s Office and the Financial Conduct Authority) are tasked with interpreting five core AI principles relevant to their domains. The UK government will monitor this framework, possibly introducing specific AI laws in the future if risks associated with general-purpose AI (GPAI) require further action
Global Cooperation and Divergence: While there is ongoing international cooperation—such as the Bletchley Declaration signed by the EU, UK, US, and others, which promotes responsible AI use—significant divergence remains. The EU and UK, for instance, differ on regulatory stringency, with the EU enacting comprehensive legislation, while the UK takes a more adaptable approach. This divergence may impact businesses operating across borders, as compliance needs vary based on jurisdiction
These regulations aim to balance innovation with public safety, privacy, and transparency, with both the EU and the UK seeking to establish frameworks that address AI’s evolving risks without stifling growth.
As AI month draws to a close, we reiterate that Seer Data is proud to contribute to the growing AI landscape in Australia, helping users work smarter and more efficiently with cutting-edge technology.
Kristi Mansfield, Founder and CEO
