AI for our Oceans of Tomorrow: Data, Models and Governance
Abstract
The session examined how artificial intelligence can accelerate the Indian “blue economy” – the sustainable use of ocean resources. Cmd. Dr. Srivastava outlined India’s Deep Ocean Mission, the growing data infrastructure, and the need for AI‑driven models and data‑governance. Ambassador Stenner highlighted Norway‑India collaboration, open‑source digital public goods, and AI‑enabled marine services. A moderated panel of government officials, researchers, industry leaders and financiers then debated data stacks, physics‑informed AI, quantum‑enhanced modelling, entrepreneurship, and blue‑finance mechanisms. The audience raised practical questions on data accessibility, impact‑driven modelling and investment pathways.
Detailed Summary
1.1 The Blue Economy Imperative
- India possesses ~11,000 km of coastline; the blue economy underpins livelihoods, trade, and national GDP.
- Sustainable and equitable ocean development is essential to avoid over‑exploitation and climate‑driven degradation.
1.2 Deep Ocean Mission (DOM) – Core Objectives
| Project | Goal |
|---|---|
| Somdrayaan / MASYA | Human‑rated sub‑mersible to reach 6,000 m for scientific exploration. |
| Polymetallic Nodules | Identify and assess deep‑sea mineral resources in the central Indian Ocean. |
| Marine Renewable Energy | Harvest wave, tidal and offshore wind resources. |
| Biodiversity & Climate Impact | Monitor ecosystem health, acidification, and temperature rise. |
1.3 Climate‑Related Ocean Risks
- Oceans act as a carbon sink but increasing CO₂ absorption drives acidification, harming marine life.
- Rising sea‑surface temperature and heat content intensify cyclones, monsoons, sea‑level rise, and coastal hazards.
1.4 Observational & Modelling Infrastructure
- In‑situ assets – buoys, research vessels, island stations.
- Space‑based assets – geostationary & polar‑orbiting satellites for sea‑surface temperature, colour (chlorophyll), and wind.
- Modelling – Global, regional and coastal coupled ocean‑atmosphere models delivering services to fisheries, ports, and disaster‑risk managers.
1.5 Data‑Driven AI & Governance
- The explosion of oceanic data (remote sensing, in‑situ) enables AI/ML for predictive analytics.
- Open‑data policies, public‑private partnerships, and the Ocean Data Stack are essential to transform raw data into actionable intelligence.
- Call to academia, industry and start‑ups to co‑create AI tools, share data via APIs, and participate in capacity‑building programmes.
Announcement: The Ministry pledged free, open access to all oceanic datasets and invited collaborative R&D through PPP models.
2. Diplomatic Address – Her Excellency May Ellen Stenner (Norwegian Ambassador)
2.1 Norway‑India Strategic Alignment
- Both nations view the ocean as a driver of economic growth and climate resilience.
- Norway’s “digital public goods” (open‑source software, open standards) complement India’s large‑scale public data platforms.
2.2 AI as an Enabler for the Blue Economy
- AI can refine cyclone forecasting, fisheries management, and coastal resilience.
- Emphasis on interoperable, trusted digital foundations to ensure inclusive, cross‑border data sharing.
2.3 Joint Initiatives & Opportunities
| Focus Area | Potential Collaboration |
|---|---|
| AI‑enhanced ocean observation | Joint development of AI pipelines for satellite and buoy data. |
| Marine Spatial Planning (MSP) | Shared standards for spatial‑temporal resource allocation. |
| Blue Finance | Co‑design of financing mechanisms for sustainable marine projects. |
| Port & Shipping Optimisation | AI‑driven vessel‑traffic‑management pilots in Indian ports. |
Quote: “All ocean data becomes better when shared, because the ocean itself is a shared global commons.”
3. Panel Discussion – Moderated by Mr. Siva Kumar Murthy (EY)
3.1 Framing the Conversation
- Moderator highlighted the knowledge gap—humans know more about the Moon than the deep ocean—and introduced the panelists representing government, research, industry, start‑ups, and finance.
3.2 Panelist Contributions
3.2.1 Dr. Shishir Shrotriya (RIS) – Building the Ocean Data Stack
- Data Layer: Satellite constellations (OceanSat, RESat, upcoming NISAR) plus in‑situ sensors (ARGO buoys, research vessels).
- Intelligence Layer: Existing AI services (Potential Fishing Zone advisories, Illegal‑Unreported‑Unregulated (IUU) fishing detection, early‑warning systems).
- Marine Spatial Planning (MSP): Calls for integrating spatial & temporal dimensions into a unified stack for governance, carbon‑credit accounting, and biodiversity registries.
- Capacity Building: Emphasised training programs for the Global South, data‑sovereignty assurances, and open‑API ecosystems.
3.2.2 Dr. Deepak Subramani (IISc) – Physics‑Informed AI & “Physical Intelligence”
- Current AI Landscape: Large language models (LLMs) are trained on internet‑scale data, unsuitable for sparse oceanic datasets.
- Hybrid Modelling: Proposes neural operators and physics‑informed neural networks to embed ocean dynamics into AI, mitigating data scarcity.
- Predictability Horizon: Aims to push forecasts from sub‑daily to sub‑seasonal scales (1‑14 days) while respecting dynamical limits.
- Future Direction: Development of “Physical Intelligence” – AI that integrates physical laws, enabling smarter oceanic decision support (e.g., fisheries, disaster preparedness).
3.2.3 Mr. Jayakrishnan Hari (IBM‑Research) – Foundation Models, Quantum Computing & Use‑Cases
- Geospatial Foundation Models: IBM’s Prithvi suite extended to marine domain; can estimate phytoplankton biomass, detect harmful algal blooms, and delineate fishing zones.
- Quantum Advantage: Quantum simulation could accelerate high‑resolution weather and ocean forecasts beyond the 6‑7 hour window of classical supercomputers.
- Economic Impact: Ocean contributes ~4 % of India’s GDP but underpins 95 % of maritime trade; AI can unlock efficiency (e.g., port turnaround reduction, emission cuts).
3.2.4 Mr. Abhay Shukla (AI Transmute Solutions) – Startup Perspective & Data Liquidity
- Seaweed Farming Case Study: AI models integrate multi‑parameter marine data (salinity, SST, turbidity, pH) for site selection, stress detection, and supply‑chain planning.
- Data Stack Gap: Start‑ups must build proprietary stacks due to lack of a unified Ocean Data Stack; stresses need for API‑first, interoperable data services akin to India’s UPI for finance.
- Impact‑Driven Modelling: Advocates shifting from pure prediction to actionable impact forecasts (e.g., early storm impact zones, optimized vessel berthing).
3.2.5 Mr. Rakesh K. Mishra (EY) – Blue‑Finance & Investment Models
- Financing the Blue Economy: Highlights blended finance, PPPs, and sovereign guarantees to de‑risk large‑scale oceanic projects (offshore renewables, port modernisation).
- Policy Levers: Calls for clear, stable policy frameworks, risk‑sharing instruments, and incentives that attract both domestic and foreign capital.
3.2.6 Shri Kartikeya Anand (AEC, UK) – Renewable Energy & Regional Blue‑Economy Zones
- Regional Success Stories: Andhra Pradesh’s 1,052 km coastal corridor, six new seaports, and offshore wind initiatives.
- Scaling Potential: India can increase blue‑economy contribution from 4 % to 10‑12 % of GDP through renewable energy, marine spatial planning, and technology transfer.
- Financing Blueprint: Suggests a mix of green bonds, multilateral development bank loans, and government risk‑sharing to catalyse investments.
3.3 Audience Q&A (Selected Exchanges)
| Question | Respondent | Summary of Answer |
|---|---|---|
| How can individuals in data/AI contribute? | Moderator (Mr. Murthy) & Mr. Shukla | Approach government portals (e.g., ULIP under PM Gati Shakti) for data access; define clear project scope; explore partnership opportunities with MoES or start‑up incubators. |
| What about data interoperability across transport modes? | Mr. Shukla | Proposes an “Ocean‑UPI” – a unified API that links weather, satellite, marine traffic, and port data, reducing >80 % of data‑pre‑processing time. |
| How to ensure impact‑driven modelling rather than just predictions? | Mr. Shukla & Mr. Hari | Combine predictive AI with scenario‑analysis tools that output actionable recommendations (e.g., pre‑emptive evacuation routes, optimized berthing schedules). |
| What role can quantum computing play? | Mr. Hari | Quantum simulations can enhance the fidelity of oceanic and atmospheric models, potentially shortening forecast lead‑times. |
| How to finance large‑scale blue‑economy projects? | Mr. Mishra & Shri Anand | Use blended finance, sovereign guarantees, and green‑bond issuance; align projects with national climate commitments to attract multilateral funding. |
4. Closing Remarks – Cmd. Dr. Prashant Srivastava
- Re‑affirmed the Ministry’s commitment to open data, capacity building for the Global South, and AI‑enabled ocean governance.
- Highlighted the session as a “trailer” – the real “picture” of AI‑driven ocean science is just beginning.
- Thanked the panel, the Norwegian delegation, and the AI Summit organisers for a fruitful exchange.
Key Takeaways
- Deep Ocean Mission provides the scientific backbone (sub‑mersibles, mineral exploration, renewable energy) for India’s blue‑economy agenda.
- Data abundance (satellites, buoys, ships) now exists, but AI‑ready, interoperable data stacks are still a work in progress.
- Physics‑informed AI and neural operators are identified as the most promising pathways to overcome oceanic data scarcity.
- Open‑source digital public goods (Norway’s approach) and public‑private partnerships are essential for scaling AI services.
- Marine Spatial Planning requires a combined spatial‑temporal data‑intelligence layer for governance, carbon‑credit accounting, and biodiversity protection.
- Quantum computing could accelerate high‑resolution oceanic and atmospheric modelling, complementing classical AI pipelines.
- Start‑ups need API‑first, “Ocean‑UPI” style data access to reduce data‑pre‑processing bottlenecks and focus on impact‑driven solutions.
- Blue‑finance mechanisms—blended finance, sovereign risk‑sharing, green bonds—are crucial to mobilise the capital needed for offshore renewables, port modernisation, and ecosystem restoration.
- Collaboration across nations (e.g., Norway‑India) and sectors (government, academia, industry, finance) is the linchpin for building a resilient, AI‑enabled ocean economy.
Prepared by the AI Conference Summarisation Team.
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