Future priorities for AI in an evolving digital energy cyber security regulatory framework

Recent fast paced IoT hyper connectivity growth and dynamic AI evolution are impacting all industries. For the energy sector, digital transformations have been particularly seismic due to their outdated infrastructures, explains Hebberly Ahatlan.

Grid modernisation and data security are of focal points as Artificial Intelligence (AI) revolutionises infrastructure performance and business insights.

The Executive Order from the White House on the "Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence" signifies a crucial step towards establishing trust and security guidelines for rapidly advancing AI technologies.

This initiative is particularly vital for the digital energy sector, where AI plays a central role in critical infrastructure projects such as Virtual Power Plants (VPPs) and Energy as a Service (EaaS).

Looking ahead, the future priorities for AI in this industry revolve around ensuring productivity, authenticity and security.

AI's role in digital energy productivity

Beyond content generation, AI serves as the driving force behind automating decision-making processes in the digital energy sector, notably in projects like Virtual Power Plants and Energy as a Service.

VPPs leverage AI to optimise energy generation and distribution, ensuring a balanced supply and demand. EaaS, powered by AI, provides consumers with flexible, adaptive energy services. These innovations have the potential to transform energy production and consumption, making it more sustainable, efficient, and cost-effective.

Ensuring data provenance and authenticity

Critical to AI's success in the digital energy industry is the assurance of data provenance, authenticity and transparency.

The Executive Order aligns with the establishment of a universal data, IoT and AI trusted interoperability standard. This framework sets clear provisions for governing and tracking content and decisions made by dispersed AI platforms.

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Key aspects include:

• Training AI Algorithms: AI algorithms rely on authentic and unbiased data for training, directly impacting their effectiveness in optimising energy processes. A layered trust stack ensures the security of data provenance and device authenticity.

• AI-Driven Decision-Making: Authentic, authoritative, and policy-compliant data is essential for AI-driven decision-making in critical infrastructure projects. An interoperable standard must be future-proofed to handle evolving cyber threats, including quantum computing.

• Verification and Authentication: The order emphasizes verifying AI compliance with policy criteria, requiring authentication of verifier credentials. A universal secure interoperability standard necessitates a stack of verification algorithms adaptable to diverse layers.

Transparency in AI-generated content

In the digital energy sector, AI-generated content influences people's actions, demanding transparency to build trust and ensure responsible AI use. Transparency provisions are effective when assuring entity authenticity and authorisation across diverse technologies and statuses.

An authoritative and authenticated web is being designed to address:

• Provenance of Data and Content: Tracing and recording the origins of data and content are crucial for reliability in energy information. In a VPP, a well-managed software platform is essential for administering all aspects, from monetisation to compliance reporting.

• Credential Authentication: Verifying data providers' credentials and sensor properties ensures the legitimacy and trustworthiness of data sources, crucial in systems like Energy as a Service.

• Interoperability for Assurances: Interoperability is crucial for applying assurances effectively in distributed systems. TEIA, the Trusted Energy Interoperability Alliance, founded by Intertrust, answers the call for AI regulation, integrating security and interoperability within a flexible standard.

Policy and data in trustworthy AI operation

The executive order stresses the need for using both policy and data to manage trustworthy AI operations. With AI influencing decision-making in various automated systems, recognising its roles is crucial.

Trust management and adaptable policy frameworks are necessary for:

• Reasoning About AI: Transparency, trust management and agile policy frameworks are vital for reasoning about the provenance and authenticity of AI inputs and outputs.

• Security Infrastructure: An efficient security infrastructure must ascertain data and AI provenance, providing tools for authentication by both people and automated applications.

• Real-Time Responsiveness: Security infrastructure and policy frameworks must be self-adaptable to meet the real-time requirements of decision-making in the digital energy industry.

• Resilience to Attack: Interoperable security measures across IoT and data processing fabrics ensure resilience against malicious attempts, safeguarding energy infrastructure.

• Integration with the Web: Seamless integration ensures broader, comprehensive security, crucial in the digital energy sector where VPPs and EaaS rely entirely on digital platforms.

The Executive Order on AI development and use is a significant milestone for the digital energy industry, emphasizing the importance of AI in optimising energy processes.

Intertrust's TEIA aligns with the order, ensuring AI-driven decisions comply with accurate data and policy criteria. Industry stakeholders should actively engage with the proposed mechanisms and TEIA solutions, contributing to a secure and dynamically adaptable digital energy future. This collaborative approach will foster efficiency, reliability, and sustainability in the evolving landscape of AI in the energy sector.

About the Author

Hebberly Ahatlan is product marketing director, energy at Intertrust Technologies and has 15 years of experience in the tech industry developing go to market strategies.