Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Linear Infrastructure Planning Panel: A Collaborative approach to AI governance



The Linear Infrastructure Planning Panel was established in March 2023 with a clear purpose: to develop good practice in the use of new technologies like AI in the planning of the major infrastructure (e.g. energy grids) that are critical for the delivery of national goals such as net zero, resilience and nature recovery. The Panel is an example of a multi-stakeholder deliberative engagement process that has sought to build consensus in a challenging area. It is a collaboration between social and environmental NGOs, data and planning experts and government / regulatory bodies. 

The Panel was kicked-off with seed corn funding from AI start-up Continuum Industries. However, it is independent. The Chair and Panel members sole duty is to forward the purpose of the Panel. 

As of June 2024 the Panel has carried out deep dives into: 

  • trustworthy new tools and approaches; 
  • the social, environmental, and economic metrics used in new tech; 
  • and how new techniques can support engagement. 

It has published all its findings and widely shared its work with key decision makers, project developers and tech companies over the last year.

Choice of approach

The Panel’s deliberative and collaborative engagement process has helped to bring diverse groups of stakeholders together in a way that has not happened before to consider how they best address a specific outcome: how to develop good practice in the use of AI and other advanced technologies in an already highly complex and contested area. By creating a consensus on how AI can transform infrastructure planning, the Panel has provided a forum to accelerate the journey towards national goals such as net zero and resilience.

The issues the Panel has considered have spanned government departmental and regulatory vires, the responsibilities of the different UK nations (much of planning is a devolved issue) and the interests of project developers, promoters, and consultancies. This has led to a collective action problem in this area where different organisations have tended to work in silos. Tackling the associated issues in the round has been vital to start to unlock the potential for AI and other advanced tech to address some of the key barriers to infrastructure planning and delivery.

The Panel has worked in an iterative way to build support and consensus. Panel members agreed a theory of change and the topics for deep dives at its first meeting. For each session, an outline of the issues to cover was circulated to members and observers for comment in advance.  Continuum Industries, who had kick started the Panel’s work and provided seed corn funding to get it going, gave insights into some of the practical challenges they had faced on that topic.

A draft briefing paper was produced on the back of this to guide panel conversations. This was amended following the deep dive to take Panel comments on board. Final copies of briefing papers were then placed on the Panel website and the Chair used these as the basis for bilateral discussions and presentations to project developers, tech companies, government departments, regulators and professional networks and associations – in the UK and globally (e.g. through the Global Infrastructure Hub). This wider outreach was seen as essential to help change the frameworks and cultures which will shape the use and uptake of AI in this area and to get wider insights into upcoming challenges and opportunities

Benefits: 

As a result of their involvement with the Panel government actors will be able to unlock the potential of AI that can address planning skills and capacity challenges and help deliver faster, more popular, and greener infrastructure.  Regulators will be able to help unleash and embed innovation by ensuring new tools are trustworthy and aligned with stakeholder views. Consumers and communities will be able to see how new tools can enable democratic engagement in planning before major technical decisions are locked in.  

Project developers will have greater confidence that the digital tools they use are trustworthy so they can radically shrink the time of technical planning work increasing certainty, reducing costs, and freeing time to focus on the key sticking points where human judgement is needed. Tech companies will be able to seize the opportunity to help create and grow a trustworthy market in this area.  And investors will be able to place reliance on new tools and approaches to help them de-risk their investments and demonstrate delivery of their ESG goals with more meaningful social and environmental impact reporting.

Limitations:

The Panel was established as a ginger group. To date, its relatively informal structure has meant it has been able to act quickly and nimbly. However, being outside a recognised public body (e.g. a government department, regulator, innovation catapult or professional association) has meant that it has sometimes struggled to get heard by decision makers and has had to continually assert its independence.

Having proved the concept of collaborative work in this area, the Panel is now exploring how to ‘dock into’ / be hosted by a larger recognised public body that can give it credibility and enable it to raise the modest funds needed to cover its costs. This is proving challenging given the collective action and silo decision making problems identified earlier. Although the Panel has an identified forward work programme, there is a risk that unless a new host and funding can be found its work could come to an end.

 

Link to the full use case.

This case study was published in collaboration with the UK Department for Science, Innovation and Technology Portfolio of AI Assurance Techniques. You can read more about the Portfolio and how you can upload your own use case here.

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.