In 2024 construction law continued to see remarkable advancements in its use of AI. Stacy Sinclair reports on the increasing use of AI and an inaugural conference on AI & Construction Law held at the Technology and Construction Court in London.
Introduction
A year ago I published an article titled “AI is about to completely change construction law”.[1]While the “complete change” I boldly anticipated of course has not materialised within just one year, construction law in 2024 certainly has witnessed remarkable advancements, driven by the growing use of AI.
For the record, I did say in the 2023 article that it would take two to five years for the transformation, as generative AI at that point was at the “peak of inflated expectations” on the Gartner Hype Cycle 2023.[2]
The Gartner Hype Cycle is a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities.[3] Those technologies in the “peak of inflated expectations” are predicted to reach mainstream adoption within two to five years, the “plateau of productivity”.
Now, in the recently released Gartner Hype Cycle 2024, we see generative AI has moved into the “trough of disillusionment”.[4] This means interest in the technology is waning and investments shift to those providers who improve their products to the satisfaction of the early adopters.[5] It also means that generative AI is still on course, moving through the expected cycle, heading towards mainstream adoption at which point, I suggest, we will see a transformed industry.
In 2024, the focus certainly has shifted to putting AI into practice. Both legal and construction professionals in the industry are starting to realise and bring to life the transformative potential of AI. While discussions and debates around AI’s opportunities and risks continue, the industry is forging ahead, exploring how to implement AI responsibly and safely to drive innovation, reduce time and costs, and ultimately enhance quality.
This article looks briefly at the growing landscape of applications of AI in construction law, along with the inaugural conference on AI & Construction Law, recently held at the Technology and Construction Court.
AI & Construction Law: Applications
AI is already part and parcel of many applications and services we regularly use, whether we are aware of it or not. From facial recognition to unlock mobile phones, personalised feeds on social media and movie recommendations on Netflix to self-driving cars and smart home devices, AI is now widespread in our everyday lives.
In terms of construction law, the possibilities too are ever growing and AI applications are available throughout the lifecycle of a construction project: project identification, stakeholder engagement, design, procurement, contract management, construction, commissioning and operation. The following diagram provides some examples in each of these areas.
In addition, should complaints or grievances escalate into claims, parties and their representatives can benefit from AI tools throughout the lifecycle of a dispute. The diagram in Figure 2 provides an overview of the areas where AI has the potential to enable more efficiency and productivity in the dispute process, if used responsibly, safely and ethically.
AI & Construction Law: Joint AI Seminar Series
To advance the industry’s knowledge and application of AI, The Technology and Construction Court (“TCC”), King’s College London, The Technology and Construction Solicitors’ Association (“TECSA”), The Technology and Construction Bar Association (“TECBAR”), the Society of Construction Law and the Society for Computers & Law have joined forces and established an AI Seminar Series.
The first seminar was held on 10 October 2024 at the Rolls Building in London, focusing on the construction industry’s current use of AI and what we can expect to see in the near future. Speakers from architectural, engineering and contracting firms were invited to speak to provide an initial overview of where the industry is at with its use of AI and where it is headed.
Mr Justice Waksman, Judge in Charge of the TCC, opened the seminar. Peter Brogden (Barrister at Keating Chambers), Martha Tsigkari (Head of Applied R&D at Foster + Partners), Pedro Rente Lourenco (Group Head of Data & Analytics at Laing O’Rourke) and Caro Ames (Data Science Strategy Lead at Arup) each provided insights into the use of AI at their respective firms, challenges faced and opportunities for the future of AI. Following these presentations, Mrs Justice Joanna Smith chaired a panel discussion.
The next seminars will be in held in 2025, and are likely to focus on the legal industry’s use of AI in the dispute process, along with the opportunities, challenges and issues of data. The dates are expected to be confirmed soon.
The following is brief, high-level summary of the first seminar in October 2024, generated by AI.
PART 1: Insights and Innovations – exploring our industry’s present and future
Disclaimer: The following summary is the output from a generative AI tool, based on the recording and transcription of the seminar. Only typographical errors in the spelling of the speakers’ names have been corrected. Otherwise, the following is the direct output to demonstrate the capability of AI. This summary is neither approved nor endorsed by the speakers.
Summary
The seminar focused on the current and future use of AI in the construction industry, featuring speakers from various sectors. Key points included the role of neural networks and transformers in AI advancements, the importance of data quality and governance, and the ethical considerations of AI deployment. Specific applications discussed were generative design, predictive systems, and large language models. Concerns about data sharing, bias, and liability were raised, with solutions like anonymization and governance frameworks proposed. The discussion also highlighted the potential for AI to enhance efficiency but emphasized the need for human oversight to avoid over-reliance and maintain professional expertise.
Outline
Introduction and Overview of the Seminar
Speaker 1 [Mr Justice Waksman] introduces the seminar, highlighting its focus on the construction industry’s use of AI and its future prospects.
The seminar is supported by various organizations, including TCC, TECSA, TECBAR, King’s College London, Society of Construction Law, and Society for Computers and Law.
Speaker 1 [Mr Justic Waksman] introduces the speakers: Peter Brogden, Martha Tsigkari, Pedro Rente Lourenco, and Caro Ames, and mentions that Peter Brogden will use an AI platform for his introduction.
The format of the evening includes talks by each speaker, followed by a Q&A session chaired by Mrs. Justice Joanna Smith.
Introduction of Peter Brogden and AI Demonstration
Speaker 2, Peter Brogden, introduces himself and mentions the use of an AI co-host.
The AI co-host introduces Peter Brogden and the other speakers, highlighting their expertise in AI and the construction industry.
Peter Brogden explains the purpose of his talk, which is to introduce AI and explain its foundations, particularly neural networks and transformers.
He uses a neural network analogy to explain how AI recognizes patterns and makes predictions, emphasizing the importance of data and dimensions in AI training.
Explanation of Neural Networks and AI Capabilities
Peter Brogden elaborates on the structure of neural networks, including neurons, weights, and dimensions.
He explains how AI models like GPT-3 and GPT-4 are trained using vast amounts of data and transformers to analyze data at various levels of attention.
Brogden discusses the different types of AI, including generative AI, which can generate new text, images, and videos, and autonomous AI, which can perform tasks and solve problems.
He provides examples of AI applications in various fields, such as text-to-speech and speech-to-text conversion, and autonomous AI in self-driving cars.
Martha Tsigkari’s Presentation on AI in Architecture
Martha Tsigkari from Foster + Partners discusses the impact of AI on the architecture industry, emphasizing the importance of data in driving AI advancements.
She explains the three key factors driving AI adoption: data, computational power, and adoption rate.
Tsigkari highlights the various AI applications in architecture, including generative design, surrogate models, and large language models for document search.
She discusses the potential of AI to revolutionize the architecture industry, particularly in design and operational efficiency.
Pedro Rente Lourenco on Deploying AI in Construction
Pedro Rente Lourenco from Laing O’Rourke discusses the challenges and implications of deploying AI in the construction industry.
He explains the different types of machine learning: supervised learning, unsupervised learning, reinforcement learning, and generative AI.
Lourenco emphasizes the importance of having a robust data infrastructure, including cloud platforms, data governance, and data quality architectures, to support AI deployment.
He discusses the risks associated with AI, such as bias, privacy, and security, and the need for governance models to manage these risks.
Caro Ames on AI in Infrastructure and Data Sharing
Caro Ames from Arup discusses the role of AI in delivering sustainable outcomes across the built environment.
She highlights the challenges of data sharing in the construction industry and the need for trustworthy and standardized data sharing infrastructure.
Ames provides examples of AI applications in infrastructure, such as digital twins for energy sector transition and document management systems for legal capabilities.
She emphasizes the importance of building capabilities and governance frameworks to support AI adoption and ensure data quality and security.
Panel Discussion on Data Sharing and AI Risks
The panel discusses the risks and challenges of data sharing in the construction industry, including confidentiality, bias, and privacy concerns.
Peter Brogden and Martha Tsigkari emphasize the importance of having data governance frameworks and legal structures to manage data sharing and AI deployment.
Pedro Rente Lourenco and Caro Ames discuss the need for capability building and understanding the value and risks of data to support better data sharing practices.
The panel also addresses the potential impact of AI on job roles and the importance of maintaining domain expertise and professional judgment in AI-assisted decision-making.
Liability and Ethical Considerations in AI Use
The panel discusses the liability implications of using AI in the construction industry, particularly in the event of disasters or errors.
Peter Brogden and Pedro Rente Lourenco emphasize the importance of professional judgment and accountability in using AI tools.
Caro Ames highlights the need for assurance processes and learning and development to ensure that AI is used ethically and effectively.
The panel also addresses the potential for AI to reinforce biases and the importance of building diverse and inclusive data sets to avoid these biases.
Future of AI in Construction and Final Thoughts
The panel discusses the future of AI in the construction industry, including the potential for AI to automate processes and improve efficiency.
Martha Tsigkari and Pedro Rente Lourenco emphasize the importance of continuous learning and adaptation to stay ahead of AI advancements.
Caro Ames highlights the need for strategic planning and collaboration to drive AI adoption and ensure long-term benefits.
The panel concludes with a discussion on the importance of ethical considerations and the need for a balanced approach to AI deployment in the construction industry.
[1] Sinclair, S (2023) AI is about to completely change construction law, Fenwick Elliott. Available at: https://www.fenwickelliott.com/knowledge-hub/annual-review/ar-2023/ai-is-about-to-completely-change-construction-law/https://www.fenwickelliott.com/research-insight/annual-review/2023/ai-change-construction-law
[2] Gartner (2023) Gartner places Generative AI on the peak of inflated expectations on the 2023 hype cycle for emerging technologies, Gartner. Available at: https://www.gartner.com/en/newsroom/press-releases/2023-08-16-gartner-places-generative-ai-on-the-peak-of-inflated-expectations-on-the-2023-hype-cycle-for-emerging-technologies
[3] https://www.gartner.com/en/research/methodologies/gartner-hype-cycle
[4] Gartner (2024), Spotlight on 2024 Gartner Hype Cycle for Emerging Technologies, Gartner. Available at: https://www.gartner.com/en/articles/hype-cycle-for-emerging-technologies
[5] https://www.gartner.com/en/research/methodologies/gartner-hype-cycle
