“The opportunities for using AI to lead to a sustainable future are huge”
Generative AI has the potential to transform the global economy, with huge potential for innovation and progress and a global market that GHD Digital estimates can reach USD 1.5 trillion in revenue by 2033.
Five years ago GHD embarked on a journey to address digital disruption in the AEC industry with the creation of GHD Digital, currently a globally recognized digital agency. Recognising that advancements in AI will lead to radical changes across industries, GHD Digital recently released a new report titled Beyond AI: Generative AI and the next wave of disruption, exploring the potential of generative AI across sectors. We had the opportunity to ask Nipa Basu, GHD Digital Global Practice Director - Digital Intelligence, about the report’s highlights and the applications of generative AI in the water industry.
Please tell us briefly about your career path and your current role at GHD Digital.
I am a global digital transformation leader helping clients transform their businesses through data analytics and artificial intelligence solutions. I lead the global Digital Intelligence team for GHD Digital. My team’s expertise and contribution covers data and digital strategy, data collection, data management, drawing insights from data, especially spatial data, predictive-prescriptive analytics, machine learning, and artificial intelligence (AI). My team collaborates with GHD engineers on projects that lead to positive improvements and outcomes across the areas of water, energy and communities. Examples of projects include the remediation of contaminated lands, reduction in greenhouse gas emissions, removal of lead pipes from households in underprivileged communities, solving clean drinking water scarcity problems, enhancement of traffic safety, etc.
I have a Ph.D. in Economics (Public Finance) from SUNY (State University of New York) Albany. My first professional job was as an economist in the Legislative Tax Study Commission for NY State.
In 2018, GHD embarked on a journey to address digital disruption in the $300 billion Architecture, Engineering, and Construction industry
My involvement in data science and artificial intelligence - this converging digital space between analytics and technology - started a long time ago when I worked for a defence lab in Albuquerque, New Mexico. I worked on the very first version of an artificial agent-based microsimulation model of the U.S. economy. The project, started by a visionary nuclear physicist, with only four people including me, continues to thrive today.
After the defence lab, I worked at AT&T, before spending more than 20 years at Dun & Bradstreet building their analytics business. For the last four years of my tenure at Dun & Bradstreet, I was the Chief Analytics Officer.
GHD Digital recently celebrated 5 years. What is your assessment of this time?
GHD Digital has accomplished a lot in the last five years. In 2018, GHD embarked on a journey to address digital disruption in the $300 billion AEC (Architecture, Engineering, and Construction) industry. Our mission was to create a startup - GHD Digital – within a long-established company to assist our clients and our own company with handling digital disruption.
Today, GHD Digital is a globally recognized digital agency with over 600 employees across nine countries and 86 offices. We serve Fortune 500 companies, major utilities, large government agencies and leading organizations across the world. We have created new capabilities in data science, artificial intelligence, cybersecurity, automation, products and platforms, and many new areas while modernizing some of our traditional businesses like data management and location intelligence.
The story of GHD and GHD Digital for the last five years is a story of boldness, resilience and disruptive thinking. This was made possible with the fantastic collaboration between established engineering specialities within GHD and the new Digital components.
The potential of generative AI extends beyond productivity gains: it can also play a role in sustainability and climate change objectives
I consider myself incredibly lucky to be part of GHD Digital’s recently celebrated five years. I had already spent a lifetime in a well-known data analytics company before I joined GHD Digital four years ago. I had a lucrative career, a great data science team, excellent clients, and great leaders/mentors, but there was one thing missing. Data science and artificial intelligence were reaching incredible heights and I often wondered whether my skills could be used to create more “good for the society”.
I took a bit of a gamble in joining a company and an industry (AEC) that I knew little about. It took some time and lots of struggle to understand the applications of data science in the various key GHD industries, but then the magic happened. I could see GHD Digital and my team’s contribution - cleaning up the environment, solving drinking water scarcity problems, and making our roads and bridges safer. We are doing good for the communities, and that is something that makes me happy to celebrate.
How did the idea of producing the report titled Beyond AI: Generative AI and the next wave of disruption emerge? What would you highlight from it?
Generative AI was already impacting how we work and interact with the world, and we knew it was important to develop our own unique point of view on the technology. We had already recognized that our clients wanted to harness AI but weren’t sure exactly where to start. We also launched an AI Centre of Excellence earlier this year, with over 40 specialists aimed to help our clients understand the benefits and risks of using AI technologies and fast-track their use of AI to provide value for their customers, people and communities.
I would highlight generative AI’s immense promise and potential from the report. Its potential applications span all sectors, offering innovative solutions and transforming traditional approaches. As businesses and society embrace generative AI tools, the impact on economic growth and productivity is set to be profound. By 2030, AI is projected to significantly enhance the productivity of knowledge workers through the automation of routine tasks, real-time data analysis, personalized assistance, improved collaboration, customized learning experiences, enhanced decision-making processes, and reduced human errors.
AI directly will not change anyone’s mind, but can make compliance with regulations and doing the right things easier for businesses
Its potential extends beyond productivity gains, as it can also play a crucial role in helping companies and governments achieve sustainability and climate change objectives. Organizations focused on critical issues such as climate change, water scarcity and sustainability play a pivotal role in understanding and mitigating their impact on communities. Engineers and data analytics specialists must harness their technical expertise and embrace the immense potential of generative AI to tackle these issues with unwavering determination.
The report discusses a number of ethical concerns related to the adoption of generative AI; which of them do you think are most pressing at the moment?
I believe the most pressing concerns are regarding biases inherent in the training data, which is often inaccessible due to its proprietary nature, as well as the potential for the model to fabricate or hallucinate information. Furthermore, challenges may arise in rectifying errors within models, and uncertainties surrounding liability may emerge when deploying solutions reliant on this technology.
Ensuring the ethical and responsible use of generative AI is crucial, requiring collaboration between governments, regulators, and business leaders to develop robust governance frameworks and ethical guidelines.
The report highlights applications of generative AI in sustainability, based on improvements to existing science, technology and design. Yet some might argue that sustainability is not currently hindered by a lack of knowledge, but rather by a lack of will to implement the solutions we already know about. Can digital technologies ever help to improve governance to support sustainability objectives, for instance helping today’s leaders think more long term?
It is true that AI directly will not change anyone’s mind. But AI can make compliance with regulations and doing the right things easier for businesses. There is still a lack of knowledge in the sustainability space. Regulations are often difficult to understand or interpret. One of our offers in this space is the deconstruction of permits. Digital technologies can also help in monitoring and proving adherence to compliance.
Areas like climate modelling and prediction are benefitting tremendously from AI’s ability to process massive amounts of data. AI can help in natural disaster prediction and recovery. AI can enable a circular economy by coming up with more efficient recycling programs or helping design products in sustainable ways. AI can help ethical and sustainable sourcing. Predictive maintenance using AI can help lead to sustainable production systems. The opportunities for using AI to lead to a sustainable future are huge.
According to GHD Digital analysis, about 50 per cent of generative AI-generated data is fabricated or inaccurate. This is quite striking; are prospective generative AI users equipped to deal with that?
Not yet. ChatGPT has created unprecedented enthusiasm, and people without any training on how to prompt a machine for the right answers are asking questions.
We now have “bigger” data; lots of research, training, and understanding is needed for the proper use of AI-generated data
We have come full circle. There was a time when data was scarce. Statisticians specialized in creating algorithms that could draw correct conclusions from small amounts of data. Advances in computer science turned the problem on its head by enabling us to process mind-boggling amounts of data. This created “big data”.Generative AI is now adding to it by creating new data/content, part of which is the result of hallucination. So, we now have “bigger” data – but, we also have the task of deciphering what is usable. Lots of research, training, and understanding are needed for the proper use of AI-generated data.
Are there additional cybersecurity risks related to the adoption of generative AI?
The adoption of generative AI in the water industry can introduce certain cybersecurity risks. Given that generative AI models like GPT-3 are trained on a vast amount of data, there is a potential for malicious actors to exploit vulnerabilities in these models. This gives rise to deceptive or harmful content like generating false reports, manipulating sensor data and even launching targeted attacks on water infrastructure systems.
Therefore, organizations in the water industry must implement robust security measures, such as secure data transmission, access controls, and regular model audits, to mitigate these risks and ensure the integrity and reliability of their systems.
Looking ahead, how do you envision the evolution of generative AI’s role in the water industry? What role do you see for GHD Digital in this process?
I see the impact of generative AI on the water and wastewater industry coming from two different sources. First, we have had the ability to use machine learning or artificial intelligence to solve many problems. However, those capabilities have not exactly been leveraged to the extent that they should be utilized. Now, the enthusiasm generated by AI will help in the utilization of those already existing tools. Second, generative AI has its own applications.
There has been a deluge of data resulting from digitization, better data collection and management, but limited deployment of these newly gained resources to make decisions. With the current tailwinds for the adoption of AI-based solutions, I see that operators will be better equipped to make decisions based on these solutions.
Prediction of future water demand based on historical data can help utilities to plan for and manage water supply more effectively. This would reduce the risk of water shortages. Predictive maintenance can be used to identify and prioritize maintenance needs. AI can also be used to create models that can detect water quality problems and simulate the impact of water management strategies. There will also be applications in designing waste-water treatment plants, optimizing treatment processes, monitoring and detecting problems, etc.
With the current tailwinds for the adoption of AI-based solutions, I see that operators will be better equipped to make decisions
Going further, I see that generative AI will be used not only for facility operations (asset management, predictive maintenance, water quality and demand forecasting, optimization and leakage detection) but also business operations (customer engagement, bids and tenders management, etc.) and designing of water-related systems.
An example of a benefit would be the reduction of energy, chemical, and water usage and overall better usage of resources including the staff. Customer engagement using chatbots will be a boost that can provide further customized responses which will lead to better engagement.
Generative AI will be used not only for facility operations, but also business operations and designing of water-related systems
This will result in the role of all the personnel shifting to higher value-added jobs within utilities. This comes at a time when we are expected to see about two-thirds of the operators retiring in the next few years and an increase in a tech-savvy, young generation who has willingly adopted newer technologies.
GHD has a long history of supporting water utilities and industry from a technical and engineering perspective. GHD Digital is adding digital and data analytics capabilities including AI to the mix. The best results are obtained when GHD’s domain knowledge is complimented by data analytics capabilities. This enables GHD to provide an end-to-end solution. GHD Digital’s AI solutions are not in a vacuum. They are provided within the context of the client’s actual needs. GHD is expected to play a major role in the evolution of how the water sector modernizes itself with the help of AI.