Re-engineering engineering for the Age of AI

Advances in Artificial Intelligence (AI), along with other recent developments in technology, are pivotal in designing a resilient future. In a recent discussion, as president of the Institution of Engineering and Technology (IET), I emphasised how engineers empowered by AI are crucial to orchestrating our collective future.

Engineering, traditionally a bastion of problem-solving and practical application of theoretical knowledge, is experiencing a seismic shift. The current technological era necessitates that engineers extend beyond their specialisations, embracing the rapid advancements in AI, materials science, and life sciences, championing continuous learning and adaptability.

AI is a force-multiplier, intersecting with various scientific domains, profoundly impacting human health and comfort. This intersection is where modern innovation flourishes. However, it also brings new responsibilities for engineers, who must now evolve into storytellers and artists, advocating for their ideas while addressing ethical implications and environmental sustainability. Leadership in this new era demands vision beyond traditional business goals. Leaders must inspire creativity and innovation while acting as change agents in our digital world.

The practical applications of AI are both diverse and impactful. As examples from my own team at Myelin Foundry, AI has enhanced video resolution and night-time video quality, improving streaming experiences, parking assistance, and surveillance applications. In another instance, AI adapted to local needs, like identifying every object on crowded Delhi streets, including cattle. In healthcare, AI’s role in predicting chronic diseases through non-invasive methods marks a shift from a reactive to a proactive approach in medicine, potentially revolutionising healthcare.

However, harnessing AI’s power requires a strong sense of responsibility. Ethical considerations in AI, focusing on fairness and privacy, are paramount. Contrary to fears of AI-induced job losses, AI is set to create new opportunities, redefine existing roles, and make work more accessible globally.

The concept of resilient futures is central to our discussion. To achieve this, we need to track and understand socio-political and consumer trends and innovate responsibly. The future of engineering and AI lies at the intersection of biology, digital technology, and material science. This convergence is crucial in sustainable innovation.

One ambitious goal I have outlined is the creation of 100 million AI jobs in India, focusing on both rural and urban areas across various sectors. This requires a multifaceted approach involving education, infrastructure, policymaking, and industry partnerships. These jobs need not be full-time and traditional -- they could be for a couple of hours a day or a couple of days a week. The key thing is that the jobs provide meaningful and fair income options.

l→70% in rural areas for data creation and annotation: Establish training centres in rural areas for skills in data annotation, improve internet connectivity, create micro job platforms, and encourage local language projects.

l→20% in urban corporates and start-ups for AI application development: Support the start-up ecosystem, foster corporate partnerships and collaborations, and set up urban innovation hubs.

l→10% in academia, government, and large corporations for AI algorithm development: Invest in R&D within universities, develop ethical AI policies, engage in international collaborations, and provide funding for cutting-edge research.

Cross-cutting strategies include educational reform, establishing regulatory frameworks, increasing public awareness about AI, and ensuring sustainable and inclusive AI development.

In India and globally, we should acknowledge the significant challenges ahead of us:

While AI fosters new job-creation, it risks displacing workers in sectors like manufacturing and healthcare, necessitating strategic retraining and reskilling. AI’s limitations in understanding context and making nuanced judgements, especially critical in healthcare, pose reliability concerns. Additionally, AI’s environmental impact, due to its high energy consumption, calls for sustainable practices in technology development. Ensuring AI’s accessibility and inclusivity for diverse populations is crucial to avoid societal divides. Lastly, the growing global skill gap in AI demands educational integration, vocational training, and international collaboration to foster a workforce adaptable to AI advancements.

As we stand at the threshold of a new era, the intersection of AI, advanced materials, and advanced biology promises a future that is not only technologically advanced but also environmentally sustainable and cantered around the betterment of humanity.