Since 2011, the World Economic Forum (WEF) has published an annual list of the Top Ten Emerging Technologies that are likely to be disruptive within three to five years. The Top 10 Emerging Technologies of 2024 was released by the WEF in June. The report is based on the insights of over 300 world-leading academics and researchers from the WEF’s Network of Global Future Councils and University & Research Network, and from the Frontiers network of over 2,000 chief editors from top global institutions.
A survey was distributed to members of these various networks asking them to propose technologies for the 2024 Top 10 list. The survey received over 300 valid technology nominations from 29 countries. After an initial screening, the Top 10 Emerging Technologies Steering Group was presented with a curated list of 70 technologies from which the final ten were selected based on four criteria:
- Novelty: The technology is emerging and at an early stage of development but is not yet widely used.
- Applicability: The technology is potentially of significant use and benefit to societies and economies.
- Depth: The technology is attracting increased development, investment, and excitement.
- Power: The technology is potentially game-changing to established ways and industries.
Here are the technologies comprising the 2024 Top 10 list, along with the reason cited by the WEF for their selection:
AI for scientific discovery — “While artificial intelligence (AI) has been used in research for many years, advances in deep learning, generative AI and foundation models are revolutionizing the scientific discovery process. AI will enable researchers to make unprecedented connections and advancements in understanding diseases, proposing new materials, and enhancing knowledge of the human body and mind.”
Privacy-enhancing technologies — “Protecting personal privacy while providing new opportunities for global data sharing and collaboration, ‘synthetic data’ is set to transform how information is handled with powerful applications in health-related research.”
Reconfigurable intelligent surfaces — “These innovative surfaces turn ordinary walls and surfaces into intelligent components for wireless communication while enhancing energy efficiency in wireless networks. They hold promise for numerous applications, from smart factories to vehicular networks.”
High-altitude platform stations — “Using aircraft, blimps and balloons, these systems can extend mobile network access to remote regions, helping bridge the digital divide for over 2.6 billion people worldwide.”
Integrated sensing and communication — “The advent of 6G networks facilitates simultaneous data collection (sensing) and transmission (communication). This enables environmental monitoring systems that help in smart agriculture, environmental conservation and urban planning. Integrated sensing and communication devices also promise to reduce energy and silicon consumption.”
Immersive technology for the built world — “Combining computing power with virtual and augmented reality, these technologies promise rapid improvements in infrastructure and daily systems. This technology allows designers and construction professionals to check for correspondence between physical and digital models, ensuring accuracy and safety and advancing sustainability.”
Elastocalorics — “As global temperatures rise, the need for cooling solutions is set to soar. Offering higher efficiency and lower energy use, elastocalorics release and absorb heat under mechanical stress, presenting a sustainable alternative to current technologies.”
Carbon-capturing microbes — “Engineered organisms convert emissions into valuable products like biofuels, providing a promising approach to mitigating climate change.”
Alternative livestock feeds — “Protein feeds for livestock sourced from single-cell proteins, algae and food waste could offer a sustainable solution for the agricultural industry.”
Genomics for transplants — “The successful implantation of genetically engineered organs into a human marks a significant advancement in healthcare, offering hope to millions awaiting transplants.”
The 2024 Top Ten report includes a more detailed one-page description of each of these technologies. Let me briefly discuss the top technology on the list — AI for scientific discovery.
AI systems have been demonstrating capabilities unimagined just a decade ago, from AlphaGo’s unexpected win in 2016 over Lee Sedol, - one of the world’s top Go players, to the impressive capabilities of Large Language Models to respond to and generate text and speech in a wide variety of languages.
But in recent months, there have been serious warning that we may be going through another AI hype cycle. A May 31 WSJ article, “The AI Revolution Is Already Losing Steam,” noted that “significant disappointment may be on the horizon, both in terms of what AI can do, and the returns it will generate for investors.” It added that while increasingly powerful AI models keep being developed, “it takes a long time for them to have a meaningful impact on how most people actually work.”
A few weeks later, a NY Times article asked “What if the A.I. Boosters Are Wrong?,” noting that there’s a heated debate among economists as to whether AI will supercharge productivity by ushering the next industrial revolution. If the boosters are wrong, it added, “it could be trouble for the developed world, which is in desperate need of a productivity breakthrough as its work force ages and declines.”
Scientific discovery is the one area where there’s near universal agreement that AI is already having a major impact. “AI is emerging as a transformative general-purpose technology in scientific research that can unearth discoveries that would have otherwise remained hidden,” said the WEF report. “Scientists predict that general-purpose AI will transform every part of the scientific discovery process over the next few years. Researchers can draw on past findings to envision new possibilities – AI allows connections to be made and inferences to be drawn that lie beyond the capacity of human minds alone.”
The report cited four major areas where AI will likely lead to major advances:
- Diagnosis, treatment and prevention of diseases;
- Novel materials that enable next-generation green technologies;
- Breakthroughs in the life sciences that extend current understanding of biology;
- Transformative leaps in how the human mind is understood, and many more.
Last year, the September 16, 2023 issue of The Economist similarly discussed “How AI Can Revolutionize Science” by accelerating the pace of scientific discovery, with three articles on the topic.
“Debate about artificial intelligence (AI) tends to focus on its potential dangers: algorithmic bias and discrimination, the mass destruction of jobs and even, some say, the extinction of humanity,” said the issue’s lead article. “As some observers fret about these dystopian scenarios, however, others are focusing on the potential rewards. AI could, they claim, help humanity solve some of its biggest and thorniest problems. And, they say, AI will do this in a very specific way: by radically accelerating the pace of scientific discovery, especially in areas such as medicine, climate science and green technology.”
A second article noted that AI “is already making research faster, better, and more productive,” while describing some of the recent AI-based achievements in drug discovery. For example, AI helped find new antibiotics, salicin and abaucin, for use against two of the most dangerous known antibiotic-resistant bacteria. “In both cases, the researchers had used an artificial-intelligence (AI) model to search through millions of candidate compounds to identify those that would work best against each ‘superbug’. The model had been trained on the chemical structures of a few thousand known antibiotics and how well (or not) they had worked against the bugs in the lab. During this training the model had worked out links between chemical structures and success at damaging bacteria. Once the AI spat out its shortlist, the scientists tested them in the lab and identified their antibiotics.
The Economist’s third article reflected on whether AI could also transform science itself , — not just generating new results but new ways of conducting the research necessary to generate new results. The article cited literature-based discovery (LBD) as a promising approach for new discoveries based on analyzing the scientific literature to suggest new potential relationships between existing knowledge. It referenced a 2019 paper by researchers at the UC Berkeley National Lab that showed that a machine-learning algorithm with no training in materials science was able to uncover new scientific knowledge by scanning 3.3 million abstracts of published papers in materials science.
The WEF report further noted that the countries with the most business and academic funding for the use of AI in scientific discovery from 2021-2023 were the US —$74 billion, China — $19 billion, India — $5.8 billion, the UK — $5.2 billion, and Germany — $2.5 billion; and the industries with the most AI funding for scientific discovery from 2021-2023 were Internet — $66.5 billion, software $24.1 billion, healthcare $10.1 billion, computer hardware $4.3 billion, and industrials $4.2 billion.
Finally, the WEF report includes set of questions designed to facilitate a deeper understanding of how the top 10 emerging technologies may help organizations identify strategic pathways for innovation and growth:
- If this technology achieves scale, how will it impact my organization’s operations and objectives?
- What are the potential applications of this technology in my organization’s current or future focus areas?
- What steps can my organization take to position itself as a key player in using and applying this technology effectively?
- What partnerships or collaborations are essential for success in this rapidly evolving technological landscape?
- Does the adoption of this technology imply significant shifts in our organization’s core business, talent structure or operational processes?
- How can my organization adapt its current strategy to harness the potential of this new technology as a driver of innovation, growth and/or impact?
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