top of page

Weak signals in Science and Technologies – 2024

  • Huw Williams
  • Apr 10
  • 5 min read

The EC’s Joint Research Centre (JRC) has recently published a report on technology horizon scanning they conducted during 2024, identifying weak signals in science and technology.  The report identifies 221 emerging technologies of interest, clustered into 12 groups.


It also identifies the geographic region in which the technologies are being developed, and the number of patents filed. This leads it to recommendations in its Executive Summary on how to improve the EU’s position within these rankings.


The report has an interesting attempt at quantifying weak signals, through “scientometric indicators”.  The logic of this is that the number of references to a technology ticks along at a low level over time but starts to be of interest as references start to increase.



Clearly, we are not going to be able to cover all 221 weak signals in this short review.  Instead we have picked out some themes in each of the 12 clusters on a subjective assessment of their novelty and importance.


Advanced Materials and Advanced Manufacturing

Several weak signals in the area of multifunctional advanced materials were identified, such as Engineered Living Materials. There are also developments to address energy efficiency and environmental impact, such as Solid-State Lithium Metal Batteries and Potassium Hybrid Ion Capacitor Batteries. Several additive manufacturing approaches were also identified. Interestingly, JRC pick out a concept they call Industry 5.0, a transformative manufacturing paradigm that “seamlessly merges human ingenuity with artificial intelligence”.


Aerospace

Key themes in this cluster are advanced communication systems (6G in space), automation, eVTOL and sustainability (alternative fuels).

 

Mobility and Transport

AI and advanced communications also feature strongly in this cluster, examples being 6G Vehicle-to-Everything (V2X) communication and pedestrian trajectory prediction systems. Smarter charging protocols for electric buses and the integration of photovoltaic systems into vehicles are part of a broader movement towards green mobility. Wider concepts such as the 15-minute city are also observed.

 

Digital Twin

The concept of integrating different data sources into a digital model is seen being applied to a wide range of situations – cities, agriculture, healthcare, transport and quantum systems. Digital twins may be self-updating and used to examine whole lifecycles and explore different scenarios.

 

Artificial intelligence and machine learning

JRC note innovations in data privacy, security, explainability and ethics. Federated Machine Learning, Explainable AI, and advanced cryptographic methods are picked out. They also note an emphasis on Human-AI Collaboration and Ethics.

 

Information and Communication Technologies

A key theme is application of AI and ML to push the boundaries of performance, security, and efficiency. Technologies such as adversarial defence, deepfake detection, few-shot learning[1], and single-chip neuromorphic computing[2]. Security and privacy also emerge as prevailing trends across a range of other technologies. Another trend is interoperability and integration: Open RAN (Radio Access Network), the metaverse, and vehicular edge computing.

 

Medical imaging

Five key themes are identified:


  • enhanced visualization, enabling better diagnosis and treatment

  • advanced image analysis, leveraging machine learning and deep learning to analyse medical images and facilitate better identification of patterns and markers

  • non-invasive techniques, reducing risks and discomfort

  • personalized medicine, treatment strategies that are more tailored to individual patient needs; and

  • multimodal imaging, providing a more comprehensive understanding of complex medical conditions.

 

Therapeutics and biotechnologies .

This cluster also features precision medicine and personalized therapies. Immunotherapy technologies are at the forefront of harnessing the body’s immune system to target and eliminate cancer cells. Regenerative Medicine and tissue engineering are also prominent, with innovations such as 3D printing for wound management.

 

 e-Health

A key theme is automating medical data analysis, aiming to improve disease detection, treatment planning, and prediction of disease progression. Again, this aligns with the trend towards personalized medicine and precision health, emphasizing the significance of data-driven healthcare and analytics.  The Internet of Medical Things and blockchain for electronic health records are driving the shift towards digital health and telemedicine, enabling remote patient care, secure data exchange, and improved healthcare access.

 

Environment and Agriculture

Regenerative agriculture, circular food systems, and building decarbonization support the need to achieve sustainability goals. The use of digital twins and simulation is also becoming increasingly prominent to enable more accurate predictions and optimizations. Technologies such as cultivated meat and e-DNA metabarcoding are yet to secure public acceptance.

 

Energy

Sustainability is the key concern in this cluster: reducing greenhouse gas emissions, increasing energy efficiency, promoting renewable energy sources. JRC also see the importance of integration and systems thinking in achieving sustainability goals e.g. positive energy districts, smart local energy systems or fifth-generation district heating. There is also a focus on local and decentralized energy solutions.

 

Quantum and Cryptography

The emerging technologies in the quantum category reflect a concerted effort to translate the theoretical promise of quantum science into tangible advances across multiple domains. There is a need to address quantum noise and the need for effective error correction. JRC also note innovations in superconducting qubits, and topological quantum computing, and the interim emergence of hybrid models that integrate classical and quantum computing,

 

Other analysis

There’s a great deal more impressive analysis in this report. For each of the clusters it explores “technology radars”, “Revealed Technology Advantage” (ie leading countries), main actors and international collaborations.

 

It is interesting that out of all this technology analysis, JRC’s Executive Summary focusses on the geo-economic consequences. USA and China alternate in the top ranking in terms of participation in top 1% scientific journals for 8 of the clusters. While not leading in any of the clusters, Europe contributes significantly to each of them. European organisations publish as many scientific articles as Chinese and US organisations, but file fewer patents to protect their research results.

 

Overall, JRC identify converging high-level trends:


  • emphasis on sustainability and environmental impact

  • interdisciplinary integration

  • incorporation of AI and machine learning into various technology fields

  • advancements in personalization and precision, particularly in healthcare

  • non-invasive and minimally invasive approaches

  • digitalization of systems and data-driven decision-making

  • heightened focus on security and data privacy.

 

This demonstrates again our contention that technology is just one of the fundamental drivers of change affecting possible futures, and that a more wide-ranging approach is needed to make “robust decisions in uncertain times”.


Written by Huw Williams, SAMI Principal


The views expressed are those of the author(s) and not necessarily of SAMI Consulting.


Achieve more by understanding what the future may bring. We bring skills developed over thirty years of international and national projects to create actionable, transformative strategy. Futures, foresight and scenario planning to make robust decisions in uncertain times. Find out more at www.samiconsulting.co.uk


 


[1] Few-shot learning is a machine learning framework in which an AI model learns to make accurate predictions by training on a very small number of labeled examples. It's typically used to train models for classification tasks when suitable training data is scarce.

[2] Neuromorphic computing is a field that designs hardware and software inspired by the human brain, aiming to create efficient and powerful computing systems, potentially leading to breakthroughs in AI and beyond

Comments


bottom of page