Quantum Technologies and the Future of Learning

Photo by © Ahmad Triwahyuutomo on Adobe Stock

Join the live webinar, part of the ITCILO Pioneers Forum, on Tuesday, 15 April 2025!

• Time: 11:00-12:30 CET
• Location: online and on campus

This dynamic session features keynote speaker Celeste Drake, Deputy Director-General of the ILO, and an expert panel from IBM Quantum, UNESCO, and Politecnico di Torino. Discover what quantum breakthroughs mean for the world of work, and how institutions can prepare for the future.

Spots are limited — register now to secure your virtual seat.

• The ILO 2024-2025 Programme and Budget Outcome A stresses enhanced knowledge, innovation, cooperation and communication as means of action to advance social justice.
• More specifically, output A.3 foresees the creation of the Innovation Sparks initiative facilitated by the International Training Centre of the ILO (ITCILO) to support innovation projects carried out by different organizational units, at headquarters and in the regions.
• The Innovation Sparks Initiative is aligned with UN system-wide efforts to actualize the UN Secretary-General Antonio Guterres’ vision of a “modern United Nations system, rejuvenated by a forward-thinking culture, and empowered by cutting-edge skills” through a fusion of data, innovation, digital, foresight and behavioural science expertise. It thus provides a technical testbed for an exploration of the potential use cases of emerging technologies for learning and capacity development.
• As part of the Innovation Sparks Initiative, ITCILO has commissioned action research on the potential impact of quantum technologies on the future of learning and capacity development.
• In this report, the authors argue that while caveats on the speed and scale at which these quantum technologies develop apply, it is high time for people in the world of work to build a basic understanding of their potentially disruptive impact on their lives – and the way they learn.
• The report also provides examples where quantum technology applications like quantum sensors are already applied in learning situations, and cautions that technological breakthroughs including in fields like quantum computing are coming within reach.

The report had as its primary aims:

• the codification of an emerging technology taxonomy for the ITCILO;
• a comprehensive mapping of quantum technology domains of interest for capacity development providers;
• an identification of priority areas for action up to 2030.

Yet, it went well beyond the scope of its declared aims to provide broader reflections and considerations on the future of training and capacity development, bound to generate curiosity across the UN training ecosystem and beyond.

With the aim of striking a balance between oversimplification and complexity when it comes to exploring the realm of quantum technologies, the report further answers a sub-set of questions including:

• Can there be a coherent and consistent terminology that can help teaching, learning and capacity development providers explore the “emerging technologies” domain, and retrieve information on quantum technologies with sufficient precision and accuracy? Could this be distilled into an ITCILO taxonomy informing the Centre (and other institution)’s work streams on emerging technologies, training and capacity development?
• Given the numerous discrete knowledge domains the term “quantum technologies” encompasses, how many and which ones should teaching, learning and capacity development providers qualify as priorities in their work streams between now and 2030?
• Out of the quantum technology domains identified as worth monitoring if not directly elevated to the status of programmatic priority, in relation to which ones should teaching, learning and capacity development providers help build readiness over the next biennium and by 2030?

• The compiling of the report relied on desk reviews of the existing secondary literature on quantum technologies as made available by public and private sector actors, supported by a series of expert interviews with quantum technology research groups, commercial providers of quantum computing, and innovation experts at ITCILO.
• The creation of a new and updated ITCILO taxonomy for emerging technologies – including quantum technologies – followed the desk review and selection of elements identified in other seven already existing taxonomies that have gained recognition primarily in the European Union, the United Kingdom, and the United States. The report recognizes the limitations dictated by its scope and acknowledges that the ambition to build a truly globally-applicable taxonomy would require opening up to the work of leading quantum technologies research centres based in the Global South.

The proposed emerging technology taxonomy is reproduced below

• Last in the report is the identification of one specific strand and one overarching quantum technology topic considered most relevant to the practical needs of the ITCILO and other teaching, learning and capacity development providers by 2030. The specific strand is the exploration of current and near-term Quantum AI/ML algorithm capabilities for learning, while the specific topic is a reflection on what it means to develop quantum capacity, i.e., “quantum readiness” through training.
• This concludes a more in-depth assessment informed by desk reviews of learning-related applications in existing sources, patents and academic publications, analysis of existing AI/ML algorithms, and informal discussions held with selected key informants on learning-related applications for quantum (at the ITCILO, D-Wave, Google Search, IBM, Quantinuum, Leiden University, Quantum Delta, NL SURF Network).

• Quantum sensors, biotechnology, and communication/cryptography solutions already exist on the market, but have relatively few short-term applications for the delivery of capacity development or training. Quantum computing and related algorithms provide more promise for this sector in the short-term. However, priority use cases in quantum computing typically emphasise sectors such as logistics, financial portfolio optimisation, drug discovery, and simulating physical systems.
• Quantum computing use cases to support the delivery of training can be identified in principle, but they typically rely on multiple breakthroughs relative to the present day. The future progress of R&D is hard to identify, especially with the funding and talent working in the field, but most corporate roadmaps place the necessary breakthroughs for these use cases in the 2030s rather than before.
• The report argues that one should not expect a single overnight breakthrough to drive the commercialisation of quantum technologies in the target use cases. For instance, innovations in quantum computing remain bottle- necked by multiple hardware and theory advancements (e.g., logical qubit scale, data encoding, algorithm design), thereby reducing the chances of black-swan breakthroughs occurring in the same way that software/statistical breakthroughs enabled by big data supported the seemingly sudden appearance of Generative AI onto the world stage.
• Commercial use cases for quantum computing nevertheless exist today. They are available to a niche audience of users with access to proof-of-concept budgets from the high-10,000s and mid-100,000s of US dollars, with full applications often requiring larger budgets. Such users are typically already making use of sophisticated computing technology to elaborate solutions to complex problems, and who may anticipate significant absolute gains from small performance improvements.
• At present, training providers do not have problems that are directly ready to benefit from such technology, although steps can be taken to be ready to benefit in the future. For global stakeholders more generally, particularly those located in the Global South, other tried and tested methods may continue being preferred until the commercial circumstances for the large-scale, accessible use of quantum technologies are present.

• World-leading quantum solution providers and developers have already expressed a general willingness to explore the feasibility of designing and commercializing quantum-empowered capacity development solutions; this nonetheless remains an entirely new area of exploration in the quantum realm, one for which close collaboration with relevant industry and/or institutional partners may be sought after and encouraged.
• At this stage, providers of training can look to general use cases which might be accelerated by future quantum technologies, but where current non-quantum technologies might not be capable enough to deliver the desired benefit. For instance, privacy concerns, form factor constraints, or sensitivity requirements beyond existing technology might motivate a provider to look towards future quantum sensor technology applied in the classroom. However, such explorations need to start with using existing Internet of Things technology to test their ambitions and understand which limits matter.
• Similarly, algorithms for personalised/adaptive learning could be accelerated with quantum machine learning capabilities hoped to come on stream in the 2030s.
• Before any quantum applications can be examined, training providers would already be working extensively with current technologies, to build up sophisticated training datasets, to understand the strength and weaknesses of the technology relative to the pedagogic ambitions, and assess what level of budget investment might be justified to improve performance. Just because future quantum technology has the potential to help does not mean it is necessary or cost-effective to move beyond classical technologies.
• Researchers working in the related areas of forecasting economic/workforce trajectories or simulating supply chains may also be well-placed to specify models and datasets that they would like to analyse, but which are bottle-necked by their current compute capabilities. Such ambitions and model specifications would provide a fertile foundation for early conversations with quantum computing providers, e.g. to understand which aspects of the models might be amenable to a quantum speed-up or which types of quantum breakthrough should be monitored before the technology is ready to make a material contribution.

It is yet to be seen what quantum technology applications can offer to the world of training and capacity development. The wait for further hardware breakthroughs and commercially deployable solutions seems to limit the scope of action of capacity development providers who are still currently questioning whether, when, and how quantum technologies will become essential to the provision of high-quality and effective training.