AI use in qualifications recognition: five key factors

According to UNESCO, the number of students enrolled in higher education worldwide doubled between 2000 and 2019, reaching 235 million, while the number of internationally mobile students tripled to six million, with many studying outside their home regions.

The recognition of academic qualifications is a key element to support inclusion, mobility and access to higher education and in order to be fair and non-discriminatory, the role played by each convention on recognition is crucial in this regard.

With the aim of supporting fair recognition of qualifications, every UNESCO region in the world adopted a revised regional convention on recognition of qualifications, and in 2023 the UNESCO Global Recognition Convention entered into force.

Together with the need to provide timely, fair and transparent recognition of qualifications to serve the needs of students, graduates and professionals, higher education institutions worldwide are facing many changes and challenges. Among them, there are the potential risks and opportunities associated with digital transformation and the use of artificial intelligence in higher education.

Here we highlight five core elements to support discussion on AI and recognition at interregional and global level, in line with regional regulatory frameworks and key Council of Europe and UNESCO documents.

Human-centred evaluation

The main goal of each regional convention is ensuring barriers to recognition are removed. The use of AI technology in evaluation may have the opposite effect because it mimics past decisions and uses an algorithm to predict the outcome.

Recognition requires an evaluative judgment that only a human being can provide. Human-centred evaluation provides assurance that a qualification is fairly assessed. The use of AI in general and the process of digital transformation in the recognition sector should serve the enforcement of this right, without forgetting the individual learning pathway.

Human-centred use of AI is seen in the light of respect for human rights, the rule of law and democracy. Being centred on the ‘human being’ is seen also in the perspective of supporting the recognition officials and credential evaluators in the recognition process.

Since it has an impact on determining the educational and professional course of a person’s life, the final decision on assessment and recognition should always be made by a human being and not by any ‘artificial’ mechanism.

Robust process and data governance

AI can potentially simplify repetitive and mechanical steps. Nonetheless, it should be taken into account that simplification of recognition procedures must be carefully regulated by human rationality in order to avoid oversimplification.

Conceptualising and designing recognition processes and workflows, from the input phase to the output phase, means identifying the need for simplification, automatisation and improvement; reengineering the process, with a participatory and inclusive approach; and involving recognition officials and professionals.

These are important steps in the digital transformation process of an institution, and this preliminary assessment phase is vital for the effective and solution-oriented implementation of technological and AI applications.

AI doesn’t work in isolation but can be used in combination with other technological tools that can be fit for purpose according to need. Combined with this, solid data architecture and governance are a precondition for sound AI implementation.

Research and innovation

As a process that supports the right of individuals to access higher education and progress along their educational pathway, recognition is a component serving quality higher education, a key Sustainable Development Goal.

A systems-level approach to AI in education which sees the cooperation of national authorities, higher education institutions, national information centres and all the actors in the higher education systems is an important dimension supporting quality recognition systems.

Furthermore, research and innovation are a critical component to ensure the up-to-date, reliable and future-proof development of AI and the digital transformation process in general beyond AI. In this sense, synergies and cooperation with higher education institutions as innovation drivers could improve the quality of the recognition process.

AI literacy and training

Relevant skills and updated knowledge are crucial in the digital transformation process. Training to upskill professional and credential evaluators working in the recognition field is an essential dimension of an effective digital transformation process.

AI literacy, knowledge of key regulatory frameworks at a national and international level and of the ethical implications of the use of AI in the recognition, access and admissions process, together with basic data analysis and data interpretation capabilities are an important part of the knowledge, skills and competences required by credential evaluators, but also by the governance of institutions, and their different role, education and expertise should be taken into account.

Networking and cooperation

Networking, cooperation, peer support and the exchange of practices and information are important driving factors for building a community of practice in the recognition field at the institutional, national and international level.

All of these factors can play an important role in supporting the application of AI that is ethically consistent, human-centred and able to support a quality recognition process.

Lamine Guèye is president of the Addis Recognition Convention Committee. Dolly Seow-Ganesan is president of the Tokyo Recognition Convention Committee. Luca Lantero is president of the Lisbon Recognition Convention Committee and Gonzalo Baroni Boces is president of the Buenos Aires Recognition Convention Committee. This article is based on a paper drafted by the above four presidents of UNESCO Regional Conventions on Recognition of Qualifications.

This article is a commentary. Commentary articles are the opinion of the authors and do not necessarily reflect the views of University World News.