UNESCO report - An algorithm in the room

UNESCO report 2026 on AI in education - The algorithm in the room : seeing and confronting the implications of AI for the future of education. 

Similar to the four scenarios from Singapore, summarised recently in this blog, this report collates 26 think pieces organised into 6 sections.  

After an introduction on the concept of 'algorithms everywhere' along with a discussion on educational purposes and the difficulties of aligning these algorithms with these. Each section presents several think pieces. 

Part one asks 'who will hold agency, autonomy and oversight'?

Part two on 'How will young people develop relationally, emotionally and cognitively?

Part three goes into 'what will be meaningful and relevant for pedagogy and assessment?

Part four moves in 'how will we think, question and express ourselves?

Part five poses the challenges on 'how will we govern education for the common good?

Part six closes with 'how might AI affect imagination about the future?

Each section has several articles, many speculative case studies. Topics discussed provide food for thought. They also provide good conversation starters and work well as thought provokers. 

The conclusion discusses the 3 horizons to empower education in algorithmic times - to see, to steer and to rewrite the algorithm.

Many of the key ethical and educational challenges are discussed through the report. Overall, a report to dip in and out of as interests in each topic arises.

ATAIN - Using LMS 'Nuku' to read and engage with policy - Dr. Lorena Gibson

An AI policy was designed for the Cultural Anthropology programme at Te Herenga Waka-Victoria University of Wellington. The presentation, hosted by ATAIN is provided by Dr. Lorena Gibson - lecturer in cultural anthropology.

The presentation is on 'Discussing AI use with cultural anthropology students'. Shared the guidelines for using AI - AI assessment scale (Perkins, Furze, Roe & MacVaugh, 2024) and how this has been used with her colleagues and students.

Her students work through the guidelines through a LMS module. There are 6 modules and students have to complete a quiz. Modules on [ need to complete before assessment!, AI, how and why to use, how to use AI in assessments, acknowledging Ai use, what not to do with AI, lecturer's own practice with AI.

Shared content of some modules which provide not only links and information but also examples which are of relevance to their context. Modeling by Lorena, and transparency from her examples, set up good practice and show authentic use of AI. 

Shared the section on using AI with course tutors. A pragmatic approach and for them to reinforce the advice provided through the AI modules. Good to see this as well as most of the time, teachers do not access information provided to students.

Interesting Q & A followed.

Important to also ensure students understand the difference between various assistive technologies and AI. Students are embarrassed or ashamed of using AI and clear, visible and educative information is always good practice. AI anxiety is very real and reported in a recent 2026 report on NZ students well-being.

Discussion on the challenges encountered in academic settings. In all, educators need to be sensitive to learners' difficulties. However, students need to engage in 'productive struggle', otherwise, they do not actually attain academic writing skills. 

Ai agents - use in education - Sacha Garrity from Unitec

Sacha Garrity, academic advisor in digital learning from Unitec, presents on how AI agents are used to support learning. The event is convened by Whitirea/Weltec. The work has received national recognition through the Tertiary ICT Association. 

Lee Smith from Whitirea/Weltec welcomed everyone. A karakia was offered before introductions to Sacha and Sharnell Aumua. Their presentation is on the Ako AI agents project: Nursing.

Agents have been used for about a year. The Ako AI agents project involved supporting kaiako to customise mini ChatCPTs, hosted on Cogniti to be used by ākonga anytime when required, help to be responsive to ākonga needs and provide additional support to kaiako. Agents are embedded in Moodle so students do not have to move between two platforms.

An overview of Cogniti provided. Agent development informed by design-based research and Te Tiriti o Waitangi health principles. Agent developed with kaiako through co-design.

Quality assuring the agent is important. Testing undertaken through a broader group of kaiako. Follow a test protocol - does it do what is intended, promote learning, avoid unwanted responses. Then test with ākonga and gain feedback.

In short - interative design and test, extended test by kaiako, followed by student test and final Q & A. 

Shared the nursing Ako AI. 3 nursing kaiako for each agent - (de-escalation agent, deteriorating patient and drug calculations. 4 developers and technical support. Stressed importance of drawing from and integrating Te Tiriti o Waitangi health principles.

Evaluation involved questionnaire, focus groups. Two iterations of testing and data collection for each agent. 

Went through the drug calculation agent capabilities - providing fomulae for conversions/rations and calculations. Provide tutorial support. A demo ensued - basically a quiz, providing support when the student is unsure or unable to do the calculation. 

ākonga feedback indicated that their learning confidence and competence was enhanced; user experience and design interactivity was appreciated; future AI tools and expanded learning support indicated - better integrations between LMS and Cogniti, videos to do revision, gamification / progress bar useful.

Demonstrated the deteriorating patient agent. A scenario agent. Two scenarios - hospital and community. Agent generates verbal and non-verbal behaviours, reactions based on student's response. New patient profiles generated at each use along with clinical/vitals. Feedback involved debrief, reflection and overall feedback - a challenge to build.

The agent has a 'toolbox' which is a link to 'help' in using the agent. Demo of agent in role as patient, perceptor and going through the debrief loop. 

Overall, positive responses from students. Students trusted using the agents as they were developed by their tutors. Interest in having a range of agents to support learning across the nursing curriculum. Support for more clinical scenarios prior to going out to clinical.

Q & A 

Oral responses - challenge with Te Reo Māori as pronunciation not the best. 

24/7 support useful. Agents able to provide more in-depth feedback when they have time or need to undertake practice. A safe place to practice or clarify concepts etc. can be done. 

Intentional learning is a key to developing how the AI agent is structured. Cogniti is user friendly and does not need IT degree to set up. 

Volume of use brought up. Currently Cogniti coping but not sure of maximum number if a agent is open to entire institution e.g. for learning, academic or library support.

Toolbox discussed and how it can be used intentionally. Access to documents supporting the learning can also be accessed through the toolbox.

Security aspects discussed. Important to only provide resources which are relevant and Cogniti itself should not have access to internal organisational data. 

Time from start to implementation averaged 3 - 4 weeks - mostly for SMEs to test, run staff test groups and gather feedback etc. 

Four future scenarios for training and adult education in Singapore - horizon 2035

This report - Four future scenarios for training and adult education in Singapore - Horizon 2035, is written by Ang, B.J., Huang, M. & Chen, Z., the Institute of Adult Learning, Singapore University of Social Sciences. 

The horizon in the report is less than a decade away. For some, a long way off, but with AI, perhaps a shorter window may apply. The report is also deeply integrated into the Singapore training and adult education ecosystem, Therefore, the report needs to be read with the context in mind.

After a preamble section, explaining the approach, philosophies and methodology for the report, the future scenarios are presented. These are:

- the trusted system - very much based on the current system whereby national standards and skilled educators provide and enable completion of qualifications. Currency is the main challenge as technology moves quickly and standards and educators struggle to keep up.

- AI skills network - based in AI being used to provide personalised, continuous and 24/7 available training. Human support and accountability become difficult to built in when required.

- the reputation economy - draws on expertise of trainers but depends on reputation and networks.

- skills market - AI is used to build capability but visibility and trust on credentials is uneven.

The scenarios are of interest as they show how difficult it is to see into the future, given the pace of change and the many challenges related to shifting an embedded credentialling system. Each country will need to undertake similar exercises, to test the efficacy and flexibility of their current training and qualification system and to think through implications, challenges and solutions from within their own contexts. 

A new direction for students in an AI world - report from Brookings Institute

This report - A new direction for students in an AI world: Prosper, prepare and protect was prepared by M. Burns, R. Winthrop, N. Luther, E. Venetis and R. Karim and published at the beginning of 2026 by the Centre for Universal Education at Brookings Institute.

The report focuses on the formal school context. It is just over 200 pages including appendices.

It is framed on the premise that at this moment in time, AI can be useful in enriching learning experiences.

The 3 pillars anchoring the report are:

- Prosper - to use AI carefully to enhance student learning

- Prepare -ensure not only educators and students, but the communities they serve are prepared through understanding the implications of AI on education.

- Protect - safeguards are important to assure privacy, safety, and support emotional and social development.

Discussion is undertaken on how AI can enrich education AND how AI can also diminish learning if overused without adequate guardrails.

Annex A provides a good summary of various AI literacy frameworks.

ASQA - principles for the responsible use of AI in VET

The Australian Skills Standards Authority (ASQA) have released their principles for the responsible use of AI in Vocational Education and Training (VET). 

The guidance is summarised on the site - AI use in VET.  The site contains links to the principles, case studies, how the principles were developed, and an AI transparency statement. The principles are found in the section on the responsible use of AI in VET. They are high level and examples/case studies are provided to inform how the principles can be applied to teaching and learning.