Early launch Human-AI collaboration in Engineering
The media are currently debating urgent concerns with AI data breaches when rogue AI agents used deception techniques to access external developer services they weren’t programmed to, communicated with people and attempted to insert malicious code into open-source software. Governments are reviewing legal options such as ‘kill switch legislation’.
Human collaborators have a lot of continuously changing complex issues to figure out in a very compressed timeline. The integration of AI into life, education, work and government is so fast that it will require a gigantic and continuous level of complex enquiry, analysis and discussion. The race is on by academics such as myself – as well as governments and industry experts – to ensure, as much as humanly possible, that AI is secure, ethical, sustainable and verifiable.
In the meantime, we are receiving clear guidance from the WEF for an imminent need to start preparing ourselves and our students for the way AI will alter our education system, jobs, the commercial world and our economy. It is a lot. How do we prepare ourselves and our students for a future that is so confusing and uncertain?
Our Engineering students are particularly well poised to contribute positively to understanding, adapting and designing optimal human-AI collaboration because Twenty-first Century Skills are core to our updated programmes. I want to keep supporting students in their journey. In his 2016 TED Talk, Tom Hulme talks about desire paths, real life, launch to learn and the need to stay responsive. Designers need to launch early, observe users’ real life ‘desire paths’ and review the divergence of design and user experience and continuously review and adapt.
Only 20% of university students agree they are being prepared for a world shaped by AI.
This has shaped my personal approach to curriculum development. In 2019 I designed a pilot Project-Based Learning module (Entrepreneurship 1) in the Engineering Department as a forerunner to update all engineering programmes to integrate 21st Century Skills development using an experiential, entrepreneurial learning methodology. This was an extremely vulnerable experience for the students and I, as a relatively early career academic experimenting with a new methodology combining PBL and EntreComp.
Some students loved it. Some found the open-endedness difficult. I led the design and construction of a new Engineering Maker Space to enhance creativity, collaboration and exploration for success during industry 5.0. This remains the heart of the updated engineering programmes. I continued to lead this process of review and redesign for all Stages and the final cycle finished in July 2024 with the successful roll out Stage 4 of the engineering programmes. I have since led a Students as Change Agents (SACA) project to mentor students in developing EDI for their Engineering Maker Space at UNIMAKER 2025.
Academics need to focus their attention on shaping a more responsive, inclusive and future-ready education system thriving in collaboration with AI.
How do we prepare ourselves and our students for a future that is so confusing and uncertain?
Co-designed as a pilot for cultivating human-AI collaboration, Entrepreneurship 2 kick-started with a project launch including lectures and workshops with academic and industry collaborators in AI and ML. This launch introduced industry-validated AI tools at an early stage, allowing us to map the organic ‘desire paths’ students took during mock venture creation. The outcomes were highly encouraging. Students were enthused by a teambuilding workshop and case studies of implementation of emerging technology. They completely immersed themselves in AI and ML environments, comprehending AI capabilities and building commercial ventures with the essential features needed to solve a core problem. They enjoyed the freedom to research new innovative areas to pursue within their mock company teams. Students requested more facilitation to master individual technical competencies in ML and AI during the entrepreneurial process to promote in their final website sales pitch. A human-AI collaborative deep dive workshop with HASS colleagues is now planned on the most popular free AI tools, culminating in a pitch for pros, cons and case study applications for all teams to benefit from during their PBL projects.
This clear student demand for knowledge and technical application of AI mirrors broader empirical research across higher education. Recent tracking data from King's College London indicates that only 20% of university students agree they are being prepared for a world shaped by AI. Furthermore, the World Economic Forum explicitly states that comprehensive instruction regarding AI capabilities must be emphasised in education.
Students are acutely aware of their need for both Human-Centric skills and AI competence. In an educational landscape accelerating at such pace, academic perfection cannot become a barrier to learning. We must embrace a culture of early launch action, experimentation, observation, and iteration to nurture successful human-AI collaboration.
