to thrive in the future tech-enabled global workforce. The introduction of and access to technology like ChatGPT is, by necessity, hastening the pace of change in approach. A recent Times Higher Education webinar,
‘Artificial
of global relocations in tech companies were for engineering roles, including software engineers, machine learning engineers, back- end engineers and developers, Cloud, Android, iOS and machine learning engineers. Significantly, a quarter of these relocations were at senior levels, including CEOs.
MORE MINDFUL MOBILITY? This is not new to those of us in global mobility who have supported the moves of tech professionals at every level internationally for the past decade and more. What is new is how the global mobility supply chain can dovetail with clients and adopt AI in a way that both optimises cost and employee experience through forecasting and feedback; and that proactively addresses and identifies immediate and broader risks, including access to mobility opportunities. “AI, including chatbots and
machine learning, will continue a recent trend of significant transformations
for Global
Mobility functions,” confirms Tom Richardson, VP of solutions consulting at Equus. “We have been using AI for some time in areas like virtual assistants and recommendation algorithms. But the recent rise in popularity of large- language models has increased awareness and the adoption of new ideas across a range of functions and expertise.” In relation to the risks associated
with AI and machine learning, which include ensuring all- important compliance and diversity, equity and inclusion considerations that reflect an organisation’s culture and mission, Tom Richardson says, “It is vital for teams to understand their responsibility in addressing challenges associated with AI and machine learning roll-outs, especially concerning algorithmic bias – which may lead to exclusion and discrimination. Primarily, this means ensuring that you have robust company governance frameworks with clear policies, ethical guidelines, and regular audits to current agreed standards.” This vital focus on critical
thinking and discernment is a reminder that AI and other technology are tools; not the answer on their own. “Transparency and ‘explainability’ in AI decision-making foster trust and accountability,” says Tom Richardson. These leadership qualities have been on the agenda for a while, reflecting the widening ESG focus. This is also something very much on the radar in international and higher education.
QUALITY QUESTIONS HOLD THE ANSWERS As Relocate Global’s series of international education webinars and our wider focus on innovation this year attests, educators around the world understand the importance of equipping the next generation with the skills needed
Intelligence and Academic Integrity’ featured panellists Benjamin Liu (University of Auckland), Jenny Davis (Australian National University), Christine Slade (University of Queensland) and Daniel Zhengkui Wang of Singapore Institute of Technology. It unpacked how to balance new technology with academic integrity. Webinar chair, Dene Mullen, introduced the panel, saying: “Generative AI is already testing the limits of what we can call honest and independent academic work and we’re really only just getting started. This is the hottest topic in higher education right now.” Calling it a paradigm shift in
teaching, panellists agreed that used in the correct framework, AI helps to personalise teaching and deepen knowledge. Students can use ChatGPT to ask simple questions, which frees up time for students and tutors alike to “deal with the big questions”. Asking quality questions, developing a critical mindset and using data towards achieving a particular goal are all skills readily transferable to the future workplace. ChatGPT and similar tools are also allowing for rapid translations and greater inclusion. It is opening classrooms and lecture halls up in new ways, bringing with it the ability potentially for greater cross-cultural understanding and knowledge sharing. Raising the level of expectation
around what AI can deliver, especially as machine and natural language AI depends on the quality of questions asked of it, is also vital. AI in academia hinges on “helping staff and students to become ethically and AI literate”, as well as making it more substance- and personal development-focused, rather than simply outcome-oriented. This last point has a message for
all of us. What outcomes do we as individuals, school and education communities, and business leaders want from AI? The answer is critical for balancing the risks with the rewards.
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THINK GLOBAL PEOPLE AI
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