Workshops

AI Readiness for Sustainable Work

From Human-AI Collaboration to Green Talent Capability 

Facilitator: 

• Dr Sean Kruger, University of Pretoria, sean.kruger@up.ac.za

This workshop is designed for delegates who want to move beyond broad claims about AI adoption and focus on practical readiness. The session uses an AI readiness diagnostic as the starting point, then connects that baseline to human judgement and green talent capability. The central question is: are we ready to use AI in ways that improve work and build future focused capabilities?

Toolkit reference: HAC Readiness Instrument / Global Toolkit

Workshop purpose

The concern is that access to AI tools does not automatically mean readiness. A person may be able to open a tool, produce an answer and move faster, while still lacking the ability to verify the output. Not to mention how to recognise risk, protect sensitive information or understand when human judgement must override automated assistance.

This workshop treats AI readiness as a work capability. Delegates will explore where AI can genuinely augment work, where human expertise remains central and where over reliance can create weak decisions, deskilling, exclusion or reputational risk. The session brings a sustainability lens into the conversation by asking how AI readiness connects to green talent.

What delegates can expect to achieve

Read their current AI readiness more clearly: Delegates will use the readiness framing to reflect on their own confidence, capability and institutional context. This includes applied AI literacy, verification behaviour, governance awareness, cyber aware use and future of work readiness.

Connect AI adoption to green talent capability: Delegates will consider how AI can support sustainable work through better evidence use, reporting, resource efficiency, circularity thinking, skills planning and transition readiness, without reducing sustainability to a technology slogan.

Identify the gaps that matter: The session will help delegates distinguish between tool access, skills, process design, governance, data quality, leadership support, infrastructure and training gaps. This is important because many AI projects fail less because of the tool and more because the surrounding work system is not ready.

Clinical Innovation and Entrepreneurship 5.0

Co-Designing a Context-Appropriate Roadmap for Sustainable Health Innovation and Entrepreneurship

Facilitator: 

• Dr Deborah Oluwadele, University of Pretoria, deborah.oluwadele@up.ac.za

Medical entrepreneurship is a business model focused on medicine that creates new business opportunities by meeting the needs of stakeholders in the domain. This is stated to sustain the functionality, quality, and performance of the healthcare systems with scope covering medical tourism, healthcare entrepreneurship, medical courier services, medical writing services, medical waste disposal services, surgical innovation, public health entrepreneurship, and medical escort services, etc.

This workshop will answer the question: How can clinical entrepreneurship be conceptualized, enabled, and evaluated as a foundation for transformative public health innovation in Africa? By mapping context-specific variables such as premises, pillars, and metrics, stakeholders can develop insights into ethical, sustainable, and scalable innovation practices and modalities for clinical innovation to support sustainable entrepreneurship in Africa. 

The following question will be discussed during the workshop:

1. What are the premises for clinical innovation and entrepreneurship in Africa?

2. What are the pillars that could drive clinical innovation and entrepreneurship in Africa?

3. What are the metrics for each pillar of clinical innovation and entrepreneurship in Africa?

4. What are the suitable modalities to drive clinical innovation and entrepreneurship programs in Africa?

These questions help uncover the foundational, strategic, operational, and evaluative dimensions of clinical innovation and entrepreneurship within the African context, moving the discussion beyond encouraging innovation, toward understanding what enables it, what sustains it, how to measure it, and how to implement it effectively.

Partnership between Human and AI in the Society of the Future

Deriving ways for human and AI interaction and collaboration

Facilitators: 

• Prof Knut Hinkelmann, FHNW University of Applied Sciences and $arts Northwestern Switzerland, knut.hinkelmann@fhnw.ch

• Dr Henk Pretorius, University of Pretoria, henk.pretorius@up.ac.za

As Artificial Intelligence progresses, the understanding of the collaboration and mutual responsibilities of human and AI in society and business becomes crucial. This will have an influence on work organisation, but also on human skill development and education. The more tasks are delegated to AI, the higher the risk that humans will lose the required skills. 

There are different levels of cooperations ranging from different levels of human AI integration, ranging from (1) full automation, where technology works independently from human, via (2) human in the loop of AI where AI takes the lead und humans taker over tasks the AI is not capable, (3) AI in the loop of human where AI supports humans by providing information or solving subtasks to (4) true collaboration human and AI synergetically coordinate each other and make decisions together. The appropriate interaction and collaboration between AI and humans can be determined by criteria such as their respective capabilities and limitations, trust and transparency, accountability, and ethical considerations. In addition, there are also aspects of the context as well as long-term considerations, such as the loss of innovation capabilities when business-critical tasks are delegated to AI.

This workshop will explore the evolving partnership between humans and artificial intelligence (AI) in shaping a human-centered society. It will delve into the dynamics of human-AI collaboration, examining the roles and responsibilities of both, the shift in human skills in response to AI's increasing capabilities, and the ethical considerations of such partnerships. The workshop shall 

• identify criteria for appropriate work assignment, responsibilities, and collaboration between humans and AI.

• derive ways of interaction and collaboration in various contexts. In the teaching and education settings, for example, AI can take the roles of a tutor, challenger, reviewer, idea provider, etc.

The workshop will consist of two introductory presentations and an interactive part in which participants discuss relevant questions.