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Systems thinking calls for a shift of our mindset from seeing just parts to seeing the whole reality in its structured dynamic unity and interconnectedness. Systems thinking fosters a sensibility to see subtle connections between components and parts of reality, especially the free enterprise capitalist system (FECS). It enables us to see ourselves as active participants or partners of FECS and not mere induced factors of its production–distribution–consumption processes. Systems thinking seeks to identify the economic “structures” that underlie complex situations in FECS that bring about high versus low leveraged changes. A system is strengthened and reinforced by feedback of reciprocal exchanges that makes the system alive, transparent, human, and humanizing.

In Part I, we explore basic laws or patterns of behaviors as understood by systems thinking; in Part II we examine the basic archetypes or structured behaviors of systems thinking; in both parts we strive to see reality through the lens of critical thinking to help us understand patterns and structures of behavior among systems and their component parts. In conclusion, we argue for compatibility and complementarity of critical thinking and systems thinking to identify and resolve management problems created by our flawed thinking, and sedimented by our wanton assumptions, presumptions, suppositions and presuppositions, biases, and prejudices. Such thinking will also identify unnecessary economic and political structures of the self-serving policies we create, which imprison us.

The interaction of systems through a designated control channel has improved communication, efficiency, management, storage, processing, etc. across several industries. The construction industry is an industry that thrives on a well-planned workflow rhythm; a change in the environmental dynamism will either have a positive or negative impact on the output of the project planned for execution. More so, raising the need for effective collaboration through workflow and project planning, grid application in construction facilitates the relationship between the project reality and the end users, all with the aim of improving resources and value management. However, decentralisation of close-domain control can cause uncertainty and incompleteness of data. And this can be a big factor, especially when a complex project is being executed.

In this chapter, a general introduction on artificial intelligence (AI) is given as well as an overview of the advances of AI in different engineering disciplines, including its effectiveness in driving the United Nations Sustainable Development Goals (UN SDGs). This chapter begins with some fundamental definitions and concepts on AI and machine learning (ML) followed by a classification of the different categories of ML algorithms. After that, a general overview of the impact which different engineering disciplines such as Civil, Chemical, Mechanical, Electrical and Telecommunications Engineering have on the UN SDGs is given. The application of AI and ML to enhance the processes in these different engineering disciplines is also briefly explained. This chapter concludes with a brief description of the UN SDGs and how AI can positively impact the attainment of these goals by the target year of 2030.

Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.

Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.

Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.

Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.

An ecologically sustainable future calls for fruitful dialogues between spirituality, modern science and policymaking at large. What could be that connects them all? We found out that ideas about holism exist across time, space, culture and thinkers – ranging from mathematics, philosophy, sociology, medicine, education, religion and quantum physics to finding its roots in ancient Indian Vedic tradition and later usage in Greek and Roman cultures.

This chapter takes a look at the history and intricacies of two seemingly distinct but interconnected fields – spirituality and modern science, particularly quantum science – with an aim to uncover what these fields can teach us about the idea of holism. This chapter, therefore, highlights one of the most fundamental and profound spiritual principles of the unity and interconnectedness of the entire universe – encapsulated in the concept of holism – and its practical applications in approaching sustainable development. We hope to ignite further research on this topic.