Harmful tipping points in the natural world pose some of the gravest threats faced by humanity. Their triggering will severely damage our planet’s life-support systems and threaten the stability of our societies.
In the Summary Report:
• Narrative summary
• Global tipping points infographic
• Key messages
• Key Recommendations
Executive summary
• Section 1
• Section 2
• Section 3
• Section 4
This report is for all those concerned with tackling escalating Earth system change and mobilising transformative social change to alter that trajectory, achieve sustainability and promote social justice.
In this section:
• Foreword
• Introduction
• Key Concepts
• Approach
• References
Considers Earth system tipping points. These are reviewed and assessed across the three major domains of the cryosphere, biosphere and circulation of the oceans and atmosphere. We then consider the interactions and potential cascades of Earth system tipping points, followed by an assessment of early warning signals for Earth system tipping points.
Considers tipping point impacts. First we look at the human impacts of Earth system tipping points, then the potential couplings to negative tipping points in human systems. Next we assess the potential for cascading and compounding systemic risk, before considering the potential for early warning of impact tipping points.
Considers how to govern Earth system tipping points and their associated risks. We look at governance of mitigation, prevention and stabilisation then we focus on governance of impacts, including adaptation, vulnerability and loss and damage. Finally, we assess the need for knowledge generation at the science-policy interface.
Focuses on positive tipping points in technology, the economy and society. It provides a framework for understanding and acting on positive tipping points. We highlight illustrative case studies across energy, food and transport and mobility systems, with a focus on demand-side solutions (which have previously received limited attention).
Detection of acceleration in radicalisation and polarisation, which, as was established in Chapter 2.3, could be exacerbated by Earth system destabilisation, can be pursued using similar machine learning and social network analysis approaches applied to user-generated online content (Gaikwad et al., 2022). Conflict early warning systems (CEWS) are well established and researched (Rød et al., 2023). A notable example is the ACLED (Armed Conflict Location & Event Data Project) CAST platform (Conflict Alert System), which is meant to predict violent events up to six months in advance. These CEWS could be enhanced with new ML/AI-based models that can capture coupled climate-conflict-tipping processes (Guo et al., 2023; Guo et al., 2018).
Finally, ML/AI-based tools are also emerging to develop early warning systems to predict financial crises (Samitas et al., 2020), which, as was established in chapter 2.3, could be triggered by Earth system destabilisation. Near real-time monitoring is also feasible with these types of data and methods, as demonstrated by the GDELT project, which monitors the world’s broadcast, print and web news from around the world in 100 languages for significant events and trends. With respect to ethical questions around surveillance and privacy concerns, it is important to emphasise that early warning systems focus on broad patterns and do not track individuals, so personally identifiable information is not included in these systems.