The development of plans of action in disaster response scenarios is a time-consuming process. Large Language Models (LLMs) offer a powerful solution to expedite this process through in-context learning. This study presents DisasterResponseGPT, an algorithm that leverages LLMs to generate valid plans of action quickly by incorporating disaster response and planning guidelines in the initial prompt. In DisasterResponseGPT, users input the scenario description and receive a plan of action as output. The proposed method generates multiple plans within seconds, which can be further refined following the user's feedback. Preliminary results indicate that the plans of action developed by DisasterResponseGPT are comparable to human-generated ones while offering greater ease of modification in real-time. This approach has the potential to revolutionize disaster response operations by enabling rapid updates and adjustments during the plan's execution.

AI is being increasingly used to aid response efforts to humanitarian emergencies at multiple levels of decision-making. Such AI systems are generally understood to be stand-alone tools for decision support, with ethical assessments, guidelines and frameworks applied to them through this lens. However, as the prevalence of AI increases in this domain, such systems will begin to encounter each other through information flow networks created by interacting decision-making entities, leading to multi-AI complex systems which are often ill understood. In this paper we describe how these multi-AI systems can arise, even in relatively simple real-world humanitarian response scenarios, and lead to potentially emergent and erratic erroneous behavior. We discuss how we can better work towards more trustworthy multi-AI systems by exploring some of the associated challenges and opportunities, and how we can design better mechanisms to understand and assess such systems. This paper is designed to be a first exposition on this topic in the field of humanitarian response, raising awareness, exploring the possible landscape of this domain, and providing a starting point for future work within the wider community.

Many organizations across the globe are seeing the potential opportunities of having a presence in the Metaverse and are beginning to prepare their digital assets accordingly. With rapid expansion and more details coming to light on the value the Metaverse may bring, innovative business leaders must start evaluating if their organization is prepared. We all know the world has changed significantly in the wake of the pandemic, and companies are leaping toward hyperautomation. Are digital twins of headquarters, products, stores, and even customers and employees the next wave? Many experts seem to think so, and this piece will take a deeper look into why.

There is a rise in the number of natural disasters happening all over the world. According to the National Oceanic and Atmospheric Administration, there were 16 natural disasters in 2017. The cost of all the damages is in the billions. The amount of destruction they cause is devastating and it has left many of us wondering what more can be done. Unfortunately, we don't have control over what nature decides to do but we can work on improving our emergency management services.

We've been hearing how "data is the new oil" for more than a decade now, and in certain sectors, it's a maxim that has more than panned out. From marketing and logistics to finance and product, decision-making is now dominated by data at all levels of most big private orgs (and if it isn't, I'd be getting a resume put together, stat). So it might be a something of a surprise to learn that data, which could transform how we respond to the increasingly deadly disasters that regularly plague us, has been all but absent from much of emergency response this past decade. Far from being a geyser of digital oil, disaster response agencies and private organizations alike have for years tried to swell the scope and scale of the data being inputted into disaster response, with relatively meager results. That's starting to change though, mostly thanks to the internet of things (IoT), and frontline crisis managers today increasingly have the data they need to make better decisions across the resilience, response and recovery cycle.

We've been hearing how "data is the new oil" for more than a decade now, and in certain sectors, it's a maxim that has more than panned out. From marketing and logistics to finance and product, decision-making is now dominated by data at all levels of most big private orgs (and if it isn't, I'd be getting a résumé put together, stat). So it might be a something of a surprise to learn that data, which could transform how we respond to the increasingly deadly disasters that regularly plague us, has been all but absent from much of emergency response this past decade. Far from being a geyser of digital oil, disaster response agencies and private organizations alike have for years tried to swell the scope and scale of the data being inputted into disaster response, with relatively meager results. That's starting to change though, mostly thanks to the internet of things (IoT), and frontline crisis managers today increasingly have the data they need to make better decisions across the resilience, response, and recovery cycle.

There is a rise in the number of natural disasters happening all over the world. According to the National Oceanic and Atmospheric Administration, there were 16 natural disasters in 2017. The cost of all the damages is in the billions. The amount of destruction they cause is devastating and it has left many of us wondering what more can be done. Unfortunately, we don't have control over what nature decides to do but we can work on improving our emergency management services.

The post-disaster environment poses immense challenges for crisis response teams tasked with assessing the extent of the damage as quickly as possible, often over thousands of square miles. These teams need a sound and reliable understanding of the situation on the ground, to quickly and safely provide the right help to the people affected. Citizen scientists from around the world can play a key role in delivering this information to emergency responders on the ground. In the wake of hurricanes Irma and Maria, which swept across the Caribbean during September 2017, an ongoing collaboration between the Zooniverse (an online citizen science platform), the University of Oxford, and NGO Rescue Global, has enlisted thousands of volunteers worldwide to analyse satellite-based information. The end result is a series of maps that highlight affected areas, providing a robust source of information which helps Rescue Global and the disaster relief community to generate more detailed mapping, and conduct needs assessments, aid deliveries and evacuations on the ground. When Rescue Global began their Hurricane Irma response operation in early September, the Planetary Response Network, a collaboration between the Zooniverse and Oxford University, was activated quickly and began sourcing satellite images of the disaster-affected areas from data providers Planet, Digital Globe, NASA and ESA.

Drones aren't just good for getting your shopping in an instant – by carrying defibrillators they could prove to be life-saving if your heart stops beating. Only around one in ten people survives a cardiac arrest outside hospital. Having a bystander perform chest compressions improves your chances, but a shock from a defibrillator must be applied quickly to restart the heart. Every minute without CPR and defibrillation reduces someone's chance of survival by 10 per cent. Defibrillators are designed to give spoken instructions so that anyone can use them, and many are available in public places.

Security remains one of the top unresolved challenges for businesses. Billions of dollars have been spent on security technology over the last 30 years, yet hackers seem to be more successful than ever. Every organization is now under extreme threat, all the time. Today, hacking is a much more complex art than it used to be: It no longer only involves just scanning and penetrating the network via a vulnerability. Yet the traditional security tools used by most companies are often inadequate because they still focus on this, ignoring what is now a very complex post-compromise chain of events.