In this episode of the McKinsey on Insurance podcast series, we discuss how insurtechs are driving innovation and disruption in the insurance industry. Experts from four different regions weigh in on rising valuations, threats and opportunities for incumbents, and the long-term outlook of insurtech. An edited transcript of the conversation follows. For more conversations from McKinsey on Insurance, our podcast series about the trends, disruptions, and strategies that are reshaping the insurance industry today, subscribe to the series on Apple Podcasts, Google Podcasts, Spotify, or Stitcher. Pradip Patiath: Welcome, everybody, to McKinsey on Insurance. I'm a senior partner in Chicago, and I'll be hosting today's conversation on the state of insurtech and what it means for the future. I'm joined by Tanguy Catlin, a senior partner in our Boston office; Alex Kimura, a partner based in Singapore; and Simon Kaesler, a partner in our Frankfurt office. So we have global perspectives on the important topic of insurtechs, which are tech-driven insurance companies that take advantage of new technologies to provide coverage or to reinvent business systems in this digital era. Insurtechs are certainly extending innovation throughout the sector. We've seen something similar in other sectors as well--such as healthcare, retail, and banking.

To develop and evaluate an automated segmentation method for accurate quantification of abdominal adipose tissue (AAT) depots (superficial subcutaneous adipose tissue [SSAT], deep subcutaneous adipose tissue [DSAT], and visceral adipose tissue [VAT]) in neonates and young children. This was a secondary analysis of prospectively collected data, which used abdominal MRI data from Growing Up in Singapore Towards healthy Outcomes, or GUSTO, a longitudinal mother–offspring cohort, to train and evaluate a convolutional neural network for volumetric AAT segmentation. The data comprised imaging volumes of 333 neonates obtained at early infancy (age 2 weeks, 180 male neonates) and 755 children aged either 4.5 years (n 316, 150 male children) or 6 years (n 439, 219 male children). The network was trained on images of 761 randomly selected volumes (neonates and children combined) and evaluated on 100 neonatal volumes and 227 child volumes by using 10-fold validation. Automated segmentations were compared with expert-generated manual segmentation.

What is the impact of artificial intelligence (AI) and big data on societies in the Indo-Pacific? How are countries using AI and big data to enhance their national security and advance their national interests? And what are the major regulatory issues? For a perspective on these and other matters, Jongsoo Lee interviewed Simon Chesterman, dean and provost's chair professor of the National University of Singapore Faculty of Law and senior director of AI Governance at AI Singapore. What are nations in the Indo-Pacific doing to develop their artificial intelligence (AI) and big data capabilities?

Singapore's public sector has kicked off 5G pilots involving uses cases for various industries, including healthcare, manufacturing, and construction. The government is targeting to run 15 live trials on the southern island of Sentosa by yer-end, before ramping this figure up to at least 30 by the first half of 2023. The first set of 10 already had started at Sentosa, with multiple agencies including the Building and Construction Authority (BCA), National Environment Agency (NEA) and Centre for Healthcare Assistive and Robotics Technologies (Chart) under Changi General Hospital. These trials would see the use of 5G for autonomous robots, tele-operated vehicles, and augment reality applications, according to Government Technology Agency (GovTech), which is the public sector's CIO. Industry regulator Infocomm Media Development Authority has set aside S$40 million (US$29.53 million) to support research and development efforts and drive adoption of 5G, which include initiatives focused on key verticals such as urban mobility and maritime.

Multi-ethnic Asian country needs to take special care navigating its use of artificial intelligence in some areas, specifically, law enforcement, as well as recognise that fostering confidence in AI requires establishing public trust in different aspects of its society. In its quest to drive the adoption of artificial intelligence (AI) across the country, multi-ethnic Singapore needs to take special care navigating its use in some areas, specifically, law enforcement and crime prevention. It should further foster its belief that trust is crucial for citizens to be comfortable with AI, along with the recognition that doing so will require nurturing public trust across different aspects within its society. It must have been at least two decades ago now when I attended a media briefing, during which an executive was demonstrating the company's latest speech recognition software. As most demos went, no matter how much you prepared for it, things would go desperately wrong.

Singapore's Defence Science and Technology Agency (DSTA) has inked a partnership with Philadelphia-based Ghost Robotics to identify uses cases involving legged robots for security, defence, and humanitarian applications. They will look to test and develop mobile robotic systems, as well as the associated technology enablers, that can be deployed in challenging urban terrain and harsh environments. The collaboration also would see robots from Ghost Robotics paired with DSTA's robotics command, control, and communications (C3) system, the two partners said in a joint statement released Thursday. The Singapore government agency said its C3 capabilities were the "nerve centre" of military platforms and command centres, tapping data analytics, artificial intelligence, and computer vision technologies to facilitate "tighter coordination" and effectiveness during military and other contingency operations. Its robotics C3 system enabled simultaneous control and monitoring of multiple unmanned ground and air systems to deliver a holistic situation outline for coordinated missions, including surveillance in dense urban environments.

In its quest to drive the adoption of artificial intelligence (AI) across the country, multi-ethnic Singapore needs to take special care navigating its use in some areas, specifically, law enforcement and crime prevention. It should further foster its belief that trust is crucial for citizens to be comfortable with AI, along with the recognition that doing so will require nurturing public trust across different aspects within its society. It must have been at least two decades ago now when I attended a media briefing, during which an executive was demonstrating the company's latest speech recognition software. As most demos went, no matter how much you prepared for it, things would go desperately wrong. Her voice-directed commands often were wrongly executed and several spoken words in every sentence were inaccurately translated into text.

In its quest to drive the adoption of artificial intelligence (AI) across the country, multi-ethnic Singapore needs to take special care navigating its use in some areas, specifically, law enforcement and crime prevention. It should further foster its belief that trust is crucial for citizens to be comfortable with AI, along with the recognition that doing so will require nurturing public trust across different aspects within its society. It must have been at least two decades ago now when I attended a media briefing, during which an executive was demonstrating the company's latest speech recognition software. As most demos went, no matter how much you prepared for it, things would go desperately wrong. Her voice-directed commands often were wrongly executed and several spoken words in every sentence were inaccurately translated into text.

In the future, if armies deploy autonomous robot soldiers and they fire on the wrong targets, who will we hold responsible - the general who deployed them or their designer, Singapore law professor Simon Chesterman asks in We, the Robots.

Singapore, Singapore--(Newsfile Corp. - October 8, 2021) - PlatON, a next-generation Internet infrastructure protocol based on the fundamental properties of blockchain, recently combined blockchain, artificial intelligence and privacy computing technology to establish a decentralized collaborative privacy artificial intelligence network, which would take utilization of data to a new level. This network will serve as the infrastructure of autonomous artificial intelligence (AI) agents, who can facilitate advanced artificial intelligence and explore the road to Artificial General Intelligence. Based on blockchain network, PlatON developers designed a decentralized privacy computing network to connect data, algorithms and hashrate through privacy computing protocols. Autonomous AI agents can obtain the required resources at low cost, train artificial intelligence models and publish them on the network, and interact with other artificial intelligence services or agents to form a self-organizing and cooperative artificial intelligence network. On this network, anyone can obtain artificial intelligence technology or become a stakeholder in its development, and realize the autonomy of artificial intelligence.