Welcome to The TechCrunch Exchange, a weekly startups-and-markets newsletter. It's inspired by the daily TechCrunch column where it gets its name. If you aren't in the United States, it's a little hard to explain. In short, certain deficiencies in our policing and judicial systems flared brightly as the week came to a close. So, today's Exchange newsletter will be shorter than intended. Hug the people you love, and everyone else.

Public policies that supply public goods, especially those involve collaboration by limiting individual liberty, always give rise to controversies over governance legitimacy. Multi-Agent Reinforcement Learning (MARL) methods are appropriate for supporting the legitimacy of the public policies that supply public goods at the cost of individual interests. Among these policies, the inter-regional collaborative pandemic control is a prominent example, which has become much more important for an increasingly inter-connected world facing a global pandemic like COVID-19. Different patterns of collaborative strategies have been observed among different systems of regions, yet it lacks an analytical process to reason for the legitimacy of those strategies. In this paper, we use the inter-regional collaboration for pandemic control as an example to demonstrate the necessity of MARL in reasoning, and thereby legitimizing policies enforcing such inter-regional collaboration. Experimental results in an exemplary environment show that our MARL approach is able to demonstrate the effectiveness and necessity of restrictions on individual liberty for collaborative supply of public goods. Different optimal policies are learned by our MARL agents under different collaboration levels, which change in an interpretable pattern of collaboration that helps to balance the losses suffered by regions of different types, and consequently promotes the overall welfare. Meanwhile, policies learned with higher collaboration levels yield higher global rewards, which illustrates the benefit of, and thus provides a novel justification for the legitimacy of, promoting inter-regional collaboration. Therefore, our method shows the capability of MARL in computationally modeling and supporting the theory of calculus of consent, developed by Nobel Prize winner J. M. Buchanan.

AI leads to'great return on investment' in dealing with pandemic The UAE approached the COVID-19 pandemic "as a scientist," said Omar Al Olama, the UAE's Minister of Artificial Intelligence, Digital Economy and Remote Work Applications. Al Olama was appointed by the UAE as the first artificial intelligence (AI) minister in the world in 2017, when he was just 27 years old. That year, his ministry launched a strategy "to become one of the world leaders in AI by 2031." The COVID-19 pandemic, it turns out, may have accelerated the UAE's applications of AI to governance and public health, and to establishing the Emirates as a world leader in AI, as Al Olama, now 31, explained in an exclusive Zoom interview with Al-Monitor on Nov. 18. Al Olama describes a policy response to the pandemic by the UAE that has been data- and analytics-driven and characterized by openness to different ideas, nimbleness in response to changing events, and willingness to accept calculated risks. "We actually were very open to many different solutions, and many different theories out there," he said. "And we worked with everyone, from the East and the West, to try to find the right solutions that can be deployed in the UAE to make us go back to living a relatively normal life. Not the normal life that we're used to. People still need to wear masks. There's still a lot of focus on the general community's safety, but AI played a big role in getting us to this point."

Hit play on the player above to hear the podcast and follow along with the transcript below.This transcript was automatically generated, and then edited for clarity in its current form. There may be some differences between the audio and the text. Welcome back to Talking Tech. This month marks a huge milestone for Microsoft and its Xbox video game console. Twenty-years ago, this month, Microsoft launched the original Xbox.

The real estate industry has started leveraging the power of artificial intelligence and machine learning to provide efficient services to property managers, landlords, tenants, and others. AI has helped to build a dedicated platform for real estate like property management software and many more for automating a complicated processes. This cutting-edge technology helps to build a strong relationship between landlords and tenants. Here is an exclusive interview with Andrews Moses, Co-Founder and CEO, Tenantcube, where he elaborates how the company integrates AI/ML into real estate to offer a property management software for efficient service with a team of real estate expertise. Tenantcube offers next-generation property management software and is designed to be an end-to-end platform fulfilling the needs of landlords, property managers, and tenants. The software drastically improves the entire experience of renting and saves time and money spent on traditional methods of rental property management.

A few years ago, at the Princeton Club in Manhattan, I chanced on a memorable chat with the Harvard psychologist Steven Pinker. His spouse, the philosopher Rebecca Goldstein, with whom he was tagging along, had been invited onto a panel to discuss the conflict between religion and science and Einstein's so-called "God letter," which was being auctioned at Christie's. Pinker had recently published Enlightenment Now: The Case for Reason, Science, Humanism, and Progress. I was eager to pepper him with questions, mainly on religion, rationality, and evolutionary psychology. I remember I wanted Pinker's take on something Harvey Whitehouse, one of the founders of the cognitive science of religion, told me in an interview--that my own little enlightenment, of becoming an atheist in college, was probably mostly a product of merely changing my social milieu. I wasn't so much moved by rational arguments against the ethics and existence of God but by being distanced from my old life and meeting new, non-religious friends. I recall Pinker almost pouncing on that argument, defending reason's power to change our minds. He noted that people especially high in "intellectance," a personality trait now more commonly called "openness to experience," tend to be more curious, intelligent, and willing to entertain new ideas. I still think that Pinker's way of seeing things made more sense of my experience in those heady days. I really was, for the first time, trying my best to think things through, and it was exhilarating. We talked until the event staff shelved the wine, and parted ways at a chilly midtown intersection.

From cars to planes, the future of transportation is already here--and is changing rapidly. Software engineering is increasingly central to both the development and maintenance of all kinds of vehicles. That means more people need to start thinking like systems engineers. Dale Tutt, vice president of aerospace and defense industry for Siemens Software, says this means companies must offer more training and planning for those designing and developing vehicles of the future. "As you try to address the talent gap, there's a lot you can do to help make the tools easier to use. By better integrating the tools and by bringing in technologies like AI to help automate the generation of different design concepts and the analysis of those concepts using simulation tools, you can extend the capabilities of the system so that it helps empower your engineers," says Tutt. "Companies that are the most successful at adopting systems engineering are doing it because systems engineering, and the tools being used are becoming almost like the DNA of their engineering organization. Everyone is starting to think a bit like a systems engineer, even in their normal job. The tools and the ecosystem that you use to do systems engineering has a large role in facilitating adoption." Nand Kochhar, the vice president of automotive and transportation for Siemens Software, says a systems engineering approach can extend more broadly, as engineers think about how cars and vehicles connect to everything else in their environments. "In a smart city, the system has become the city itself. Take a vehicle in the city, for example. The definition of the system has moved from the single vehicle to include the flow of traffic in the city and to how the traffic lights operate. You can extend that expansive ecosystem to other aspects like building management, for example, into the smart city environment," he says.

Artificial Intelligence and machine learning have added a whole new scope for actuaries. But, it almost seems like there could be a bit of a conflict in terms of AI taking over some of what actuaries do. We caught up with Ronald Richman, chief actuary at Old Mutual Insure to get his opinion and insight into the relationship between AI and actuaries and the regulatory environment around the use of AI.

Craig Mermel is currently the Research Lead in Pathology at Google Health where he leads a team focused on accelerating the application of machine learning for improved diagnosis of important human diseases, especially cancer. Prior to joining Google, Craig worked at Apple on the Apple Watch and related health initiatives. Mermel completed a joint MD/PhD training at Harvard Medical School, where he developed novel statistical methods for mining the cancer genome for his PhD dissertation. He conducted residency training in Clinical Pathology at Massachusetts General Hospital and is board-certified in Clinical Pathology. What initially sparked your interest in medicine and subsequently, AI in medicine? As a child, I was always interested in mathematics. I thought it was a lot cooler than science, so I dreamt of becoming a mathematician or a code breaker. When I was a high school freshman, we had a chemistry teacher who was this amazing human being, a cancer survivor who taught me to appreciate science. He was the one who opened my door to this amazing yet mysterious subject.

The next wave of aerospace is just around the corner, and a lot of that innovation is happening thanks to new, faster methods of development. "What's happening now is that companies are trying to understand how they take the lessons from Agile software development and apply those to Agile product development," explains Dale Tutt, vice president of Aerospace and Defense Industry for Siemens. With Agile software development, you can build software and test it relatively quickly. "When you start talking about an airplane or an air taxi," Tutt says, "it's expensive to build a prototype and test them, so you have to think about it in a different way and take a different approach. It really takes good program planning." This new type of product development, where planes and other kinds of air transport are developed faster than ever, still needs to incorporate safety as a top priority, which creates new kinds of challenges. These kinds of products are different than smartphones or other consumer electronics, Tutt explains. "Part of it is driven by the safety and reliability you want to have--so that when you're flying around, you can safely operate the vehicle. There's a certain amount of durability and reliability that's built into the design of the product. The amount of investment that these companies or that an individual would make in buying one of these aircraft means there's an expectation that it's going to last a while, and that you're going to have value in that asset. It's a little bit different than some of the consumer goods that we buy, and it's more expensive to repair them than it is to replace them."