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To solve space traffic woes, look to the high seas

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To solve space traffic woes, look to the high seas


Can you start off by giving me the lay of the land of space traffic management and space situational awareness today? How would you evaluate how well the world currently does these things? 

Space traffic management is very much an emerging field. We’re in the early stages, where the discussions in the international community are in the development of norms and standards of behavior. The fundamental purpose of space traffic management is to prevent collisions in space. Collisions, by their nature, are debris-generating events, which cause the domain itself to become polluted and less safe for future actors. So it’s twofold—it’s not just that a collision damages satellites; a collision also causes long-term damage to the environment itself. And we see that very clearly in all of the evaluations of the [2009] Iridium-Cosmos collision.

Space situational awareness is a different thing—it’s about providing data. Different countries and companies around the world detect where these objects are in orbit and share what’s out there. For 50 years, you didn’t really need much information other than [the location of debris so it can be avoided]. But as the orbital domain becomes more congested with junk, it’s not just a question of “How do you avoid debris?” It’s now “How do you interact with other [satellite] operators up there?” When there’s two maneuverable satellites that want to be in the same place at the same time, that’s when you get to that question of management rather than space situational awareness. 

Along those lines, when there is a possible collision between two objects, what’s the general process in place to prevent a disaster from ensuing? Is there a quick outline you can provide?

I’ve been on a quest to find an authoritative reference that talks about the process from end to end. I wish I could say, “Go to this resource, and it’ll show you what happens from the time they look for a close approach to the time that the decision is made for whether or not to maneuver a satellite.” But it’s a bit opaque. Different operators have different internal processes that they don’t necessarily want to share. 

The US Space Force’s 18th Space Control Command Squadron is constantly watching the skies and reevaluating the situation every eight hours. If they detect that a close approach is possible, they’ll issue a conjunction alert to the owner-operator of the satellite. Then it goes into the hands of the owner-operator to decide what to do with that information. And then the 18th will continue to monitor things. The projection of where something might be in space varies wildly based on the object, how it’s shaped, how it reacts to the atmosphere around it … If there’s any intention by the operator to move it on purpose, that changes the observations as well.

You’ve argued that while air traffic control might seem like a sensible analogue to space traffic control for obvious reasons—namely, that it’s about the prevention of collisions—it is actually an inappropriate model, and that maritime law actually provides a better one. 

All of the world’s international airspace is designated to a single entity state for the purposes of providing air traffic control services. So, for example, the US controls 5 million square miles of domestic airspace but 24 million square miles of international airspace. They are the sole authority to provide those air traffic control services in that airspace by virtue of the ICAO [International Civil Aviation Organization]. 

Space doesn’t have anything like that. But the high seas don’t have that either. What the high seas have is a collection of agreed-upon rules of behavior and the authority over each vessel: the state under which the vessel flag is flown. There’s not a high-seas authority that says yes or no, you can operate here and you can’t operate here. Everyone has access to this shared resource, and the principles of freedom of the sea include the freedom of navigation, freedom of overflight, freedom to lay cables underneath, freedom of fishing. Within the maritime agreements, there is freedom to conduct commercial activities. This is different from airspace, which historically has been an area purely for transportation. 

The orbital domain is not solely for transportation [either]. It’s the domain in which the commercial activity occurs: telecommunications, remote sensing, etc.

Of course, maritime law is also meant to prevent collisions on the high seas. Collision regulations, or colregs, dictate what’s supposed to happen if two vessels are [on course for] a head-on collision: who has priority to maneuver, what to do if something happens in a narrow channel … These sort of principles are laid out very clearly. They have very clear applicability to the challenges we’re facing in the space domain. There are very clear parallels. Whereas if we take the aviation model, we’re really trying to force a square peg into a round hole.

Is there pushback or disagreement on the idea of using maritime law as the inspiration for space law? Is the general consensus moving toward this idea?

I think it’s trending that way, by virtue [of the fact] that it’s really the only viable path forward, but there is always discussion. Having someone or some singular body decide what we can do is not a realistic outcome, given the nature of the space domain. We don’t do space traffic like air traffic because it’s not simply a safety question. It is a diplomatic question and an economic question as well. 

Giving control of space traffic to one regulatory body would be easy, like the 18th Space Control Squadron, which provides these services free of charge. But there are countries that are suspicious of that [idea]. And then, of course, there is the issue of classified data. So you get into these complexities of trust—you know, if there was one trusted global entity, then sure, we could do that. [But] there aren’t any that are trusted by all, and trust is something that changes over time. 

So the path forward is to create a way for that information to be shared and trusted. For example, I’m working on a project where we’re talking about blockchain as an enabler for trusted information sharing. By nature of the blockchain, you can determine who inputted the information and validate them as a legitimate participant, and that information can’t be altered by a third party. 

Space is often described as a new kind of Wild West—lawless and unregulated, and anything goes. How can a framework for something like space traffic management even get established if there’s also just no set pathway for establishing rules to begin with? 

I would argue that space isn’t actually the Wild West. There is an obligation in the 1967 Outer Space Treaty for states to supervise objects that they permit to launch from their countries. So it’s not unregulated; it’s not completely free. It’s just we haven’t agreed on what that actually means for continuing supervision. 

The Iridium-Cosmos accident was a wake-up call. It sparked a lot of activity, like the development of on-orbit servicing technology to dispose of big objects that remain in space, and also the development of commercial sensor networks so that we can have better and better space situational awareness information. 

The next big catalyst, I believe, is megaconstellations. We’re seeing more [potential collision] alerts between two maneuverable satellites, which is a solvable problem if we have a set of rules. This creates a lot of pressure on the system to start reaching these agreements. Capitalism is a pretty effective motivator. When people see more and more economic opportunities in popular orbits, then balancing access to those orbits becomes a motivator as well.

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The way forward: Merging IT and operations

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The way forward: Merging IT and operations


“People in operations see a ton of opportunity,” says Irani-Famili, who has worked in the energy sector for the better part of a decade. For problems they encounter every day, OT dreams up potential fixes. For example, if there’s a power outage, relevant supervisors could automatically get notifications wherever they are. Or staff availability data could flow through company systems so supervisors and managers can more easily assign projects or shifts. 

“And then they go and talk to IT, and IT’s response might be ‘Not possible. This could be breaking every security protocol,’” Irani-Famili says. Operations sees solutions to problems. IT sees cybersecurity, integration, and support risk. “But from the operations perspective, what they see is IT red tape, IT is not collaborating, or IT is not playing the game.” 

It’s easy to describe IT and OT as different departments with different objectives and starkly different cultures. They are often managed independently in organizations and treated as isolated groups that cater to specific problems and employ their own protocols. But that results in inefficient, costly setups that fail to foster innovation and standardization. 

As global economies gain steam after near collapse amid the 2020 coronavirus pandemic, the pressure is on to boost productivity, innovation, and agility. Companies need to increase the speed of business by digitizing processes and using the internet of things and artificial intelligence (AI) to extract actionable insight from large data sets. 

To undergo such digital transformation in industries that rely heavily on physical assets—manufacturing, oil and gas, transportation, energy, and utilities—organizations must integrate IT and OT into one seamless organization that connects systems on both sides. 

“IT/OT convergence is an inevitability,” says Fay Cranmer, senior managing director in Accenture’s natural resources practice and former chief information officer at mining company Rio Tinto. “It’s the only way to have a full digital transformation, especially in the heavy industry space.” 

But there are significant challenges to overcome. Many industrial environments are characterized by legacy equipment, time-honored, manual processes, and resistance to change—from both sections of the business, OT and IT. Often the attitude is, OT alone knows how to generate the products and services that produce revenue for the company. 

Conversely, IT folks often think only they know how to help modernize OT departments, by enabling the systems that allow the benefits of AI, the internet of things, and other digital technologies. True collaboration is a must, but the complexity of new technology and infrastructure merging with legacy machines prompts questions concerning investment, leadership, and governance. 

Bala Arunachalam, an executive in oil and gas for more than 30 years, says specific industry characteristics are a big factor. “This industry is a legacy industry. For them to move onto the technology space, to capitalize on the opportunity that is in front of them, is a struggle.” 

As physical assets, whether in the factory or out in the field, become digitized through internet-of-things technology; as applications, data storage, and data processing move to the cloud; and as employees stick to their home offices more than a year into the pandemic, any perceived boundaries between OT and rest of the business are crumbling. “The challenge is that we need to bring data together across all those boundaries,” says Cranmer. The biggest hurdles, she says, are organizational and cultural. “The technological side is much more easily overcome than the human side.” 

The good news is there are guidelines that organizations can follow to achieve the IT/OT integration that’s so critical for successful digital transformation initiatives. 

Download the full report.

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Forget dating apps: Here’s how the net’s newest matchmakers help you find love

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Forget dating apps: Here’s how the net’s newest matchmakers help you find love


The thread took off. Morgan basked in the feel-good vibes of seeing people find each other—“I love love!”—and reveled in the real-life connections she was able to mastermind: multiple dates in her hometown of Portland, Oregon; someone who was thinking of flying to meet somebody in New York because of the thread; even a short relationship. Even today, people continue to add their pictures to the thread, seeking love all across the United States.

If this feels a bit like old-fashioned matchmaking, it is. But it’s a long way from gossipy neighborhood grandmas setting up dates. These operations are often ad hoc, based on platforms like Twitter and TikTok, and—unlike the dating apps, with their endless menu of eligible suitors—hyperfocused on one person at a time.

Play by mail

Randa Sakallah launched Hot Singles in December 2020 to solve her own dating blues. She’d just moved to New York to work in tech and was “sick of swiping.” So she created an email newsletter using the platform Substack that had a seemingly simple premise: apply via Google Form to be featured, and if you are, your profile—and yours only—is sent to an audience of thousands.

Yes, each profile features the requisite information: name, sexual orientation, interests, and some photos. But crucially, it has a wry editorial slant that comes from Sakallah’s questions and the email presentation. This week’s single, for example, is asked what animal she would be; the answer is somewhere between a peacock and a sea otter. (“My main goals in life are to snack, hold hands, and maybe splash around a bit,” she writes.)

Sakallah says part of the appeal of Hot Singles is that only one person’s profile is delivered via email on Friday. It’s not a stream of potential faces available on demand, she says, which makes it possible to really savor getting to know a single person as a human being and not an algorithmically offered statistic. 

“I try to tell a story and give them a voice,” says Sakallah. “You really want to think about the whole person.”

Dating apps may be quick and easy to use, but critics say their design and their focus on images reduces people to caricatures. Morgan, who started the long-running Twitter thread, is a black woman who says that the dating-app experience can be exhausting because of her race. 

“I’ve had friends just put their photo and an emoji up, and they would get someone asking them to coffee so fast,” she said. Meanwhile, “I’d have to put more work into my profile and write paragraphs.” The results of her effort either didn’t get read or attracted a slew of uncomfortable, racist comments. “It was frustrating,” she says.

Scratching a different itch

Dating-app fatigue has a number of sources. There’s the paradox of choice: you want to be able to select from a wide variety of people, but that variety can be debilitatingly overwhelming. Plus, the  geographic parameters typically set on such apps often actually make the dating pool worse. 

Alexis Germany, a professional matchmaker, decided to try TikTok videos during the pandemic to showcase people and has found them immensely popular—particularly among people who don’t live in the same place. 

“What makes you think your person is in your city?” Germany says. “If they’re a car ride away or a short plane ride away, it could work.”

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These weird virtual creatures evolve their bodies to solve problems

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These weird virtual creatures evolve their bodies to solve problems


“It’s already known that certain bodies accelerate learning,” says Bongard. “This work shows that AI that can search for such bodies.” Bongard’s lab has developed robot bodies that are adapted to particular tasks, such as giving callus-like coatings to feet to reduce wear and tear. Gupta and his colleagues extend this idea, says Bongard. “They show that the right body can also speed up changes in the robot’s brain.”

Ultimately, this technique could reverse the way we think of building physical robots, says Gupta. Instead of starting with a fixed body configuration and then training the robot to do a particular task, you could use DERL to let the optimal body plan for that task evolve and then build that.

Gupta’s unimals are part of a broad shift in how researchers are thinking about AI. Instead of training AIs on specific tasks, such as playing Go or analyzing a medical scan, researchers are starting to drop bots into virtual sandboxes—such as POET, OpenAI’s virtual hide-and-seek arena, and DeepMind’s virtual playground XLand—and getting them to learn how to solve multiple tasks in ever-changing, open-ended training dojos. Instead of mastering a single challenge, AIs trained in this way learn general skills.

For Gupta, free-form exploration will be key for the next generation of AIs. “We need truly open-ended environments to create intelligent agents,” he says.

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