Planetary Radio: Space Exploration, Astronomy and Science - Space Policy Edition: What does “science as a service” really mean?

Episode Date: October 9, 2026

Can you buy science the way you buy a rocket launch? NASA is exploring the idea of “science as a service,” asking industry how commercial companies could provide scientific data and capabilities for Earth science, space weather, and astrophysics. But the concept isn’t new. It’s the latest chapter in a four-decade effort to commercialize space science that stretches back to the brief, troubled privatization of Landsat in the 1980s. Casey Dreier is joined by Jack Kiraly, chief of advocacy for The Planetary Society, and Britney Schmidt, planetary scientist, astrobiologist, and Planetary Society board member, to unpack what commercial science services can and can’t deliver.  Discover more at: https://www.planetary.org/planetary-radio/science-as-a-serviceSee omnystudio.com/listener for privacy information.

Hello and welcome to the Space Policy edition of Planetary Radio. I'm Casey Dreyer, the chief of space policy here at the Planetary Society, and this is the show that goes into the processes and policies behind space exploration. This month, joining me is my colleague, the Chief of Advocacy at the Planetary Society, Jack Karali, and a planetary scientist, astrobiologist and board member of the Planetary. Society, working scientist, Dr. Britt New Schmidt. Both of them are here to talk about the idea of SAS, science as a service. This concept was formalized in the recent years by Jared Isaacman's leaked Athena document for NASA,

promoting the idea of using science as a service, purchasing scientific data products, perhaps, activities primarily for Earth Science data. NASA has since followed up with an RFI, what's called a request for information from industry about ways that commercial industry could provide scientific capabilities for Earth science, heliophysics, astronomy. It's an open discussion and it's actually the continuation of a nearly four-decade-long effort to find ways for commercial entities to offset the costs of scientific data in space. Going all the way back to the 1980s with the Lansat debacle, briefly privatizing and then un-privatizing Earth observation data from the Lansat satellites, ongoing efforts to purchase block amounts of data from Earth-observing companies to varying degrees of success, and then seeing where else that could apply.

Obviously, NASA is in the midst of a variety of commercial experiments, launch paying off particularly handsomely, at least at the moment, Clips the Commercial Lunar Payload Services CLPS program. Open question, but getting a significant increase in investment, as NASA now is intending to build out a moon base. And as we'll find, commercial means a variety of different things to different people. So we will explain and explore this idea of science as a service, both from the perspective of policy and from a working scientist,

a working planetary scientist and Dr. Brittany Schmidt. Really interesting conversation. I recommend you stick around for that one. But before we get to that, I'd be remiss if I did not mention that this show, the Space Policy Edition, is a product of the Planetary Society, which is a non-profit organization,

member-supported organization. We do not have government money. Thankfully, right now, makes things a lot easier for us to say what we believe. We do not have significant corporate money. We are funded by individuals. Anyone can be a member around the world, And if you're not, please consider joining us.

It's only four bucks a month. We haven't raised our prices in, I think, over a decade. That's a pretty good deal these days. Can you even get a cup of coffee, maybe in a few places for $4 a month? Four bucks a month starting. If you're already a member, first, thank you. Honestly, your membership enables us to do this work, this show, and all the other great work that we do in our policy and advocacy program at the Planetary Society.

So consider upgrading your membership. There are higher levels to support us more, or you can just give us a donation at planetary.org slash join or planetary.org slash donate. Please consider it. This is an effort we do because of you, literally. So thank you. And now my conversation with Dr. Brittany Schmidt and Jack Carolley. Brittany and Jack, welcome to the space policy edition of Planetary Radio.

Thanks for having us, Casey. Yes, indeed. a rare two-guest episode, but we have something often admit that we are actually working through together, which makes it a perfect podcast episode, which is the idea of science as a service and a topic that is quite relevant these days. Jack, do you want to just give us a heads-up of why this phrase has entered our vernacular and what's kind of been going on with this idea? Yeah, so science as a service means a million things to a million different people. NASA itself, it seems is working through what exactly this program could mean going forward.

Now, there's been a number of different experiments in this science as a service, or really space access and space exploration as a service over the years. I think most recently we have the Clips program, commercial lunar payload services program, which these are your, you know, the Astrobotics Paragrinlander, fireflies, blue ghost. This program is going through a transformation from Clips 1.0, which is these smaller lander systems that NASA has built out a number of missions planned for the next few years. And moving into Clips 2.0, which is going to be described as larger missions, more payloads, more payloads space, more power capacity, all building up towards supporting future Artemis missions, connecting in with the Moon Base program.

And this is built off of a long legacy of a trend towards commercialization for a number of different activities that the agency goes through. And in the hopes of creating marketplaces for companies to develop technologies and provide these services to the government with the idea that the more companies you have doing this, the more technology development that happens, the lower the cost to the government. And this really dates back to the 1984 Commercial Space Launch Act that kind of set in motion the somewhat robust commercial launch sector that we have today with a number of different players, Rocket Lab, SpaceX, Boeing, United Launch Alliance, all vying for government and commercial and international contracts to get payloads into space. But we see other programs, the commercial satellite data acquisition program within Earth science, buying data from companies like Black Sky, Macs,

XR and using that data for Earth science applications. So there's a number of different experiments that NASA and the U.S. government as a whole have initiated all built on this kind of central idea that if you can develop the commercial capabilities, the commercial marketplace, it will allow you to access areas of space, collect data, and do activities in space for a cheaper, overall cheaper cost because it's commercially available. Yeah, I mean, I think that's the, they're trying to say, Can we spend less on some aspect of space science by having the private sector pay for some share of it?

And then we can just buy what we need is that, and I would say the fantasy, maybe that's too strong a way, but the hope, the intent. Hypothesis. Hypothesis. There you go. That's a much more neutral. Maybe I'm betraying some of my opinions on this. You mentioned the 1984 Commercial Space Launch Act. There is also in 1984, very pertinent to this, the Land Remote Sensing Commercialization Act, which,

actually created a, you know, basically put the government out of the earth observing Lansat business for a time by creating a commercial company to sell this data that the government would purchase as any customer but with no special relationship. We'll talk about that. So this has been really like an experiment for over 40 years now going back to the mid 80s. We'll touch on how that story went. But before we do, Brittany, you're a working scientist. I'd say a relatively successful one, not just because you're a board member of the Planetary Society. But I've always found this idea, science as a service, kind of a strange, it alliterates, right?

It's SaaS, which is also, I think, software as a service, which is where everyone's made their money in the last 20 years. But you're a scientist. What's a unit of science that you deliver that you charge for? Like, what would that even be in terms of your experience as a science, particularly a planetary scientist? Yeah, I think this is the fundamental misunderstanding of what science is. Science is not a parcel of data, right?

Science is the conclusion that comes from that. And there are people involved in creating that conclusion, right? We talked about this hypothesis that this would work. That's a question posed by people. You get the information to then try to answer this or to validate your hypothesis or invalidated or to answer a question that you find compelling or that the government finds compelling. and then take the data and turn it into something. So this idea of science as a service coming from corporations who don't employ scientists who aren't going to do anything with the data that they are not actually even producing themselves, right?

We're talking about missions that are going to launch instruments. Well, the hypothesis is that these instruments for free will exist that scientists, somehow will give them instruments to quote unquote launch for free. And then they're going to sell the data back to the people that built the instrument, the government that furnished the entire industry with opportunities to launch missions. And it just doesn't really make any kind of sense. You know, it's kind of like space corporate welfare is what I am concerned about because it's not recognizing that science isn't a unit of data.

There's still a lot that has to be done from any instrument to calibrate it, to handle it correctly. There have to be people in the loop to do those things, and then to take that data and work through it. And in fact, right now, a lot of that data analysis gets done by some pipelines, but the conclusions that are drawn by it are drawn by people. and oftentimes at an incredibly reduced cost because it's done at universities

or it's done at research institutions with low overhead and low cost structures. People who are invested in the system because it's valuable. And so I think it's really important to kind of remap our understanding that science isn't a unit of information. It is a process that involves people.

And we're not talking about the funding that would be needed to, to keep that going and to provide the services that science really represents, right? Science really serves people. We learn things about ourselves. We learn things about our planet. We make better things to make life on our planet easier and better, right? To predict the weather, to understand our changing environment,

to maybe one day move to another planet. But all of that comes from the people that ask and then answer the question. launching something into space and sending down a piece of data is not a science. You in particular work a lot with hardware. And this is, I'm very interested to hear about that process because, you know, when you build something,

and I think maybe this is maybe one of the detriments of what sci-fi has done. I always think about this, the idea that on Star Trek, you just like push a button as like, oh, here, we know everything about this planet now. Or they send a probe and it just like does magically and it understands everything about what it's doing.

but building something to go into a hostile environment like space and then understanding the data that comes back, that's actually an incredibly difficult process, right? And you mentioned things like calibration, just very briefly for people to never thought about this. Why is that hard? Why are things like calibration really important between understanding and not understanding what your data says?

You mentioned the environment. That's one of the key things that we have to think about when we're calibrating. If you just take out a camera and point it through the atmosphere of the earth, the actual number of photons you get is changing. Even if you're looking at the same background, it's going to change constantly. Clouds, a little bit of dust in the air, a little bit more scattering, a little bit less scattering. And so any kind of change.

So we've got the environment and its impact. So are we looking through our atmosphere that's changing and then open space to another atmosphere that's changing to a surface? or are we looking from space through that atmosphere to the surface? Okay, we can answer those questions. How is that environment changing? How is the sensor itself changing? So we have to have a whole set of things that we do. So for an astronomy set of measurements, we do things called dark currents,

which is where we take a measurement of the signal when the camera isn't basically even open. So we just know what the electronic noise is. Then we open it up, but we have a clear, a clear picture, right? And we take an image of just a flat background. It's literally called a flat to then see how the sensor varies over space. And then we correct for that. And then we take a look at something that we think we know, and then we build back from there.

So these are all steps in order to make sure that instrument's working well in order to interpret that data. And most importantly, we're making comparisons. If you use one instrument in one set of circumstances and you don't understand that environment, the comparison between two datasets isn't valid, right? You can trick yourself into believing something if you didn't do good enough calibration. And every once in a while we figure that out. There's a great example. And it works for every kind of sensor.

Right there, I gave you the camera one because we're humans. We use our eyes. It's something we understand. Everyone's looked through clouds or gotten a different sunburn depending on different things out in the environment on a particular day. But with radars, for example, there's all kinds of signal. One of the things that happened early in the radar exploration of Mars was that the ionosphere of Mars was interacting or was causing phantom signals in the radar data. And so people were interpreting data in the planetary data that actually wasn't there at all. It was an internal reflection,

and basically caused by charged particles in the upper atmosphere of Mars. So these kinds of signals and these kinds of thought processes really have to be thought all the way through and tested over and over and over again. You don't just send down the data. Right. And I remember this a lot from your colleague,

our board member Jim Bell, who works on the cameras for Mars surface landers and right now Mass Cam Z. you know, they had a whole calibration. They, man, that's planetary society submitted these things, but you took like pantone color chips that you know precisely, here's the wavelength this thing is emitting. And then you looked at it through the actual camera that was going to fly to Mars and say, given all the random errors and imperfections of just the physical world, here's what that

signal looks like and you're just calibrating it to that. Or like in your iPhone, when you take a picture and then you hit the color gradients or the tint, what is the actual color, right? Isn't there like a famous thing where the, when Viking landed, the sky looked blue because that was just the default color calibration that people on Earth applied to it. And they, oh, but now like the U.S. flag looked green or something like that. They actually had to use U.S. flag as a calibrator. So you don't, there's so much you don't know. It's kind of a humbling.

One of my memorable classes in college was physical chemistry, which basically said, you basically don't know anything. Every instrument. Here's all the ways that instruments are imperfect. and you have to understand, and I think that's the key, you have to deeply understand at a basic level, the engineering and performance of hardware that is collecting your data in order to understand anything about it. Absolutely.

And that's where, with the way we do space expiration right now, a scientist poses a question, the government has said that this is an important area to investigate. scientists pose questions. They propose instruments that can get information that can help with answering that question. Then they build the instrument to spec for that spacecraft, for that environment. They test it and test it and test it. It flies.

And then they get the information down. They look first for what's going on with the instrument itself. We have commissioning phases on everything. You test the whole spacecraft first. and then you start pulling down information and getting to higher and higher fidelity data. All of that involves incredible amounts of involvement from the people who built it

and who asked the question in the first place. You don't just stick an iPhone on a satellite and pointed in a direction you hope is interesting. Yeah. I mean, you can get a picture. The thing is, all you could say is, here's what it looks like. Couldn't really see anything else about it. You're not at this pixel level calibration.

Jack, do you see this? this complexity being reflected in this discussion so far from what you've seen in terms of buying science as a service? Because I've seen bits and pieces of this, but I guess where is this even kind of being decided beyond this? Well, it's not. Right. I think the simple answer is that the science that could be done, the scientific questions that should be driving, that could be driving decisions on where to land on the moon, taking just the click. example, right, as kind of the planetary science element of science as a service, because you could also define things like the spacecraft that they launched and unfortunately failed to dock

with the Swift Observatory as science as a service and has been described as such, even though the spacecraft itself is not even collecting any data that could be used for a scientific purposes, engineering data, anything, or telemetry that it did collect. That could be viewed as enabling science through a service provided by a commercial contractor. But looking at something like clips, science is not driving necessarily the decisions on where to land, what power requirements are there. It's really focusing more on the technology development and part of the economic incentives, creating the economic incentives for there to be companies competing for these contracts to land things on the moon. It's the missing link, right, is, well, what are the instruments?

even though we are increasing the number of selections of clips landers through that program, we are not increasing the number of instruments being selected through a competitive process, which, as Brittany described, is a very iterative process, right? It is scientists, the smartest people among us asking the most profound questions about, you know, in the case of the moon, the history and geology and the core questions as to why the moon is such a compelling thing to study, they're not being given the funding to develop the instruments that could fly on these landers. And so even if you go to a compelling place with one of these clips landers, you just kind of have to hope that the right instrument is being provided for that.

And there is a level of coordination that NASA itself is doing through its clips program office, through the exploration science ESSIO, is the acronym within the planetary science division within the science mission directorate, that there is a collaboration that should be happening, but it is also being balanced against, you know, technology development and workforce considerations and just which companies are bidding for what capability. And so not every lander is fit for every job on the lunar service. So science is one of many things being considered. I think, yeah, the idea of the commercialization is that as one customer, you no longer to define the requirements for the rest of the mission, right?

You're getting what you can out of it. And that's a pretty dramatic change in terms of what's actually worked really well in the paradigm that Brittany has grown up in all we all have grown up in in terms of how we've made these discoveries. I want to go back bringing to something you said about this idea of the service aspect of science and what that even means is kind of a misnomer. And I've thought about this quite a bit that they're really talking about data. And let's put aside the calibration issues, is that there's been experiments over the last 40 years.

Lansat's been one of them. There's been, as Jack, you were saying, these commercial data buys of other primarily Earth-observing satellite constellations. You're buying data. You're not buying science. Science is what happens after you get the data. And I don't know who among our listeners has read Bruno Latour's laboratory life, but he's a very kind of sociologist of observing the process of science. He was embedded in a biology lab in California in like the late 1970s and just watched the process of how science develops with a large

group of people. And science, again, it's this process social function of where you have all these data, you argue about it, you try to convince others. You don't know, there's directionality only appears in retrospect, right? You don't know which direction is going to be. pay off. And so you're kind of grappling with what seems promising and maybe it leads to a dead end or maybe it leads to something else. And we don't remember all that uncertainty after the fact. We look back and see this kind of linear line of discovery. But it was this, it's the one path that happened to work. And when you get a bunch of data and you're saying that science is the service, not data is the service, you're trying to package and quantify something that is this ongoing process.

it just seems to be a mismatch at a fundamental level from what science actually is. Brittany, does that resonate with you? Is that basically what science is to you is just ongoing arguments with other people until the arguments were readily accepted or not? Well, I mean, that is the scientific method, right? And that's how we know we're getting it right. And we know, you know, part of the process of science is asking a question and then proposing a possible answer.

It doesn't mean that it is answered completely, sometimes you get lucky and you answer it right off. That's very uncommon. Usually what you find is by asking the question, getting some information, you're missing some level of depth, something that was in there because the natural world, while we've gotten very used to it, is incredibly complex and is not visible to us in the ways that we wish it was. And so that process is careful and it's thoughtful and it is important that the process is respected. And I think that is really what's missing. It doesn't mean that there aren't opportunities to get some extra return.

You mentioned data buys from commercial providers. That is a different model than what's happening right now with the clips program, right? With a commercial satellite that's taking pictures for a particular company, for, I don't know, pointing out agricultural use of fields or how urban development is going. And then we just figure out that it flew over a glacier and we can use that chunk of data to do science that wasn't planned. That's fantastic. That's optimizing, right? That's bring this data at very low cost because the satellite's been funded through completely other means and then we use the data. What's happening here is that we're taking dollars that, you're,

used to be directed to get results and information that science community and the government agreed was important. We're taking that money. We're just saying go to a place that may or may not have information we want. You can go anywhere you want, build whatever you want to. We hope we'll have a camera or a thing that'll go with you. And then what's being proposed is effectively like when you buy a, you know, you buy a car and then they want to sell you back the ability to use its GPS on a monthly service. Or you're like, I own the hardware, right? This is why farming in the U.S. has been a real challenge lately is because farmers bought tractors with capacity that they then had to pay for on a monthly subscription. Like, it's just destroyed

what has happened. You know, who likes the fact that we're now at, you know, you know, You need five different subscriptions to all kinds of streaming services to get the same thing you used to get from your one cable provider, right? It's basically dividing this up into less and less useful chunks. And another way to think about it is like we used to custom design these outcomes. So a really amazing, I don't know, a pair of shoes. But now we're being told that if we get them from the dollar store, we're getting the same thing as we went and bought the Nikes. I don't think that that's what we want. And if we're paying

a Nike price for a dollar store sneaker, I think we've got a problem. Even just abstracting all of the kind of philosophical or ideological aspects from this, if you're not optimizing your work to deliver the thing that you say is important, in this case, science, it's just not going to return as good to science by definition, right? Because you're no longer optimizing along that return. Right. You're adding it on as this bonus. And you may get something out of it, but then your question is, what are we then spending? What are we then doing this for? The way we do expiration right now is we decide on the outcome that's going to be important.

And then we go for that outcome. What's being proposed is, if you have an outcome, we'll buy it later, but we'll also have paid for all the steps in between. I can understand trying to build a new opportunity and trying to lower costs. But when you start to chip away at the entire infrastructure that's already performing what's really needed by people in an opportunity to maybe save 10%, that's probably not actually going to have the returns that you expected. Right. And I'll emphasize here that the NASA leadership and, you know, all formal statements from this administration say, we want big science results. We want cutting edge science results. We want this to continue. We want the U.S. to be leaders. And so that's the issue that there's a tension between the, I think, somewhat ideological or hope-driven approach for this. Can we spend less money and let someone else subsidize scientific research? Right. Then we'll get more. more and still wanting big results that have all been a product of this paradigm that you just described. This idea of science being a process by, again, by which you can just kind of chop

up. I think about back to the future, obviously, all the time. And Doc Brown, for those who are close watchers of the first movie, his van at the beginning, he's like an itinerant scientist is the way that they present him at the beginning of this movie, where he goes around and, like, does science for people. He, like, charges a, like, a plumber or something. And I always thought that was hilarious because who is like, oh, I need one science thing done today. Well, let me call, like, a scientist to do it.

Like, it's a very, like, it's absurdist because it does not make sense, right? Because one problem may take months or years or be partially solved or never solved. But that's in a sense, like, what is kind of being proposed here, the Doc Brown science service or the guy drives up in a van and does your science for you. Well, actually, what's being proposed is the van. It's true. Doc Brown isn't in the van. They're saying, don't worry.

We're going, we're going to make it to 88 miles per hour, but no one's driving the car. Okay, that's actually, Brinney, that's such an important point to emphasize because this goes back to my framing of, we're buying the actual pitch is to buy data. and data is not going to science itself, right? Data doesn't inherently have meaning or intrinsic value to it. It's how it's ingested and perceived, calibrated, internalized, and then processed through the process of science. And there's been a lot less investment in the actual people to do science in the last few years.

Tell me how that's been affecting you and some of your colleagues. Yeah, this has actually been going on for at least a decade. But what we track in planetary science or an astrobiology is the research and analysis funding. It's called RNA. But that part of the program at NASA and then all of the dollars coming out of the National Science Foundation, those dollars are individual grants where investigators propose what to go looking for in data or with computer models or something. And they propose it. and then a panel of experts says, yeah, this is important, or no, this isn't important,

or this is important, but you haven't told us how you would do it. Right? So they make sure that any dollar spent is really efficient and is doing the best work on behalf of the country. We have been cutting and cutting and cutting the funding in RNA. RNA, for the most part, pays for people's salaries to do the best science and to do it in the United States. and everything is visible to NASA. They can go through why you're charging for these particular analyses, what's the salary rate for this particular person,

how many hours do you think this person is going to need to do their job? It's not abstract. It's incredibly practical, and every part of it is reviewable. None of it is competition sensitive. I can't see what's happening at somebody else's institution when I'm a reviewer, but NASA can. That's different when you get into corporate structures, right? The money can be competition sensitive or internal fees or something like that, which doesn't happen at other types of institutions.

But the other thing that the RNA program does is it advances early stage technology. And that's true in Earth science. It's true in planetary science and heliophysics and all of this. And that allows us to build things that will eventually become the instrument that goes on a spacecraft. Or, you know, we learn something about a particular type of a sensor that may or may not work. and then we can advance it or we can go in a different direction. All of that is housed within the research and analysis programs, and they're all going away. And then even the money that Congress has appropriated suddenly goes missing.

So like we've been cutting for the last decade into the number of jobs we can support of scientists. And that has to stop or we're going to lose the service that we need. So, you know, that science is serving people is why it's been, important, right? The government's role is to make sure we're doing important work. The scientist's roles, we get involved in this because it's fascinating and helpful, not because we're going to make infinite amounts of money, because no scientist is getting paid what their education and their commitment is actually worth. And scientists like myself are given a choice between, do I want this answer that I'm committed to, or do I want a nine to five job? And we mostly choose the answer. And we mostly choose the answer.

And so we're all working overtime for free while that's not happening in other parts of the system. So it is getting harder and harder because the wedge is shrinking and the number of things are being asked to do for the same amount of money is also growing. I remember doing a quick analysis once. I mean, you're basically buying wages. And wages, for the most part, increase greater than because of things like insular benefits, health care costs, payroll taxes. They increase at a greater rate than inflation. And so even if you have flat funding, we had a lot of inflation a few years ago, that actually just reduces the buying power. You just can buy less of people's time as a consequence of that.

And just to be super completely clear, I mean, professors, people who work in universities, the university does not pay you to do research. They pay you to teach generally, right? So most professors get nine-month salary. And grants and funding, like you're talking about, actually pay them to only do research during those other three months or to have different relation or to hire postdoctorate students or postdoctorates or graduate students to spend all of their time doing the research on this stuff. And so it doesn't happen for free, right? We don't have, I think we made the comparison. It's like you don't build a house by throwing a bunch of lumber on an empty plot and then expect someone to just come and build it for you

because it's interesting. They need to be paid to have to be expert builders for this. Jack, where are you seeing this in terms of not just funding, but this idea that when doing more for less in terms of science is always something that's been bandied about. Is it possible to do more for less when you just have, are buying people's time or that you're basically, it's a wage function?

Where do you see the cuts beyond just people in your experience? Well, science really is people. Right. That's the bumper sticker. Science is people. I like it. And going back to what Brittany was alluding to in the overall cuts being made to RNA programs, which, by the way, is not just one program line at NASA, right? It's split between all of the science divisions. It's split even within those divisions into different buckets. And those don't even necessarily line up with the programs being offered in the grant opportunities. And so, you know, this has been a very difficult thing to track and friend of the show and in the society, Mark Sykes, just put out an investigative report that showed that we're down 30% in purchasing power from 2011. And that's so 15 years, right, where we've, over the course of the last 15 years, we've cut research and analysis funding by 30%.

And so that is less people going through the pipeline. that is less scientists and researchers doing the work that they are functionally interviewing for every year, right, to continue, you know, making these breakthroughs. Because this kind of science as a service discussion is an extension of things like the commercial crew program, the commercial orbital transportation systems program, commercial cargo program for the ISS, you know, these are all just extensions of kind of this idea that if you kick certain activities over to the private sector, you will save money as a government. But the problem is, is that for those programs, you're paying for people, of course, but you're

paying for an activity to happen. And those things are discrete. A space launch is a space launch, right? You know when it is a success and when it is not. Right. When it reaches its destination. Science, kind of by its nature, is not so product-driven, right? It's not defined by a specific activity. This fundamental research, right? It's not, you don't even know if you'll, hypothesis is right. Right, exactly.

And so the model that they're proposing to apply towards science doesn't necessarily fit the market itself because you are paying for people. You're paying for graduate students and research assistants. That's your next generation of scientists, right? This is, it is both working towards scientific discovery, but also a workforce development program, right? It is like all these things wrapped into one. And so where the science as a service approach misses the ball, I think, is that there is not that discrete product.

It is not a launch vehicle. It is not a satellite bus. In some cases, maybe there is, there are, there are elements of things that could be more easily obtained through commercial means. Certain components might be. cheaper on the commercial market than building something disposed. But when you're talking about people and people's time, there's not really a suitable, tangible replacement for that, right? It's the only thing you can't get back is time. We'll be right back with the rest of our space policy edition of Planetary Radio after this short break. What if a salty frozen lake in British Columbia holds the key to searching for life in other worlds? That's just one of the questions, Dr. Jacob Buffo and his team.

have been working to answer, thanks to generous supporters like you. Dr. Buffo is a recipient of the Planetary Society's step grants. That's our science and technology empowered by the public program, which funds groundbreaking research driven by your support. They've been studying salty lakes with chemistry like ancient Mars, chemistry that may still exist in the hidden oceans of distant icy moons. Now it's time for the next phase. With your help, the team will build artificial intelligence,

tools that let future spacecraft help find the most promising places to look for signs of past or present life and be able to do it all on their own as needed, even without waiting for instructions from Earth. They'll test it right here on Earth at Mono Lake in California and the Great Salt Lake in Utah. Since 1980, the Planetary Society's members and donors have supported science and technology projects crucial to future space exploration. Visit planetary.org slash step. That's S-T-E-E-E. today. Your support will help fund the next phase of Dr. Buffo and his team's work. Thank you. There is an assumption here that the model that we're using right now is the most expensive

option and that a commercial option is going to be less expensive, but also will have this benefit of corporations making money. Oh, it's good for the economy. But what people are not thinking about in this is that right now a lot of the expertise is actually basically donated by institutions. We're usually paying the newest people, their salaries with the grants, the way what Casey was saying. But the institution is basically like at a university, the faculty members nine months salary, even though they're going to work on that grant all year, you're only paying for three months of their salary, right? And then the younger people, the earlier career people are the ones coming up. Those people are valuable, too. All of those people have value. Why is the

idea that if a company makes money, it's more valuable than people in a research institution making money? There isn't a difference between the value of a student and the value of a person in business. Why is corporate profit thought of as more valuable than the individual? salaries that are being paid for. And this idea that it's going to get cheaper by putting it in corporations and then therefore the government's going to save more money really doesn't add up when you think about how much is being offset by the institutions that participate. Research facilities that have long-term investments in the infrastructure that then is basically

donated to the government to use. In a corporate setting, you'd have to build that entire infrastructure again. So these costs are going to balloon and they're just kind of funny math. So there's value in everybody's salaries regardless of where it's coming from on the corporate side, on the public side, on the research side, any of that. But there's this question about reinventing the wheel behind all of this that isn't being accounted for in thinking that we're going to make it cheaper by going to some corporate model before we even get to whether the value of the answer we're going to get back is

anywhere close to what we would have gotten before. Yeah. I mean, I think there's an interesting predisposition to say we know what the problems are with the current system, and I don't think any of us here arguing that this current system is perfect. Bernie, I'm intimately aware of all the challenges of working in it even as a successful scientist. But then any other alternative has to be better,

not just alleviating your immediate frustrations. And I think you're pointing out that there's a lot of challenges and problems with this alternative paradigm that really don't necessarily solve or maybe just completely flat out would not work. It's kind of like why, if you know your air conditioner is broken, you replace the air conditioner, right? It'll be more efficient. You bought a new one. You don't burn your house down. So like that's what we're dealing with here is we're saying the air conditioner doesn't work to burn down the house and get something new. The fundamental, I think it also under this kind of

approach to like, well, we're just everything is just going to be commercial. It's going to ultimately be cheaper. I think also devalues the role that fundamental science plays in just creating these industries in the first place. And so there is like an element of iteration that happens just by the process of doing it, right? Where you have science is happening, technology development is happening, commercial capabilities are happening, and they're all reaffirming one and another. And so, like, it isn't to say that, like we were just talking about, that the old system, as we, as I think has been kind of perceived as like this government only thing, is if that it was perfect, but the, this kind of alternative of commercial only, also misses the sort of intrinsic kind of feedback cycle that happens between fundamental science, applied science, and engineering and technology development. Those things need to be in concert and in balance and how. have the appropriate values associated with them. I think we're also building on these assumptions of answers to experiments that haven't fully matured quite yet.

So taking a look at the commercial crew program, I think it's been in the news quite a bit recently that SpaceX is walking back and will eventually decommission Falcon 9 and crew dragon spacecraft, which is going to leave the United States with only one commercial provider, that being Boeing and the Starliner program. that is another area where that was seen as a successful program as creating this robust capability when really there was one provider for the vast majority of the commercial crew program, which is now pulling out only to be replaced by another single provider that has needed an injection of another $300 million to continue the production of that vehicle.

And so is that ultimately cheaper than what an alternative would have been 20 years ago when that program was initiated. And it's, you can't really disprove that, but that is a problem with this path going forward. And so how much of that model is applicable to something like science, which requires a lot of, as we were talking about earlier, is that sometimes bespoke dedicated funding streams for instrument development, for funding the next generation, for doing the work of taking data and turning it into discovery. Yeah, the long term reliable capability. Brittany, I know you have to go, but I wanted to ask you, going back briefly to your discussion of scientists and time, I think people who are more sympathetic to science as a service or at least, you know, not wanting to invest in RNA as much would say, well, how can we improve the productivity of scientists?

If we can't pay them less, how do you get more out of existing scientific capabilities? and I'd say maybe even the extreme position would be, well, we're going to have advanced AIs here soon that are going to be doing science anyway, and science is going to go the way of mathematics or commercial jingles of songs or whatever kind of realm that's going to be replaced in. Where do you see that, do you see any reality there,

do you see any actual opportunity for things like AI to increase productivity that could help? And do you see yourself being replaced by an advanced AI here anytime soon? Well, I'm optimistic that at least the AI won't be as interested in talking to people. So maybe that'll help. But really, honestly, this gets sold by people who don't use it or don't interact with science. It's a little bit like your Instagram feed.

There's a whole lot of answers. And a lot of them are wrong. And that algorithm isn't getting it right, right? You're not necessarily getting truth from things. you're getting information, but the quality of the information isn't necessarily good. And that's true in AI as it is with anything else. And how we think about using it right now, what it's good at doing is helping people be more efficient, but you still need someone in the loop that knows when something's gone horribly wrong.

And so we've just kind of been relabeling things as it goes along, but it's the same process. There's a reason why it's super easy for me to tell who's sent me an AI-generated email. It's because I've seen it 100 times now, and all of the emails are the same, right? I don't get new things from this conversation. When AI is generating lots of options and finds self-consistent solutions, just because it's consistent using one perspective does not make it right. Right. It's like groupthink on steroids. And having people in the loop who can see the difference is critical. And I am not an AI expert, but I interact with it enough to understand that difference. And you can see that happening, right? There's a reason why there's news articles all the time about suddenly an AI doing something that wasn't intended to do and doing it wrong and people having to get back in and stop it. And so you're just moving the needle on where people's focus has to be. Right? We can maybe make things more streamlined. We can probably make things

more efficient, but we can't make them more right by just trusting some randomness. Right. I think there's an interesting challenge of how AIs handle utterly novel data sets, like a new planetary data set from a, you know, literally nothing has, it can have not trained on anything like that before, right? And so how does it handle that? But then also, I mean, we're seeing this, even if it's making these big strides and solving these really hard math problems, you need a mathematician to tell us if it's right, like, I couldn't tell you if it was right. And you need an expertise in able to judge itself, because it has no inherent meaning internally, meaning is derived from expertise.

Like, is this relevant or not? Brittany, I know you need to go. Is there anything else you'd want to leave us with before you have to run? No, I just want people to remember that science. isn't a unit. It's a process. And really, its goal is to serve people, right? It's to serve us. It is to, it is people helping people. And that's not what's being proposed with, with quote unquote, science as a service, right? When NASA missions are producing data, I get the data for free, you get the data for free. Anyone can go onto a NASA repository and get that data, including companies who can

go use it to make money, which plenty of them do. In this new model, none of it gets to us for free and we've already paid for it. So it's like an infinite subscription. And I'm just really concerned that we're going to lose the people, the process, and the quality of what has been fundamental in our country and on our planet for hundreds of years. So it's really cool to imagine a space economy. I want one as much as anybody else. But it doesn't exist yet. and we shouldn't throw the baby out with the bathwater, right, by expecting that cheaper is going to be valuable.

Thank you, Brittany. I really appreciate your input. Brittany is Schmidt is a planetary scientist, astrobiologist, and board member of the Planetary Society. Jack, can I tell you now the sad story of Lansat commercialization in the 1980s as an example for what we're talking about? I have been waiting to hear this story. Who among us? Please. Please, tell me.

I'm sure everyone here already knows it, so I'll go through it quickly. But I had known about this broadly. I did a little bit of reading behind it to remind myself this, I think debacle is a reasonable term for it. But in 1984, there was two commercial space bills. There was the commercial launch act that you mentioned. And then there was this commercialization of Earth imagery. So Lansat, very broadly, is a series of spacecraft that take very specific.

consistent measurements for, I think, over half a century now of the Earth. And the value comes from the consistency that these are highly calibrated. So you can compare a pixel on the Earth from Lansat 3, you know, in the 1970s to a pixel on the earth from Lansat 8 or 9 right now. And you have a situation where if you lose that consistency, you lose quite a bit of utility. And because, you know, such that the broader community cares about space data, it's space data that goes up and then points back down at the Earth, right? There's a ton of uses you can make with Lansat.

So, Jack, did you know that in 84, this bill fully privatized Lansat and gave it to a new entity called EOSAT, the Earth Observing Satellite Company? I was not aware it. So Lansat, they took over operations of Lansat 4 and then 5 during the 1980s. And that era was associated with. So at the time, researchers would have to pay per image to get. So you wanted some data product because it was privatized now. The company owning it had to operate.

They had to make their operating funds. They had to build a new one. They were going to build Lansat 6. And so they had to raise money, but also they had to make money. They had to have revenue. And so suddenly the cost of Lansat image. went up by an order of magnitude upwards from a few hundred dollars to thousands of dollars per scene. And that era is actually associated with a collapse of the number of papers that use Lansat data

because suddenly just to access it, you had to have thousands of dollars. If you got the wrong scene, too bad. There was no broader government commitment to buy data either. This was like full on, you're on your own. Sell it to other customers, sell it to us, whomever. We're not going to tell you, you know, too much beyond that. They did give a subsidy of almost $250 million, however, to build the next Lansat. Because even what happened was, you know, you were charging $4,000-ish, $6,000 in image.

A lot fewer people used it. And so suddenly their revenues weren't great either. And so you had a situation where within years that you basically had a collapse and near collapse of the system, it culminated in the launch of Lansat 6, which failed. and they're you know that this is a private in a sense of private commercial company building this not putting in the resources for that systems engineering right trying to save money and so they're incentivized to save money not to have a functional landsat things got so bad i again i always show my age when i reference the simpsons now i guess as elder millennials but there's an episode where they have

they find out that springfield still has prohibition and then at the end they like blow off some dust like oh, actually they repealed it like a year later because it sucked. No one liked it. So they passed the 84 Commercial Land Acquisition Act, sensor acquisition act, remote sensing act. And in 92, they actually undid it completely. They're like, okay, this is not working. This is so bad within eight years.

They passed a second bill that made Lansat publicly owned again. And then after the failure of Lansat 6, it became basically a fully, this is why NASA and then no. National Oceanographic agency now manage it. And data is now effectively free for use. And of course, there's a commensurate huge increase in and usage of it. And actually, we see this. We're doing this project of studying the output of data from these various scientific missions.

Lansat 5 has a very low data use compared, like a number of research papers compared. That's the privatization one. That's when he had to pay so much money to access. So you actually see this was really kind of thrown out to the wolves. And it just did not work in that sense, even for what should be the most broad market, which is Earth data, right, where we all live. I can't imagine it said that no one lives on Mars, right? There's no agricultural motivations for Mars.

You're not monitoring crop growth or other issues on Mars. You really cannot expand that beyond this. Yeah, the demand signals are not necessarily. going to be there. And I see that as that there's a fascinating case study and maybe a very extreme example. Would you even call that science as a service? Is that that's just... I think it was the commercialization of a scientific product, right? And that's, when you talk about at the beginning, like, what does science as a service even mean, right? It could mean a variety of things. This is probably the most extreme concept of that,

which is just you privatize the data collection source and you make the data product the value of what people want. And theoretically, people do want that. But they just didn't have the money to buy it, right? Because they need money from scientists. It's not a commercial consumer product. Universities aren't giving people money to work with themselves. They have to get their own grants to buy it.

And then that just makes the risk. It just slowed down the entire research. And that goes back to what Brittany was saying, that there's a social benefit. beyond a pure economic benefit to fundamental science, I think, right? And the social benefits harder to measure, but clearly a real thing

because that's why you have, you know, public institutions and not just everything privatized. And, I mean, I think there is an argument being made that the goal of the agency should be to accelerate discoveries being made, right? We as taxpayers in the United States

pay money to the government, government to perform services and activities. And for the 0.34% of our dollar that we give to NASA, we want that money to be accelerating scientific discovery. But it kind of sounds like that kind of total commercialization model, in fact, slows things down because you're adding these additional checkpoints in which currency is then exchanged, whether it's the the government and a private entity, between private entities, between the consumer, in this case being a scientist and those entities, that you add all of those additional checkpoints, it just is going to slow down the process.

Yeah. And now what I'm kind of curious in, in NASA formulating science as a service over the past many months, that what outcome do they come to is something like CST? the commercial satellite data acquisition program, right, where we buy data from individual companies that are already collecting that Earth observing data and then use that for scientific purposes. Is that the model that we go with? Is it the complete privatization, right, as Lanset 5 and 6?

Is that an avenue that they want to go down? Is it providing a service to a science mission a la la the link to? spacecraft to boost the Swift Space Observatory. You know, all of those are, you could, again, define those as science as a service, but all have completely different markets, completely different profit motivations, and a completely different relationship that you're defining between the scientist, who also is not being paid throughout any of what we just described, right? Because that is that RNA funded.

That is that dedicated money to say, we value fundamental scientific research. It is what won us the second world war. It is what created the economic prosperity of the 20th century. It is what has given us the computational power tenfold of the Apollo lem in our pocket. Ten orders of magnitude, maybe. Maybe even more. I keep thinking of a formulation of the equivalent of if a tree falls in the forest, no one hears it. We collect data and don't pay any scientists to work on it.

What do we have? It's not useful. The data has to be converted into a useful state in a way. And you're right. All of this discussion seems to have focused on that first step, the data collection step. And there's very little discussion or interest, it seems like, in the second step, of turning that data into something useful. And I think that has a lot of, as we were discussing with Brittany,

the process of science is not a thing. And so it's just, it's, you're just paying for an activity. And that's just, I think our brains of nothing else as humans who like lots of causality, kind of these innate, like you get this for that. It's hard. You're just, you're paying for a thing. And then you'll see how it turns out over time. And it takes a long time, too.

I mean, that's the other thing with science. It takes years. It's hard to accelerate social acceptance of new ideas, basically, through this process of argumentation, hypothesis. revision and so forth. Yeah. I mean, I wish it was easy as, okay, we saw this image of the surface of Mars. We have now understood that that sort of McGuffin technology that Star Trek certainly personifies,

but is found throughout science fiction of, oh, yeah, we took a picture of this thing, and we suddenly know everything there is to know about this. We know the composition of every rock on the surface of Mars just from one action. But it's not that, right? And it is certainly frustrating, and I can empathize with that frustration of, but I want to know answers to these questions now, right? Because I want to be able to ask the follow-on question, but the process of science is not linear. Right. It is not question.

Ruppie PQ model. Let's just mention very quickly a bit more that the request for information, RFI that came out earlier this year, because I think that's telling as well that shows the challenge of trying to grapple with this. I find it almost a bit encouraging, actually, based on what it didn't say. So why don't you summarize what that RFI was and what it asked for and where it didn't ask for things? Yeah. So earlier this year, feels like much longer ago, but it was just in March or end of February, end of March, sometime around the beginning of this year, Administrator Isaacman convened the ignition of it. And at the time came about just before the budget request had come out just before the Artemis II mission. had began and was one of the first actions that Administrator Isaacman had initiated.

And one of the elements of this very much felt like Apple unveiling the new iPhone is, we dropped this new RFI and this new RFI, and by RFI, I mean, request for information. These open questions that the agency was sending out to industry, to the scientific community, to the public, to other stakeholders to say, tell us about. your answer to a given series of questions. And one of those was in relation to science as a service. And it had a pretty narrow scope just in that of NASA's five science divisions, planetary science, astrophysics, heliophysics, biological and physical sciences and

Earth science, it only asked for industry and science community input on heliophysics, Earth Science and Astrophysics. And Earth Science, we already have something like we said, that CSDA program, which is a bit of an experiment in acquisition of commercial satellite data. Heliophysics, also something that typically exists within near Earth space, an activity of studying the sun. And astrophysics, which, again, we point back to the link spacecraft is kind of the prime example that has been used as science as a service. Now, this RFI was a pretty open-ended. tell us how your company or your institution could use a service-based relationship with scientific data or provide that scientific data.

And results of that RFI are not released publicly. And we have not had an RFP, a request for proposals, as to providing that science as a service out to the broader industry, space industry, or science community. And so it's kind of sitting in this middle limbo state as to NASA requested information. They received the information. At some level, I'm sure, have ingested it and begun formulating some sort of path forward for science as a service, but as of yet, as of recording, has not released a plan and certainly was not included in the most recent budget request, which, like I said,

happened just a week after this ignition event. So it certainly was not enough time to turn around any sort of resour. response. So we're kind of in this limbo state with this RFI as to what science as a service could mean going forward. And that's, I think, the crux of this conversation. Yeah, I find it's so interesting that planetary science was excluded. And I think that goes back to this. I mean, the core conceit is that there have to be other customers. And there just isn't for planetary. It's just like I'm here. And our closest planetary body, the moon, you have a program like Clips.

NASA is the sole purchaser of those Clicks landers. Well, I think, I mean, even if it's not, I mean, there's a few small things that ride along those. They're certainly not being paid for by NASA or by. They're not breaking their income off of those. Right. When we're talking about Clips, right, there's kind of two parts of it. There is the purchasing of the landing services.

And then there's the purchasing of the landing services. of available spots, both in terms of like physical space, but also power. Yeah. Because these things have only so much power to give, solar power, all of them. None of them are nuclear. But with that, those spots, you can sell those to other companies, to other nations, to other agencies within the federal government. But as it yet, the vast majority of those are being purchased by NASA.

and those spots are being filled by NASA payloads, or at least NASA affiliated payloads. And so there's the, I will say, the accounting of how much each of those landers costs, not just the landing contract itself, but also the value of all of the payload spots as filled, is kind of hard to track down because it goes across all of these different vendors possibly. But again, NASA being the primary one, you're getting most of the value is coming from the government both paying for the landing service and some, if not, in some cases, maybe all of the instruments, slots, payload slots that are available.

The idea, I think, of what was theoretically had a broader audience would be space weather, right, because there's a sound interest in, you know, not having your electronics right, if you have something in space. But even then, that's probably just other, primarily other governments, maybe some, I mean, you've got commercial satellite companies. Or like, Department of Defense, Department of Energy might, right, have some, a state, And then our science, I mean, Earth observation, obviously. And then I guess the Astrosis is which is also one that's, I mean, maybe you could also draw a connection with the, what is it, Lappitus, the Schmidt Sciences space telescope, which is not close to being online.

Right. They're still on the, well, certainly not commercial. It's like a billion fraud. It's a charity. Functionally a charity. I mean, maybe you could get some sort of like stellar photometry. You can maybe do something clever. But again, I think, you know, there's a couple other instances in NASA history in the late 1990s and 2000s when they purchased Earth observation data to varying degrees of success.

But it does seem at the end, they have to, in order for it to be useful for science, scientists at some level need to say what the needs are. Right. And so if you're just buying data and, you know, and you can maybe do some interesting things, as Brittany was saying some novel stuff. but it's all kind of just incidental, or it's all, you know, you build off of what you can do, but it's not the core of your science program. And I find it interesting after 40 years, the data buys are still in the single or tens of millions of dollars,

right, relatively very, very modest over the course of, you know, a $7 billion-ish-dollar science budget. And so there's nothing that has clearly taken off. There keeps being ongoing efforts to try, and just a resistance for it to truly succeed in a way. Because otherwise, you'd see a lot more of these companies. Great, we'll have NASA buy stuff. It's just expensive to put things in space.

And that's not who's, you know, scientists, as Brittany correctly pointed out, are not, you know, loaded. We're not in the era of your gentleman scientist, right? Your large landowner doing your studies for the most part. Well, in a way, it's a more mature scientific field, right? It is you have institutions and processes and there is a lot of value, as Courtney points out, well, there's a baby in that pathwater, right? And so there are things that could change.

And I do see, and maybe this is a great follow-on activity, is identifying where a commercial service does make sense as it relates to the science program, because it certainly is not in replacing the actual activity of science. But then the thing is that then you start getting into conversations about risk tolerances and other parts of the pipeline that are not necessarily even yet data collection. But you're talking about, you know, administrator Isaacin talks about companies like Rocket Lab, right, as an example of one that build satellite buses, right? And has standardized that process and is rolling them off assembly lines, which is certainly a significant. advancement. And you have companies like space, that are building in other companies, Blue Origin and Rocket Lab as well,

who are building and building towards reusable launch vehicles, which, again, theoretically, reduces the cost of access to space, which I know that is, again, a whole other topic. But again, those are all enabling activities for what is then data collection, turning that data into science. Yeah. And so that part of the equation, there is not a compelling answer for how do you spend less money to get more out of people that doesn't result in less people getting money or people getting less money? I mean, I think that's always, I keep going back to at some level, the problem here

is that this is just a mismatch of domains, that science is to some degree. I mean, this always goes back to why Vannevar, I realize, Vanever Bush in 1945 wrote science, the endless frontier of like, why we need public investment? Because fundamental science like this just does not happen

in a pure self-interested commercial ecosystem. And so this is like that, by definition, it's just not easy to map onto this. And anything you do get is probably going to be this you know, maybe bonus stuff.

or nice to have stuff. But yeah, I think like you, I was thinking about what would be, what would I like to see going forward, you know, assuming that this, the fundamental structure as maybe simplistically conceived is not possible. I think it is something. Can you really invest in find more ways to make that process of science more efficient and easier? We've talked about this a bit with the lowering the paperwork burden on scientists that

has been actively increased in the last two years, making it easy. easier for them to actually do science, giving them modern tools. And I do think there's actually quite a bit of opportunity, as Brittany said, with assistance from AI tools. But at the end of the day, you just need to pay people to sit and think and do science and take away as many roadblocks to that as possible. And I think focusing on how can the commercial aspects enable that precise and necessary and important data collection, not just any data. Yeah. And I will also, I'd be remissed if I didn't also mention the issue that we've been dealing with for the better part of the last six months, which is the inclusion of even more barriers through the Office of Management and Budgets, uniform guidance for federal assistance. Right.

It is in fact adding a number of layers of bureaucracy, what they're calling pre-issuance review, but the review of grant decisions by, political appointees who are not experts in the field, prohibiting collaboration with international partners, prohibiting the use of funds to, in fact, share the results of studies. And again, there are areas where, I mean, maybe it shouldn't cost as much as it currently does to publish a paper. Maybe conferences have also grown in expense, and those are areas you could look into to to find cost savings, but prohibiting individuals from even participating in those also adds a burden on them. Is it then worth them to ask those questions and even apply for those, that funding, and to go through this rigorous process, if they can then not even share those

results with their peers, let alone the public, right, who ultimately pay for these discoveries. And so these are compounding issues that all are a part of this, I think, nebulous topic of science, right? The future of science. And so it's really expanding my horizons as to where these issues are intersecting. And not necessarily in a good way. But maybe out of this, we can help build a better system of science that does fully support the individuals, that fully supports the institutions and this kind of collective knowledge and process that we define, I think, broadly as science, but how do you do it in a way that also optimizes for cost, optimizes for capability, optimizes for these things that are also deemed as incredibly valuable?

And you see, again, programs like clips and commercial crew and these things that are that are highly valued politically and economically, but don't always necessarily have a scientific case for them. And so it's, again, balancing all of these different impoverdemeanor. puts all of the different stakeholders and appropriately valuing what it is that the government and people do, which is in this case, science. Well, you can count on the fact that, Jack, you will be there in the mix and as will I in the planetary society as we go through on this. Jack, thank you for joining me and talking about this today as we kind of figure this out ourselves. And I welcome feedback from our listeners about what does science as a service mean to you.

Could it work? How would it work? Surprise me. sound pretty skeptical because I am, but I want science to work better, as Jack said. And I think there are ways to make that happen. And I'll point out Jack as well, so far when we're recording this, that application of those draconian rules from the Office of Management and Budget is temporarily suspended by the current spending bill. It seems like it's not getting any more popular in Congress. And we hope that those will be resolutely rejected in upcoming funding bills. Is that still a possibility? I certainly hope so, that we are, of course, tracking that individual agencies are going their own ways in implementing some of these rural changes. And so the issue has become a

lot more complicated. And so a definitive solution from Congress prohibiting the implementation of the uniform guidance would be a great path forward. And like you said, this is bipartisan opposition. Both sides of the Hill, House and Senate, are opposed to the implementation of these draconian rules. So now it's just on to December 11th as the next fiscal cliff that we are careening towards in between now and then we have the November midterm elections where we will hopefully soon after that understand the balance of power in Washington and the 120th Congress. All of these things are factors that we are keeping our eyes on as we go into the latter part of 2026. You will hear all about it in future episodes of the Space Policy Edition.

Jack Carolli, our chief of advocacy at the Planetary Society. I think that's the first time me saying your new title. I think so. Well, thank you, Casey. Thanks for being here. That's it for this month's episode, a planetary radio space policy edition. I'm Casey Dreyer, the chief of space policy here at the Planetary Society, also the host of this show. The Planetary Society is a global member-supported nonprofit organization.

If you're not a member, please consider joining us. Planetary.org slash join. If you are a member, thank you. You enable this show and all of our other great work to happen. Also responsible for this show, Ray Paoletta, our producer. Kate Howells and Mark Hilverta are associate producers for the show. Sarah Al Ahmed is also the host of the weekly edition, of course, of Planetary Radio, executive producer.

Matt Kaplan, the Book Club Edition. the Book Club Edition. Don't miss that show either. Andrew Lucas is our audio producer and makes us sound good. Thank you so much, Andrew. The theme for this show was written and composed by myself and my colleague at the Society, Merk Boyan. Until next month, at Astro.