Neighborhood Improvement Association to hold free income tax prep sessions
SAVANNAH, Ga. (WSAV) — The Neighborhood Improvement Association (NIA) and the Volunteer Income Tax Assistance (VITA) program will hold free income tax prep on Saturday, April 12.
The event will be held at the Moses Jackson Advancement Center, located on 1410 Richards Street, on Saturday from 10 a.m. to 3 p.m. NIA and VITA will also provide prep for back taxes, with years dating as far back as 2019.
This date is urgent, because anyone expecting a refund from 2021 must file by April 15th to receive the refund. According to the IRS, over 38,000 individuals in Georgia have not claimed refunds that total $33.5 million.
You will need to bring the following material to the site:
Official Photo ID for Taxpayer and Spouse
Social Security Card or ITIN letter for all on return
All W-2's and other income information, Unemployment (1099-G), Retirement (1099-R), 1099 NEC, 1099 MISC and Social Security Benefits (SSA-1099), if applicable
Healthcare Forms 1095-A (Marketplace-ACA)
Home Mortgage Interest (Form 1098)
Forms 1098-T (Education) or 1098-E (Student Loan Interest) (if applicable)
Childcare Expenses (if applicable)
IPPIN – IRS Identity Protection Pin (if applicable)
Checking & Savings account information for direct deposit.
For more information, click here.
Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
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They're doing their academic work in the morning, and then we're able to incorporate all the proven learning science techniques — spaced repetition, rapid feedback, regular quizzing — that help kids learn without cheating. Abby Mellott: Alex, let's transition to you. Tell us about your journey from public school to Alpha School and what it was like moving from one end of the spectrum to the other. Alex Mathew: Yeah, very wild experience. At my traditional school, I spent about eight hours a day in class, learning the normal way — teacher at the front of the room, students at their desks. Then I'd go home and spend another three or four hours locked in my room trying to study, finish homework, and complete all these busywork assignments. After that, I would try to cram in all the things I actually loved doing, like hanging out with friends or exploring what my passion is. I would end up losing a lot of sleep, and every day felt like I was changing my focus. I was struggling on the academic side, and on the passion side and being present with my friends and family. Overall, it was just a bad quality of life. I was also just so tired of being defined by this one metric — grades — and constantly comparing my grades with my friends. It turned into this toxic feedback loop. When I heard about Alpha, I was like, 'I have to go there.' What really stood out was the focus on process-based learning and actually learning how to learn. When I came to Alpha, I was reading at an eighth-grade level — even though I'm an 11th grader — but I was doing college-level math. So I could go at the pace I needed to for each subject. Now, I'm at a college level in both reading and math. But my favorite part about Alpha isn't the academics, it's the masterpiece. So a masterpiece is a passion project where you dive deep into something you love, but with the highest standards possible. We're not aiming to be the best for our age group; we're aiming to be the best in the world — like an Olympian. You can take it in any direction and go as deep as you want. When I got to Alpha, I quickly found what I was passionate about, and I'm still diving deep into that rabbit hole. Abby Mellott: Very cool to hear your story. I'm sure your parents are proud of you and glad that you convinced them you should go to Alpha. Alex Mathew: Yeah. It took a lot of convincing. Abby Mellott: Can you talk about some of the partnerships or collaborations you're working on — whether with tech companies, universities or others — to help prepare students for the job market, especially as AI continues to evolve so quickly? Dr. Ju Long: In my own classes, where I teach machine learning and generative AI, we often have to be resourceful. Universities don't have the deep pockets that major tech companies do, so we work with open-source technologies whenever possible. One company we collaborate with is GaiaNet. We also use open-source large language models like Meta's Llama, as well as many other models that are publicly available. And on the university side, we benefit from partnerships like the one we have with Microsoft. Through Azure, students receive $100 in credits, which is plenty to support a full course in a semester. MacKenzie Price: Bjorn, since we're talking about preparing students for an AI-driven market, and I know you're already leveraging AI for other purposes, are you also offering AI training as well? BJORN Billhardt: That's a good question. We really have not created a "how to use AI" course. Actually, I feel that a lot of the AI courses out there right now might be less effective than they appear to be at first. I often compare it to when the Internet first became popular. Back in 1997, there were tons of courses on "how to use the Internet," but in the end, it was really just about learning how to search online. I feel like a lot of today's AI courses are similar — focused on things like how to write a good prompt. That's valuable, but it's a five-minute training, not a full course or curriculum. So I predict that, just like there's no degree in Internet Studies today, we probably won't see a degree or full curriculum in AI Studies. MacKenzie Price: I don't think there will be either. But what we focus on with our students is helping them become AI-first in everything they do. I think that's going to be the biggest shift moving forward. We've actually partnered on an initiative called Gauntlet AI — it's a 12-week boot camp program. Our first cohort ranged in age from 17 to 54, and after just 12 weeks, many of them graduated with $200,000 job offers waiting for them. Corporations want AI-first people, not because they've graduated in AI Studies, but because they can go be expert marketers, coders, or entrepreneurs. That's what's so exciting — giving people the durable skills they need. And that's exactly what we want for our students: to go into whatever passion or interest they have and utilize AI to free up more time for the human side. BJORN Billhardt: I think the best way to prepare people is through real projects — the kind where you actually have to use AI to collaborate with others and create something, not just learn from a chatbot. As for the future of jobs, I think they're changing rapidly. STEM fields have traditionally been in high demand, but — and I may have a slight bias as a liberal arts major — I believe liberal arts skills are going to become more and more important. Skills like asking the right questions, connecting ideas across disciplines, and seeing the bigger picture will be paramount. Those are the kinds of human abilities AI won't easily replace in the next few years. MacKenzie Price: I'll share an example of that: We have a student at Alpha named Sloan who has 2 million TikTok followers. In the past, success in tech was all about knowing how to code. But Sloan realized that coding an app is the easy part; distribution is the real challenge. Building an audience is the harder, more valuable skill. Alex is leveraging this too, because if you can reach customers, the rest becomes much easier. Abby Mellott: Shifting back to you, Alex. You mentioned your passion project, which incorporates self-care, mental health and AI. Can you tell us a little more about it? Alex Mathew: Yeah, so the project I'm building is called Berry. It's an AI-powered stuffed animal you can hold and talk to about your mental health. I'm working with therapists, neuroscientists, and psychologists to design the back end, making sure all the advice Berry gives is very personalized, vetted by experts, and that it's legit. I believe that AI-powered transitional objects, like plushies, could actually be better than therapists for teens. There are numerous reasons behind this. One, teens often struggle to connect with much older therapists. Also, there's stigma around seeing a therapist, and traditional therapy can feel like a big commitment. Berry reframes support as a simple daily reflection tool — just five minutes a day — through something cute and approachable. And I believe that will genuinely improve mental health outcomes. Right now, I'm preparing to run a study with a group of 20 teens to track how Berry impacts their mental health over a six-week period. I'm also making a huge sprint toward partnering with a company like Build-A-Bear to launch a "Build-a-Berry" program that would let teens customize their Berry plushies. But my goal isn't to be the best plushie maker in the world — it's to build the best mental health tool in the world. That means focusing on the AI, rather than the manufacturing side, and finding the right partnerships to help streamline it. Abby Mellott: So is it basically a unit that sits inside the bear, like a small computer? And does it talk back to you? Alex Mathew: Yes, it is. And it talks back to you — you can have full conversations with it. There's also an app connected to it where you can enter information about yourself, and it customizes to you. I actually set a cap on how long you can talk to Barry. It's only an hour, because I don't want it to replace real friendships. It's meant to be a supplement. And so it will remember your name and say things like, 'Mackenzie, why are you talking to me so much? You should go talk to your friends.' Abby Mellott: In a more extreme situation, would it suggest to someone that they seek out more help? Alex Mathew: So if you go on Google and type in something related to self-harm or harming others, it'll pull up the National Suicide Hotline. But the problem is that people often don't really want to take action on it. But if someone is talking about those things with Berry, there's an emergency contact system in place. It'll text or call the emergency contact you set at the beginning, and it has to be a registered adult. In the future, I want Barry to be free for schools and covered by insurance. This summer, I'm going to a private school conference with Alpha, and I'm planning to show private school principals why they need to have a Barry in their counselors' offices, so kids can take one home with them. MacKenzie Price: And think about the financial barrier that this is going to remove, as opposed to the cost of weekly therapy, right? Abby Mellott: We touched on this earlier, but what about ethical concerns around data privacy and bias when using AI platforms? MacKenzie Price: Obviously there are valid questions about data privacy. I'm not going to pretend to be an expert on that. What I am an expert in is how to educate children really well. I understand there are concerns, but what we can show is transformative. One of the amazing things about our AI technology is that it's like doing a CAT scan of a child's brain. We know exactly what they know, what they don't know, and where the gaps are — and we can go in and fill those holes. Another thing that excites me is how AI lets us map not only a student's knowledge graph but also their interest graph, and then overlay the two. So that seven-year-old boy who hates to read but loves the Avengers and plays soccer with his best friends? Suddenly, he's reading a choose-your-own-adventure story about saving the world with his soccer buddies — at exactly the right Lexile reading level for him. Suddenly, he wants to read. You can extend that same approach to learning math through fashion design, or teaching financial literacy based on a student's personal goals. So yes, I get very excited about it. And no, I don't spend as much time worrying about the other parts. Abby Mellott: To wrap it up, what role do you see AI playing in education over the next five years? MacKenzie Price: There has never been a more exciting time to be a five-year-old, and there has never been a more exciting time to be a teacher. It's so important for people to understand that education is finally at the point where it can be truly transformed. It's one of the last major industries to experience such a profound change. I hope we see wide-scale adoption, where people really jump in and use these tools fully — not just continue with the old model and add a little smattering of AI here and there. Dr. Ju Long: To build on what Bjorn was saying, it's like that image where three people are standing on the beach and a tsunami is coming. We are definitely already facing the wave, and there's no way to avoid it. The only way forward is to go through it. But I think, in order not to get swept away by the wave, what anchors us is still the human side of learning. In our college, a lot of people, including my own students, ask me, 'Am I going to be replaced by AI?' That's a very legitimate question. What I tell them is: your human agency matters. You decide what you want AI to do for you and how you want to learn. It's the same for faculty — we ask, "Are we going to be replaced by AI?" But when we look at AI as our partner, we can see there's so much potential. We are still in the pilot's seat, even if AI acts as a co-pilot. BJORN Billhardt: What I'm seeing now, and what AI is enabling, is a real shift in the role education plays, not just for kids but also for adults who will need to be reskilled and adapt completely to new ways of working. I believe that's where the world is headed: education becoming integrated into daily life and work. It's a little scary, but it's also incredibly enabling. If we can figure out how to make that kind of education feel productive, not creepy, it will move education from being on the periphery of our society to being central. Alex Mathew: The last thing I'll add is that AI is helping create a more level playing field. It means you can be the best in the world at what you're doing. And it's really leveraging young people's natural curiosity. It allows them to discover what they really love doing at an earlier age, unlocking that potential sooner. Plus, there's now a much wider range of possibilities available to them.
Forbes
2 hours ago
- Forbes
In Facebook Case, the Cost-Sharing Regulations Pass Their First Test
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The two most critical inputs when applying the income method under the 2009 temporary cost-sharing regulations (T.D. 9441) are financial projections and discount rates, and Pugh rejected the IRS lead witness's testimony on both. Pugh was even more critical of the IRS's reliance on an unusual and aggressive variation of the income method. The cumulative monetary effect of these setbacks for the IRS will be dramatic. The final platform contribution transaction (PCT) value won't be official until Rule 155 computations are complete, but Pugh estimated that applying the income method with reliable inputs would yield a roughly $7.8 billion PCT value — far closer to Facebook's $6.3 billion valuation than to the $19.9 billion value derived from the IRS's method. Based on this estimate, less than 11 percent of the IRS's total PCT value adjustment would stand. The tax revenue gain will still exceed the IRS's litigation costs, but in purely monetary terms, Facebook hardly looks like a major IRS victory. However, a win for Facebook on the facts isn't necessarily a loss for the IRS. The $12.2 billion difference between the IRS's PCT valuation and the value tentatively cited by Pugh was entirely attributable to inputs and other methodological details. These were ultimately questions of fact, and their relevance is limited to the facts of this case. On questions of statutory and regulatory interpretation, which have ramifications that extend far beyond this case, Facebook was a resounding IRS win. Billions of dollars are at stake in Facebook, and the case pairs one of the world's best-known and most polarizing companies with one of U.S. tax law's most widely exploited and frequently criticized profit-shifting tools. But Facebook is, above all, the first judicial test of the cost-sharing regulatory regime created by the 2009 temporary regulations, which was the product of a painstaking effort to fix the loopholes (real or perceived) responsible for the IRS's losses in Veritas Software Corp. v. Commissioner, 133 T.C. 297 (2009), nonacq., AOD 2010-05, and Inc. v. Commissioner, 148 T.C. No. 8 (2017), aff'd, 934 F.3d 976 (9th Cir. 2019). In Veritas and again in Amazon, which was later affirmed by the Ninth Circuit, the Tax Court held that the buy-in requirement for 'preexisting intangible' contributions in the 1995 regulations (T.D. 8632) excluded residual business assets like goodwill and intangibles developed over the life of the CSA. This was a consequence of restrictions that, according to the Tax Court and Ninth Circuit, followed from reg. section 1.482-4(b)'s definition of intangible and the modifier 'preexisting.' Because the buy-in payments derived from the IRS's discounted cash flow (DCF) valuations included the value of residual business assets and later developed intangibles, courts held that the 1995 regulations prohibited their use. To stop the uncompensated transfers of valuable assets allowed by this interpretation, the 2009 temporary regulations and the substantially identical 2011 final regulations (T.D. 9568) replaced the term 'preexisting intangible' with 'platform contribution.' This decoupled CSA participants' PCT payment obligations from any definitional limitations inherited from reg. section 1.482-4(b). It also clarified that the PCT value must include the value of intangibles developed under the CSA to the extent that their development benefited from access to the platform contribution. Arguably more important than these terminology changes was the introduction of specified PCT valuation methods that mechanically prevent artificial exclusions. The 1995 cost-sharing regulations cross-referenced reg. section 1.482-4 for pricing methods, and DCF valuations are permitted by reg. section 1.482-4 only as 'unspecified methods.' Courts thus consistently turned to the comparable uncontrolled transaction method, which allows for the kinds of exclusions that DCF valuations do not. It also indulged the historical judicial preference for transactional methods. The specified PCT valuation method at issue in Facebook is the income method, and it is a close cousin of the DCF valuations rejected in Veritas and Amazon. Similar to a DCF valuation, it derives the PCT value by discounting projected income to present value, and it provides no plausible basis for carving out excluded items. The IRS's ability to defend its selection of the income method in Facebook was thus the first test of the new regulatory scheme's ability to prevent another Veritas or Amazon. To some, it seemed hard to conceive of any plausible basis for reading the old exclusions and methodological preferences into the new law. It would be counterintuitive, to say the least, if the interpretations of the 1995 regulations that compelled Treasury and the IRS to draft a more elaborate version of reg. section 1.482-7 from scratch somehow remained viable under the new regulatory scheme. Construing the 2009 cost-sharing regulations to exclude residual business asset value and prioritize transactional methods would be like reading Prohibition into the 21st Amendment. It would turn the regulatory scheme on its head. But this view was never unanimous. Undaunted tax advisers proposed ways to resurrect the old loopholes, and skeptics criticized the whole effort for legitimizing an irredeemably flawed profit-shifting technique. Until the Tax Court released its Facebook opinion, the only real signal of how courts would interpret the new regulations was in a footnote to the Ninth Circuit's Amazon opinion: "If this case were governed by the 2009 regulations or by the 2017 statutory amendment, there is no doubt the Commissioner's position would be correct." What's correct may not have been in doubt. What would actually happen when a taxpayer tested this prediction certainly was. Facebook's briefs attest to what must have been a determined and all-encompassing search for a winning legal theory, and some of Pugh's comments at trial arguably suggested skepticism toward the income method. The legal questions presented in Facebook won't be definitively resolved until at least one or, more likely, multiple appeals courts confirm the answers. But in Facebook, the income method and the regulatory scheme that introduced it passed their first major test. What was clearly correct to the Ninth Circuit panel that decided Amazon was clear to Pugh as well. Any inferences to the contrary drawn from Pugh's questions at trial and dissent in 3M Co. v. Commissioner, 160 T.C. No. 3 (2023), were apparently misguided. Pugh found that the IRS derived its PCT value from a severely flawed application of the income method, and these findings had a drastic effect on the PCT value. But she unequivocally affirmed the general validity of the income method, and by extension the regulatory scheme, despite Facebook's determined effort to discredit it. As the opinion concludes: 'Applying the statute and regulations, we conclude that using the income method to determine the requisite PCT Payment value and resulting payments for 2010 produces an arm's-length result if the correct inputs are used. . . . The regulations themselves are not invalid merely because they impose a limit on the expected return on [intangible development costs] at a discount rate reflecting market-correlated risks.' The basic premise underlying the income method is that, for CSAs in which only one party makes any nonroutine platform contribution, the PCT value should equal the difference between the net present value (NPV) of entering the CSA and the NPV of entering the best realistic alternative transaction. The PCT value is thus the difference between the NPV of the PCT payer's reasonably anticipated operating income under the cost-sharing alternative and the NPV of its operating income under the hypothetical best realistic alternative. In general, although not in Facebook, the PCT payer's best realistic alternative is to license the right to exploit the cost-shared intangibles from an independent developer. The NPV of the best realistic alternative is thus the present value of the PCT payer's expected returns as a hypothetical licensee, as determined using either the comparable profits method or the CUT method. In effect, the income method forces the PCT payer to hand the expected NPV excess associated with CSA participation back to the participant responsible for the nonroutine platform contribution. This leaves the PCT payer with an expected return on the cash it invests in the CSA equal to the cost-sharing alternative discount rate, which represents the return that a market investor could expect to earn on an investment with the same risk profile as the CSA activity. If the PCT payer makes nonroutine contributions specific to its own territory, the income method requires that the payer's best realistic alternative be adjusted to reflect a return on its contributions. This approach follows from the general 'investor model,' which provides that all PCT valuation methods should offer CSA participants a return on their aggregate net investment commensurate with the CSA activity's risk profile. A corollary of this principle is that all cash contributions included in 'aggregate net investment' should have a uniform expected rate of return, regardless of whether they take the form of a PCT payment or a cost contribution. As reg. section 1.482-7(g)(2)(ii) explains: 'The relative reliability of an application of a method also depends on the degree of consistency of the analysis with the assumption that, as of the date of the PCT, each controlled participant's aggregate net investment in the CSA Activity (including platform contributions, operating contributions . . . and cost contributions) is reasonably anticipated to earn a rate of return (which might be reflected in a discount rate used in applying a method) appropriate to the riskiness of the controlled participant's CSA Activity over the entire period of such CSA Activity.' The method's logic is sound. The income method is appropriate only when the PCT payer makes no nonroutine platform contributions, so the payer's principal contribution to the CSA will be the cash it invests through the PCT payment and cost contributions. The arm's-length return for a cash contribution is the expected return available to market investors for bearing the risk associated with the CSA activity, and this is what the CSA discount rate represents. Unless the PCT payer makes nonroutine contributions of its own, any excess in its expected returns over the CSA discount rate must be attributable to the PCT payee's platform contribution. One could reasonably suggest that the discount rate for developing sophisticated and potentially extraordinarily valuable technologies, which Pugh found to be 17.7 percent in Facebook, overcompensates PCT payers that don't functionally contribute to cost-shared intangible development. But it prevents the far more egregious results made possible under the 1995 regulations by the residual business assets exclusion, the use of decay curves and finite useful lives, and the general judicial aversion to income-based valuation methods. The income method generates an aggregate PCT value that reflects the full NPV difference between alternatives, and it provides no basis for carving out value attributable to excluded assets. If the income method didn't establish a meaningful limit on profit shifting, a taxpayer like Facebook wouldn't make such a determined effort to invalidate it. Facebook upheld the general validity of a method that aggregates the value of all platform contributions, and in doing so, it implicitly rejected the notion that a residual business asset exclusion survives hidden somewhere in the 2009 and 2011 regulations. Pugh expressly rejected that notion as well, and in short order: 'Petitioner also spends a couple of pages in its opening brief on an argument that Facebook Ireland should not be required to compensate Facebook US for residual business assets. It is true that the definition of intangible property in the second sentence of section 482 in 2010 was limited to the intangible property listed under section 936(h)(3)(B). But the first sentence of section 482 has no such limits; the statute does not constrain the contributions to a CSA that might be compensable through a PCT Payment.' Facebook's more intricate methodological objections, including its 'zero NPV' critique, fared no better. During briefing, Facebook's zero NPV argument seized on the arithmetic relationship between the PCT value and the NPVs of the two alternatives. Because the PCT value is equal to the NPV of the cost-sharing alternative minus the NPV of the licensing alternative, the post-PCT NPV difference between the two alternatives is, by definition, zero. In other words, the income method requires that the PCT payer transfer all of the incremental value associated with entering the CSA back to the PCT payee. According to Facebook, the arm's-length standard entitles cost-sharing participants to retain some of the NPV excess associated with CSA participation. However, as Pugh rightly observed in her opinion, claiming that a PCT payer's cost contributions have an expected rate of return in excess of the discount rate would discredit every PCT method based on the investor model. This claim, the opinion explains, implies that PCT payers should receive a preferential rate of return in excess of what a market investor would receive on the same investment: 'Petitioner's objection that a generic investor would seek a return that is greater than its cost of capital proves too much. It necessarily assumes that this investment should be more attractive than another similar investment. The arm's-length standard does not require a preferred return (a positive NPV); it requires a return comparable to returns on other similar investments. Moreover, petitioner does not explain why in a controlled transaction, such as this, a positive NPV for Facebook Ireland would not result in a negative NPV for Facebook US.' Another way in which the income method allegedly shortchanges PCT payers is by denying them a return for the entrepreneurial risks and functions associated with exploiting the cost-shared intangibles in their territory. Echoing reg. section 1.482-7(g)(4)(vi)(E), Pugh explained that any such contributions can be accounted for by properly valuing the licensing alternative: 'To the extent petitioner's objection is that Facebook Ireland receives no return for its entrepreneurial contributions, that is addressed by proper comparables for the licensing alternative. . . . It is incorrect therefore to conclude that the income method denies an economic profit for any entrepreneurial efforts of the PCT Payor. Petitioner's objections are addressed through selection of the proper inputs into the income method.' Consistently applying this reasoning also led Pugh to reject the way in which the IRS applied the income method in Facebook. The regulations generally assume that the PCT payer's best realistic alternative transaction will be to license the cost-shared intangibles from the developer. This assumption shifts all development risk to the developer, but it leaves the risks associated with exploiting the cost-shared intangibles with the PCT payer. As the final cost-sharing regulations provide (in reg. section 1.482-7(g)(4)(i)): 'In general, the best realistic alternative of the PCT Payor to entering into the CSA would be to license intangibles to be developed by an uncontrolled licensor that undertakes the commitment to bear the entire risk of intangible development that would otherwise have been shared under the CSA. [Emphasis added.] But the IRS valuation expert instead used a 'services alternative' as the best realistic alternative, which treated Facebook Ireland as though it were a low-risk marketing services provider. Under the services alternative, Facebook Ireland received a cost-plus markup of 8 percent, which was nominally based on a set of marketing services companies that bore none of the exploitation risk typically associated with the licensing alternative. Although the 8 percent markup was within the interquartile range (6.8 to 14.2 percent) for the comparables set, it was well below the median value (13.9 percent). Whether it's necessary or appropriate to reward PCT payers with an expected return consistent with the returns of real risk-bearing licensees is open for debate. But the reason that Facebook's theoretical criticism of the income method failed is also the reason that, at least under the regulations, the IRS's services alternative approach was inappropriate. Calculating the PCT value by reference to alternatives with drastically different risk profiles also raises major practical problems, including those associated with a wide discount rate differential that cannot be attributed to a specific risk. Unlike a services alternative, the licensing alternative can differ from the cost-sharing alternative in narrow and predefined ways that relate only to development risk. It's unclear why the IRS opted to use a novel and more aggressive variation of the income method when the method's overall validity was at stake. But it was logically consistent for Pugh to uphold the income method in general while rejecting the method's application in Facebook, and the trade-off for the IRS was a favorable one. By confirming the income method's general validity, Facebook tentatively vindicates the foundations of the current cost-sharing regulations. Pugh rejected Facebook's attempts to create a new residual business asset exclusion and invalidate the investor model, both of which were critical for the regulatory scheme to function. But Pugh's endorsement of the income method's arm's-length bona fides in Facebook followed from her interpretation of the arm's-length standard in general, which could have implications that extend far beyond cost sharing. For Facebook, the income method's zero-NPV effect is invalidating because it creates a conflict between reg. section 1.482-7(g)(4) and the arm's-length standard. This assumes that Treasury and the IRS had an obligation to conform reg. section 1.482-7(g)(4) to the arm's-length standard. It also assumes that the arm's-length standard is a transactional and comparables-based concept, regardless of what the regulations say on the matter. As noted in Facebook, this interpretation implies that any transactional evidence at all takes priority over the methodological reliability standards specified by regulation: 'Where there are no uncontrolled comparables, petitioner maintains, the arm's-length standard requires a 'method that is expected to most closely approximate the way in which unrelated parties price transactions.' Petitioner submits that this approximation can be accomplished through sources such as peer-reviewed academic literature and broad industry standards.' The two assumptions underlying Facebook's argument are related, and the distinction between the two is often blurred. But they are distinct. Whether Treasury and the IRS have a statutory obligation to adhere to something that falls within the ambit of the arm's-length standard is one question, and whether they have to interpret the arm's-length standard in a narrow and archaic way is another. On the first question, Pugh emphasized that the applicable statutory standard established by the first sentence of section 482 is a clear reflection of income. Her opinion observes that 'neither sentence of section 482 expressly adopts the arm's-length standard,' which 'originated in the regulations promulgated under the Revenue Act of 1934.' Only the sentence added by the Tax Reform Act of 1986 directly addresses controlled intangible transfers, Pugh said, and it does not support Facebook's contention: 'The only statutory touchstone relating to intangibles in section 482 is the 'commensurate with the income' requirement. That addition seems to move the statute away from, not toward, an 'arm's length' standard, at least as petitioner defines it; it requires compensation commensurate with the income earned in the transaction. [Emphasis added.] The Facebook opinion doesn't directly say whether Treasury and the IRS could issue regulations that openly repudiate the arm's-length standard. But if the statute doesn't bind Treasury and the IRS to the arm's-length standard, then any obligation to apply it would be a self-imposed regulatory restraint on their broader statutory authority. It would follow that Treasury and the IRS have the right to specify the terms of that self-imposed restraint. However, in Facebook and other best method cases, the authority to openly abandon the arm's-length standard is less important than the discretion to interpret it. On the second question, Pugh was unequivocal. Drawing heavily on the Ninth Circuit majority's reasoning in Altera Corp. v. Commissioner, 926 F.3d 1061 (9th Cir. 2019), rev'g 145 T.C. 91 (2015), Pugh rejected the antiquated interpretation of the arm's-length standard favored by Facebook and other taxpayers: 'In Altera, the Ninth Circuit expressly held that in the light of concerns over third-party comparables, a focus on internal allocations that follow economic activity is an appropriate method to reach an arm's-length result.' Pugh's unqualified reliance on Altera in Facebook is significant in multiple respects. Although Altera is binding circuit precedent in Facebook, Pugh's opinion reflects a broader acceptance of the Ninth Circuit's reasoning. It also confirms that, at least in the Tax Court's view, the Ninth Circuit's holding was unaffected by Loper Bright Enterprises Inc. v. Raimondo, 603 U.S. 369 (2024). Therefore, all taxpayer validity challenges targeting the cost-sharing regulations' treatment of stock-based compensation, including in Abbott Laboratories v. Commissioner, No. 20227-23, and McKesson Corp. v. United States, No. 3:25-cv-01102, should fail. Perhaps even more significant, Pugh's reliance on Altera in a best method case thwarts a ubiquitous and foundational element of taxpayers' arguments in methodological disputes. As the Facebook opinion explains: 'Petitioner attempts to convert the arm's-length standard, as defined in Treas. Reg. section 1.482-1, into an independent rule. But nothing in the text of section 482 bars Treasury from prescribing what arm's length means when no comparable transactions can be identified. Section 482 does not contain the words 'arm's length'; rather, its focus is on clear reflection of income and preventing tax evasion in controlled transactions.' In other words, neither section 482 nor reg. section 1.482-1's general articulation of the arm's-length standard provides any basis for invalidating the method-specific provisions that apply them. This is critical because manufacturing such conflicts has become the basis for taxpayer attacks on all income-based methods, including the CPM in Medtronic Inc. v. Commissioner, T.C. Memo. 2022-84. If legitimized by courts, those conflicts would twist the section 482 regulations into an ineffectual knot. The significance of upholding one of the centerpieces of the 2009 cost-sharing regulations, and by extension the regulatory scheme itself, in Facebook can't be understated. But the Tax Court's broader acceptance of Altera, and the corresponding rejection of an inappropriately narrow interpretation of the arm's-length standard, is arguably even more important. For the IRS, these victories on the law far outweigh its loss on the facts in Facebook.
