After decedent’s daughter was removed as executor for failing to administer the estate, including the failure to pay the mortgage and other costs of maintaining the decedent’s residence which the daughter continued to occupy, the court gave the daughter the right to purchase the residence at a price to be agreed upon with the decedent’s son as the other beneficiary of the estate. The parties failed to agree on a purchase, and the court’s order directed the daughter and her family to vacate the residence so that the son could take possession as successor executor and sell the property. Randolph Estate, 3 Fid.Rep.4th 310 (Bucks O.C. 2025).
The Orphans’ Court has mandatory jurisdiction over a challenge to the validity of a beneficiary designation to a deferred compensation plan, and so a preliminary objection to the petition was dismissed. The petition alleged that the decedent changed the beneficiary designation on-line three months before his death, when the decedent was mentally handicapped from drug addiction, the elements of undue influence, fraud, lack of capacity, or mistake could be inferred from those allegations, and so the preliminary objection to the petition for failing to state a claim was also dismissed. DelVecchio Estate, 3 Fid.Rep.4th 283 (Philadelphia O.C. 2025).
One of the few good things about the Act of July 2, 2014, P.L. 855, No. 95, which made a number of significant changes to 20 Pa.C.S. Ch. 56 (“Powers of Attorney”), is that the act provided a list of…
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Chester County has published new fee schedules for the Register of Wills and Clerk of the Orphans’ Court, effective January 12, 2026. “Fees to be Charged by the Register of Wills and Clerk of the Orphans’ Court,” Administrative Order No. 3-2025 (Chester O.C., 1/9/2026), 56 Pa.B. 477 (1/24/2026).
The legislation proposed by the Pennsylvania Bar Association for electronic wills has now been introduced in the Pennsylvania legislature as SB 1138.
Future legislative actions on this bill will be reported on the “Pennsylvania Legislation Pending” directory, which lists and shows the current status of legislation which might be of interest to estate practitioners.
See “PBA Supports a Proposed Electronic Wills Act” and “Electronic Wills Co-Sponsorship Memo” for the background on the drafting and development of this legislation.
Although the trust instrument restricted distributions of principal, the trustee nevertheless had the power under a provision of the Uniform Principal and Income Act (“UPIA”), 20 Pa.C.S. § 8104, to allocate amounts of principal to income, and distribute that income to the beneficiary entitled to the income, in order to be fair and reasonable to the beneficiaries, and the allocations made by the trustee were not an abuse of discretion because the increases in the value of the principal were disproportionate to the trust’s production of income. The trust instrument did not forbid the adjustments made by the trust (and appeared to authorize them; see note below), and the UPIA applied to the trust even though it was created before the enactment of the UPIA because section 14 of the Act of May 15, 2002, No. 50, which enacted the UPIA, states that the act shall apply to trusts “existing on or after the effective date of this act.” In re: Hess Kline, Deceased, ___ A.4th ___, 2025 PA Super 295 (12/31/2025), aff’g, Kline Estate, 2 Fid.Rep.4th 339 (Montgomery O.C. 2024).
[DBE Note: This appears to be the first appellate court opinion in Pennsylvania affirming an adjustment to income and principal under § 8104, and it affirms that the statute means what most practitioners understood it to mean. However, the Superior Court concluded that the trust instrument (the decedent’s will) authorized the allocation of principal to income even without the UPIA, and I disagree with that conclusion. The sentence in question authorized the fiduciaries to claim items as either income tax or estate tax deductions, and “to make or not make adjustments or apportionments among the beneficiaries or as between principal and income.” I believe that the intent of the provision was to avoid the kind of mandatory “equitable adjustment” that might otherwise be required under decisions such as Matter of Warms, 140 N.Y.S.2d 169 (1955), and In Re Bell’s Estate, 7 Fid.Rep. 1 (Pa. O.C., 1956), when principal expenses are claimed as income tax deductions (or vice versa), and that there was no intent to create a new power of adjustment in other circumstances. The court held that the trustee had the power of adjustment under § 8104 regardless, and the counsel for the appellant might not have explained the Warms issue very well, so the court’s discussion of adjustments allowed by the will may hopefully be ignored by other courts in the future.]
The Orphans’ Court properly found that the alleged incapacitated person (“AIP”) was incapacitated and in need of guardianship services, notwithstanding the testimony of the AIP to the contrary, based on medical testimony that the AIP had impaired short-term memory, so that he lacked the ability to make medical, self-care, and financial decisions, as well as the court’s own observations of the AIP and his difficulty in recalling events and in responding to his own counsel’s questions. The evidence also supported the decision of the Orphans’ Court not to direct that the AIP be returned to his home under the care of a guardian as a less restrictive alternative. In re: Person and Estate of J.P.D., 987 EDA 2025 (Pa. Super. 12/30/2025) (non-precedential).
Many legal commentators and publications have noted that there are problems with relying on “generative artificial intelligence” or “large language models” such as “ChatGPT,” which are often referred to (somewhat derisively) as “chatbots.” The problems are usually described as “hallucinations” when a chatbot has been asked a legal question or is asked to draft of legal memo and provides a citation to a court opinion that simply does not exist. But there are other problems that are more subtle and more fundamental.
Chatbots simply manipulate words based on perceived patterns in documents that have been used to “train” them. They have no understanding of the meaning of words or any understanding of legal concepts. So even if you can train a chatbot to not fabricate citations to nonexistent court opinions, there is still no guarantee that it will accurately describe the real court opinions it cites.
This more subtle kind of error is described in Jarrus v. Governor of Michigan, No. 25-cv-11168 (USDC ED Mich. 12/2/2025). In an opinion and order on the possible imposition of sanctions for the use of Chat GPT, Judge F. Kay Behm provides three examples of citations that appeared in a pleading filed by a pro se litigant that were real citations to real court opinions but were cited for propositions that the opinions did not support. The court explained the problem as follows:
“[A]lthough Chat GPT generated ‘holdings’ that looked like they could plausibly have appeared in the cited cases, in fact it overstated their holdings to a significant degree. And while a litigant might get away with similar overstatements because they could, perhaps, reason their way to showing how a case’s stated holding might extend to novel situations, an LLM does not reason in the way a litigant must. To put it in a slightly different way, LLMs do not perform the metacognitive processes that are necessary to comply with Rule 11. LLMs are tools that “emulate the communicative function of language, not the separate and distinct cognitive process of thinking and reasoning.” Benjamin Riley, Large language mistake, The Verge https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intelligence-neuroscience-problems [https://perma.cc/7EHD-PLLZ]. When an LLM overstates a holding of a case, it is not because it made a mistake when logically working through how that case might represent a ‘nonfrivolous argument for extending, modifying, or reversing existing law or for establishing new law;’ it is just piecing together a plausible-looking sentence — one whose content may or may not be true.”
Legal publishers are putting together their own generative AI systems which are presumably designed to avoid the fictitious citation problem, but they cannot avoid the problem which is inherent to large language model technology, which is that the systems are not capable of doing any legal reasoning, but are only constructing “plausible-looking sentences” based on the documents that have been used to train them.
With better training methods, document drafting may be an effective use for AI technology (in the late 1980s, I co-authored a document drafting system that used what was then considered AI technology, but was not able to market it successfully), but at this time the use of generative AI for legal research or drafting legal briefs or memoranda should be considered only with an understanding of it’s considerable limitations.
As previously reported, the Pennsylvania Bar Association, acting on a joint report and recommendation of the Real Property Probate and Trust Law and Elder Law Sections, is now supporting the introduction and passage of legislation authorizing electronic wills and other estate-related documents in Pennsylvania.
A co-sponsorship memo from Lisa Baker, the Senator from District 20, has been circulating since 12/9/2025 asking for support from other Senators for the legislation (which has not yet been introduced).
[1/10/2026 Update: The electronic wills legislation endorsed by the PBA has now been introduced in the Pennsylvania legislature.]
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— Short Term Rates for 2025 —
| Month | Annual | Semiann. | Quarterly | Monthly |
|---|---|---|---|---|
| Jan. | 4.33% | 4.28% | 4.26% | 4.24% |
| Feb. | 4.34% | 4.29% | 4.27% | 4.25% |
| March | 4.31% | 4.26% | 4.24% | 4.22% |
| April | 4.16% | 4.12% | 4.10% | 4.09% |
| May | 4.05% | 4.01% | 3.99% | 3.98% |
| June | 4.00% | 3.96% | 3.94% | 3.93% |
| July | 4.12% | 4.08% | 4.06% | 4.05% |
| Aug. | 4.03% | 3.99% | 3.97% | 3.96% |
| Sept. | 4.00% | 3.96% | 3.94% | 3.93% |
| Oct. | 3.81% | 3.77% | 3.75% | 3.74% |
| Nov. | 3.69% | 3.66% | 3.64% | 3.63% |
| Dec. | 3.66% | 3.63% | 3.61% | 3.60% |
— Mid Term Rates for 2025 —
| Month | Annual | Semiann. | Quarterly | Monthly |
|---|---|---|---|---|
| Jan. | 4.24% | 4.20% | 4.18% | 4.16% |
| Feb. | 4.52% | 4.47% | 4.45% | 4.43% |
| March | 4.46% | 4.41% | 4.39% | 4.37% |
| April | 4.21% | 4.17% | 4.15% | 4.13% |
| May | 4.10% | 4.06% | 4.04% | 4.03% |
| June | 4.07% | 4.03% | 4.01% | 4.00% |
| July | 4.19% | 4.15% | 4.13% | 4.11% |
| Aug. | 4.06% | 4.02% | 4.00% | 3.99% |
| Sept. | 4.04% | 4.00% | 3.98% | 3.97% |
| Oct. | 3.87% | 3.83% | 3.81% | 3.80% |
| Nov. | 3.83% | 3.79% | 3.77% | 3.76% |
| Dec. | 3.79% | 3.75% | 3.73% | 3.72% |
— Long Term Rates for 2025 —
| Month | Annual | Semiann. | Quarterly | Monthly |
|---|---|---|---|---|
| Jan. | 4.53% | 4.48% | 4.46% | 4.44% |
| Feb. | 4.86% | 4.80% | 4.77% | 4.75% |
| March | 4.82% | 4.76% | 4.73% | 4.71% |
| April | 4.61% | 4.56% | 4.53% | 4.52% |
| May | 4.62% | 4.57% | 4.54% | 4.53% |
| June | 4.77% | 4.71% | 4.68% | 4.66% |
| July | 4.90% | 4.84% | 4.81% | 4.79% |
| Aug. | 4.82% | 4.76% | 4.73% | 4.71% |
| Sept. | 4.83% | 4.77% | 4.74% | 4.72% |
| Oct. | 4.73% | 4.68% | 4.65% | 4.64% |
| Nov. | 4.62% | 4.57% | 4.54% | 4.53% |
| Dec. | 4.55% | 4.50% | 4.47% | 4.46% |