HHS Is Using AI Tools From Palantir to Target'DEI' and'Gender Ideology' in Grants Since March of 2025, the Trump Administration has used tools from Palantir and the startup Credal AI to weed out "DEI" and "gender ideology from child welfare programs. A view of the Palantir building is seen during the World Economic Forum Annual Meeting 2026 in Davos, Switzerland. Since last March, the Department of Health and Human Services has been using AI tools from Palantir to screen and audit grants, grant applications, and job descriptions for noncompliance with President Donald Trump's executive orders targeting "gender ideology" and anything related to diversity, equity, inclusion (DEI), according to a recently published inventory of all use cases HHS had for AI in 2025. Neither Palantir nor HHS has publicly announced that the company's software was being used for these purposes. During the first year of Trump's second term, Palantir earned more than $35 million in payments and obligations ...

In science, promotional language ('hype') is increasing and can undermine objective evaluation of evidence, impede research development, and erode trust in science. In this paper, we introduce the task of automatic detection of hype, which we define as hyperbolic or subjective language that authors use to glamorize, promote, embellish, or exaggerate aspects of their research. We propose formalized guidelines for identifying hype language and apply them to annotate a portion of the National Institutes of Health (NIH) grant application corpus. We then evaluate traditional text classifiers and language models on this task, comparing their performance with a human baseline. Our experiments show that formalizing annotation guidelines can help humans reliably annotate candidate hype adjectives and that using our annotated dataset to train machine learning models yields promising results. Our findings highlight the linguistic complexity of the task, and the potential need for domain knowledge and temporal awareness of the facts. While some linguistic works address hype detection, to the best of our knowledge, we are the first to approach it as a natural language processing task.

How are the merits of innovative ideas communicated in science? Here we conduct semantic analyses of grant application success with a focus on scientific promotional language, which has been growing in frequency in many contexts and purportedly may convey an innovative idea's originality and significance. Our analysis attempts to surmount limitations of prior studies by examining the full text of tens of thousands of both funded and unfunded grants from three leading public and private funding agencies: the NIH, the NSF, and the Novo Nordisk Foundation, one of the world's largest private science foundations. We find a robust association between promotional language and the support and adoption of innovative ideas by funders and other scientists. First, the percentage of promotional language in a grant proposal is associated with up to a doubling of the grant's probability of being funded. Second, a grant's promotional language reflects its intrinsic level of innovativeness. Third, the percentage of promotional language predicts the expected citation and productivity impact of publications that are supported by funded grants. Lastly, a computer-assisted experiment that manipulates the promotional language in our data demonstrates how promotional language can communicate the merit of ideas through cognitive activation. With the incidence of promotional language in science steeply rising, and the pivotal role of grants in converting promising and aspirational ideas into solutions, our analysis provides empirical evidence that promotional language is associated with effectively communicating the merits of innovative scientific ideas.

Many of us have already been trying ChatGPT. If you've checked science social media recently, it's likely that you've already seen many of its writings. In common with many other researchers, I worry about artificial intelligence (AI) replacing me. I'm a vaccine researcher and spend much of my time writing grant applications, papers and articles about science careers, so I set the chatbot the task of writing an opinion piece about the use of AI in grant writing. In my opinion, ChatGPT has the potential to revolutionize the process of writing scientific grants.

Data mining techniques can transform massive amounts of unstructured data into quantitative data that quickly reveal insights, trends, and patterns behind the original data. In this paper, a data mining model is applied to analyse the 2019 grant applications submitted to an Australian Government research funding agency to investigate whether grant schemes successfully identifies innovative project proposals, as intended. The grant applications are peer-reviewed research proposals that include specific ``innovation and creativity'' (IC) scores assigned by reviewers. In addition to predicting the IC score for each research proposal, we are particularly interested in understanding the vocabulary of innovative proposals. In order to solve this problem, various data mining models and feature encoding algorithms are studied and explored. As a result, we propose a model with the best performance, a Random Forest (RF) classifier over documents encoded with features denoting the presence or absence of unigrams. In specific, the unigram terms are encoded by a modified Term Frequency - Inverse Document Frequency (TF-IDF) algorithm, which only implements the IDF part of TF-IDF. Besides the proposed model, this paper also presents a rigorous experimental pipeline for analysing grant applications, and the experimental results prove its feasibility.

A team at Flinders University in South Australia has developed a new vaccine believed to be the first human drug in the world to be completely designed by artificial intelligence (AI). While drugs have been designed using computers before, this vaccine went one step further being independently created by an AI program called SAM (Search Algorithm for Ligands). Flinders University Professor Nikolai Petrovsky who led the development told Business Insider Australia its name is derived from what it was tasked to do: search the universe for all conceivable compounds to find a good human drug (also called a ligand). "We had to teach the AI program on a set of compounds that are known to activate the human immune system, and a set of compounds that don't work. The job of the AI was then to work out for itself what distinguished a drug that worked from one that doesn't," Petrovsky said, who is also the Research Director of Australian biotechnology company Vaxine.

Steve Marshall is directing the city of Bellevue's efforts to bring a fleet of self-driving vanpools to the region. If it is successful, it could shuttle up to 3,000 commuters along the I-405 corridor from Auburn to Kirkland. Aaron Kunkler/Staff photo As the technology powering self-driving vehicles continues to advance, the cities of Bellevue and Kirkland have a plan to bring a fleet of vans to the Eastside. The CommutePool program was drafted by staff from the two cities, which submitted a grant application to the U.S. Department of Transportation last week asking for $3 million to help fund the $9 million project. Bellevue Transportation Technology Partnership Manager Steve Marshall has been working with large employers in the area to gather support for the electric, self-driving vanpools.