For decades, the possibility of discovering extraterrestrial intelligence has captured the imagination of scientists, sci-fi enthusiasts, filmmakers, and the public alike.
In line with such efforts, the IAA SETI Committee and the uNHIdden Foundation, two separate not-for-profit organizations, have recently released updated rules for evaluating and disclosing detections, and preparing for public preparedness in the event of potential disclosure of extraterrestrial intelligence.
With the release of director Steven Spielberg’s new alien film Disclosure Day, nearly coinciding with the recent release of the government records from the Department of War related to UAP, it seems a growing number of individuals, from the film industry to the science community, have extraterrestrials and “disclosure” on their minds.
In June 2026, the International Academy of Astronautics (IAA) approved a major update to the protocols governing the evaluation, verification, and communication of evidence related to extraterrestrial intelligence. The revised guidelines were designed to address a modern information environment shaped by social media, artificial intelligence, and the rapid pace of the 24-hour news cycle.
Professor Michael Garrett, Sir Bernard Lovell Chair of Astrophysics, led the international effort to revise the long-standing post-detection protocols used by researchers engaged in the search for extraterrestrial intelligence. The updated guidelines have since been formally ratified by the IAA.
“The information environment we operate in today is vastly more complex than it was in 2010,” said Garrett, Chair of the IAA SETI Committee, in a statement. “In an era of deepfakes, automated misinformation, and instant global connectivity, a single unverified claim could trigger confusion or panic. These new protocols ensure that scientists maintain the highest standards of evidence before making announcements to the world.”
The revised declaration reflects the broader scope of modern SETI and technosignature research. Since the previous guidelines were adopted in 2010, advances in technology have enabled scientists to investigate the entire electromagnetic spectrum, including excess infrared heat signatures that could indicate megastructures, optical laser emissions, and even multi-messenger signals.
The updated framework also addresses modern challenges, including protections for researchers who may face harassment, doxxing, or intense media scrutiny. It further emphasizes the importance of distinguishing verified scientific data from viral rumors, hoaxes, or terrestrial interference.
At the heart of the new guidelines is a familiar scientific principle: extraordinary claims require extraordinary evidence.
Under the revised protocols, no public announcement should be made until a signal or artifact has been rigorously verified by independent organizations using different instruments and methodologies.
“We do not shout ‘alien’ the moment we see a strange blip,” said Garret in a statement. “The scientific method demands we check, check again, and then ask others to check. Only when we have reached a consensus that a signal is credible do we bring it to the world.”
While the protocols explain how to share discovery news, they make one rule clear: no reply should be sent.
“The threshold for ‘extraordinary evidence’ is subjective,” Siemion says. “Because of the vast diversity of modalities in which a technosignature might manifest, it is impossible to state explicitly the criteria that would meet this threshold under all circumstances.”
“In the case of a coherent electromagnetic signal, like a narrowband carrier or a series of laser pulses, an example of ‘extraordinary’ would be if we repeatedly detected the signal at the same location with multiple independent observatories,” Siemion adds.
He also noted that, for a transient signal, compelling evidence might include multiple lines of data indicating that it traveled through interstellar space. Determining whether a phenomenon truly originated from extraterrestrial technology would likely be a lengthy process, with evidence presented, challenged, and reassessed over time.
The declaration reinforces that any response to extraterrestrial intelligence would be a decision for all humanity and should only occur following international consultation, particularly through the United Nations.
With the updated declaration now ratified by the IAA Board, it will be shared with stakeholders, including the United Nations. A formal presentation of the protocols is scheduled for the International Astronautical Congress (IAC) in Türkiye later this year.
“The release of these updated rules and protocols marks an important step in acknowledging both the radically different media landscape that science functions within today, and the vastly expanded efforts in terms of technology and resources being deployed in the search for intelligent life beyond Earth,” said Bill Diamond, President and CEO of the SETI Institute and IAA SETI Committee member. “We applaud Prof Garrett’s leadership in developing these new protocols and the IAA for their ratification.”
Another nonprofit organization has taken a different approach, focusing on the potential psychological and public-health implications of disclosure. The uNHIdden Foundation, whose mission is to support mental health related to Unidentified Anomalous Phenomena (UAP), recently released a preparedness framework addressing the societal impact of a paradigm-shifting discovery.
If governments prepare for natural disasters, pandemics, and other low-probability, high-impact events, should humanity also consider preparing for the possibility of contact with another intelligent civilization?
On June 8, uNHIdden Foundation Founder and Chairman John Priestland, alongside clinical spokesperson Dr. Martin Abbas, launched what they describe as the first public-health preparedness framework focused on disclosure-related scenarios.
Developed by healthcare practitioners, physicians, clinical psychologists, and public-health specialists, “Preparing for Disclosure: A Public Health Framework for Paradigm-Shifting Revelations” examines how society might reduce harm, build resilience, and support individuals processing a profound shift in humanity’s understanding of its place in the universe.
“This report is not a prediction. It is a preparedness exercise,” Priestland says. “Governments prepare for all kinds of low-probability, high-impact events.”
“Our view is that if a paradigm-shifting disclosure were ever to occur, we should at least have thought about the human consequences in advance,” Priestland added.
The report suggests that certain groups could be more vulnerable to disclosure-related distress, including individuals with pre-existing mental health conditions, those facing socioeconomic hardship, UAP experiencers, highly religious individuals, and some STEM professionals. The authors emphasize that the report neither predicts disclosure nor attempts to judge future discoveries; rather, it argues that preparedness is a prudent response to the possibility of transformative new information.
David Whitehouse, former BBC Science Correspondent, wrote the report’s foreword, arguing that planning is essential should such a discovery ever occur.
The new framework proposes several practical actions to be taken, which include:
The report argues that stronger community resilience, clearer communication during periods of uncertainty, and improved mental-health support would be critical not only during a disclosure event but during any large-scale societal disruption.
Ultimately, the question remains whether humanity is truly prepared—or whether a globally coordinated framework is still lacking. Voices ranging from the UAP community to figures within the U.S. government have argued that the public is ready. However, only time will tell what the result may be if confirmation of extraterrestrial intelligence were to arrive—and how humanity will collectively respond to the discovery.
Chrissy Newton is a PR professional and the founder of VOCAB Communications. She currently appears on The Discovery Channel and Max and hosts the Rebelliously Curious podcast, which can be found on YouTube and on all audio podcast streaming platforms. Follow her on X: @ChrissyNewton, Instagram: @BeingChrissyNewton, and chrissynewton.com. To contact Chrissy with a story, please email chrissy @ thedebrief.org.
A groundbreaking AI-designed vaccine aims to protect against not only today’s coronaviruses, but tomorrow’s as well. A new type of universal coronavirus vaccine has passed its first test in humans, marking an important step toward broader protection against future viral threats. Researchers from the University of Cambridge and biotechnology company DIOSynVax (DVX) Ltd reported that [...]Microsoft has open-sourced an AI evaluation framework that converts natural-language requirements into executable tests, expanding its push into enterprise AI governance as organizations struggle to validate agent behavior before production deployments systematically.
The framework, called ASSERT (Adaptive Spec-driven Scoring for Evaluation and Regression Testing), generates evaluation scenarios, datasets, metrics, and scorecards from written specifications, product requirements, and governance documents, Microsoft said in a blog post announcing the release.
“Agents fail in ways that are hard to see,” Microsoft wrote in the blog post. “They drift from policy, produce unsafe outputs in edge cases, and behave differently in production than they did in testing. Generic benchmarks do not catch these failures because they are not built around your policies, your agent, or your use case.”
Rather than requiring developers to manually create evaluation suites, ASSERT translates written intent into reusable tests that can be integrated into AI development pipelines, the company said in the blog post.
With ASSERT, Microsoft is entering an increasingly competitive AI evaluation market that already includes platforms such as LangChain’s LangSmith, Braintrust, Patronus AI, Galileo, Arize AI’s Phoenix, and Promptfoo, which help enterprises benchmark, monitor, and validate large language model applications.
The release comes as enterprises rapidly expand AI agent deployments while formal evaluation practices remain the exception rather than the rule.
“Most organizations, in fact, 99% of them, do not evaluate any AI agents pre-production,” said Anushree Verma, senior director analyst at Gartner.
According to Verma, the industry’s next competitive advantage will depend less on advances in reasoning models than on how effectively organizations simulate and stress-test AI agents before deployment.
“The next competitive moat in agentic AI is not about the sophistication of reasoning models or the underlying architecture,” she said. “It will be about the depth and realism of the training environment through agentic simulation, particularly for mission-critical deployments.”
Gartner estimates that by 2029, more than 75% of domain-specific agents designed without agentic simulation in regulated industries will fail to deliver value.
Forrester sees enterprises moving toward behavioral evaluation but says most organizations have yet to make it a formal production requirement.
“Most enterprises are still in an intermediate stage where behavioral evaluation is inconsistently applied rather than treated as a formal production gate,” said Biswajeet Mahapatra, principal analyst at Forrester.
According to Forrester data, more than 45% of organizations are already using AI agents, and another 25% are piloting them, yet many continue to struggle with scaling because of immature governance and limited operational rigor.
“The net is that behavioral evaluation is becoming important, but for most organizations it is still ad hoc or tool-driven rather than a standardized release gate enforced across the lifecycle,” Mahapatra said.
Microsoft said ASSERT uses large language models as judges, with model-generated evaluations agreeing with human reviewers 80% to 90% of the time in the company’s internal validation.
That level of agreement can help automate large portions of AI testing, but should not be treated as a standalone governance mechanism, Mahapatra said.
“An 80% to 90% agreement rate with human reviewers indicates strong alignment but is not sufficient as a standalone control for governance or compliance,” he said.
Instead, enterprises should adopt layered oversight where AI evaluates AI at scale while humans retain supervisory accountability for high-risk, regulated, or ambiguous scenarios. Buyers should also watch for bias, consistency issues, and overreliance on a single model acting as both generator and evaluator, he added.
Microsoft released ASSERT under the MIT open-source license, allowing organizations to inspect, modify, and integrate the framework into existing AI development workflows.
But open sourcing a framework does not eliminate questions around evaluation neutrality, Mahapatra said.
“Open sourcing under an MIT license reduces lock-in concerns and enables broad interoperability across model ecosystems,” he said. “However, it does not fully eliminate trust or conflict-of-interest questions because the originating vendor still influences how evaluation criteria, scoring logic, and definitions of acceptable behaviour are encoded.”
Instead of relying on a single evaluation framework, enterprises should validate AI systems against multiple evaluation approaches and retain ownership of internal evaluation policies, he said.
Databricks on Wednesday unveiled OpenSharing, a new open protocol designed to let enterprises share AI models, agent skills, dashboards, and unstructured data across platforms without having to copy or move those assets.
That sharing is made possible by OpenSharing’s zero-copy credential vending model that allows recipients to securely access shared assets directly from a provider’s cloud storage using temporary, scoped credentials rather than requiring the assets themselves to be copied, moved, or replicated, the company wrote on its GitHub page.
The ability to share AI assets without creating duplicate copies could help reduce integration complexity, improve governance, and limit the operational overhead associated with operationalizing AI systems across environments for CIOs, said Ashish Chaturvedi, leader of executive research at HFS Research.
“Every organization building AI, such as multi-agentic systems, is hitting the same wall, i.e., the model, the skill, and the consumer reside on three different platforms. The integration tax is enormous, and it grows exponentially with every new partner, customer, or internal team,” Chaturvedi said.
Echoing Chaturvedi, The Futurum Group’s lead of the CIO practice, Dion Hinchcliffe, pointed out that the reduction in operational overhead could help CIOs cut down on the hidden costs of integration around AI deployments: “Today, hidden costs include more than just model development. It is the endless packaging, translation, sync, and governance effort required to operationalize AI assets across organizational boundaries.”
That cost reduction is becoming even more important because enterprises are beginning to treat AI assets as business assets that need to be shared, said Stephanie Walter, practice lead of the AI stack at HyperFRAME Research.
“Enterprises are quickly realizing that the value is no longer just in the dataset. It is in the governed context, logic, and intelligence built around the dataset. Existing approaches can share datasets well, but they often do not address the broader AI package,” Walter said.
“OpenSharing is directionally aligned with that shift because it extends the sharing model beyond tables and files toward the artifacts that power AI workflows,” Walter added.
For Hinchcliffe, that alignment should work in CIOs’ favor, trying to operationalize AI across their systems: “CIOs increasingly want AI supply chains, not isolated data lakes like before.”
Additionally, Chaturvedi pointed out that the new protocol can help CIOs accelerate the monetization of AI investments.
“For CIOs, the speed at which you can share AI assets across partners, subsidiaries, and customers determines the speed at which you can monetize your AI investments. If sharing an agent skill takes six weeks of integration work, you’ve lost the window. If it takes a protocol call, you’ve turned AI into a distribution business,” he said.
Achieving those benefits, however, will require developers to move AI assets across disparate platforms more efficiently, and analysts pointed out that OpenSharing’s ability to reduce integration complexity could significantly improve productivity.
“Developer productivity depends on reducing platform translation work. Developers do not want to rebuild the same asset for every consuming environment, and enterprises do not want every partner or customer interaction to become a platform migration conversation,” Walter said.
In fact, Chaturvedi sees the new protocol as unique in the industry, in the specific sense that “no other open protocol covers agent skills and AI models as shareable, governed objects”.
Walter, in contrast, sees the openness of the protocol as novel: “What is more interesting is the combination: an open protocol, cross-platform interoperability, Linux Foundation governance, and a broader asset model that extends beyond datasets into AI models, agent skills, dashboards, applications, and unstructured data.”
“The novelty is not that Databricks invented sharing, zero-copy access, or marketplace-style distribution. Those capabilities already exist in various forms across the market,” Walter said, pointing towards Snowflake’s offerings, such as the Zero-Copy integrations.
The difference, though, the analyst noted, is that Snowflake allows data to be copied only if both provider and receiver are on Snowflake.
With Databricks’ OpenSharing, data can be copied across platforms, Walter added.
OpenSharing, which is an evolution of Databricks’ existing Delta Sharing protocol, is currently a sandbox project under the Linux Foundation AI & Data Foundation and is available via GitHub.
Its current list of generally available connectors includes Python, Apache Spark, Tableau, PowerBI, Snowflake, DuckDB, Clojure, Node.js, Java, Arcurate, Rust, Go, C++, and R.
Other connectors that are expected to be made generally available soon include Google Spreadsheet, Excel, Airflow, and Lakehouse Sharing.
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