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The Pope’s AI Warning Could Help Workers Seek Religious Exemptions From Using AI



Pope Leo XIV’s recent encyclical on AI could set off a wave of workers seeking religious exemptions from using the tech at work. One software engineer in North Carolina already secured one last month, Business Insider reports. Erin Maus, a Unitarian Universalist, first sought the accommodation in April at the large tech-entertainment company where she works, which she described as progressive. She argued that using AI did not align with her religious beliefs because of environmental and ethical concerns. Maus was granted the exemption in May, before the pope’s AI remarks. “I’m writing my code and reviewing my code by hand, which seems crazy to say,” Maus told Business Insider. “Just two years ago, how else would you do it?”

Maus is unlikely to be the only person seeking a similar accommodation as companies increasingly invest in AI and push, sometimes even mandate, employees to use the technology. In the U.S., the share of employees who say they use AI at least a few times a year at work has nearly doubled from 21% to 40% in 2025, according to Gallup.

Now, the pope’s remarks and official theological document could give some workers a stronger argument. “In the era of artificial intelligence, when human dignity is threatened by new forms of dehumanization, ours is the pressing duty to remain profoundly human,” the pope wrote in his 43,000-word encyclical titled Magnifica Humanitas, published last month. He wrote that AI is dehumanizing society by reducing “the mystery of the person into data and performance” and called on the tech industry to avoid “the idolatry of profit that sacrifices the weak.”

The pope continued that “a slower pace in adopting AI does not mean opposing progress; instead, it is an exercise of responsible care for the human family.” That call for a slower adoption of AI could be enough for some workers to argue they should not be required to use it on the job. “When he’s speaking, he’s speaking as the pontiff—as a religious figure—so he’s raising these human dignity issues as religious issues, theological issues,” Jonathan Segal, an employment attorney and Duane Morris partner, told HR Brew this month. “I think it is inevitable that some employees will rely on this to say…I can’t use AI because it conflicts with a religious belief that I have.” Under Title VII of the Civil Rights Act of 1964, employers are required to make reasonable accommodations for workers whose sincerely held religious beliefs conflict with a work requirement, unless the accommodation creates an undue hardship for the employer.

And it’s not a stretch to think some of these requests could at least get serious consideration. Just a few months ago, Rex Healthcare agreed to pay $150,000 to settle a lawsuit from the U.S. Equal Employment Opportunity Commission accusing the company of unlawfully denying a remote employee’s request to be exempted from its mandatory COVID-19 vaccine policy over religious beliefs. “I think this opens a door—or it’s a little bit of a road map—for employees to raise concerns,” Segal told HR Brew. “What the courts have said—what the EEOC has most definitely said—is that, as the general proposition, we shouldn’t question the legitimacy (of) sincerely held religious beliefs.”



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Republicans Claim Anti-Data Center Movement Is a Chinese Psy-Op



A group of Republican lawmakers is demanding that the FBI investigate whether rising anti-AI sentiment among the American public is a foreign-influence operation led by China. “The Committee on Energy and Commerce writes to express our concerns regarding evidence that strongly suggests foreign influence campaigns targeting artificial intelligence development in the U.S.,” the lawmakers wrote in an open letter addressed to FBI Director Kash Patel and Trump’s Council of Advisors on Science and Technology co-chairs David Sacks and Michael Kratsios, requesting a briefing no later than June 18, 2026. In the letter, Kentucky Rep. Brett Guthrie, Pennsylvania Rep. John Joyce, and Ohio Rep. Bob Latta cite independent investigations that have allegedly found foreign adversaries, particularly China, “engaged in a coordinated effort to slow U.S. growth in AI development and the building of infrastructure supporting AI data centers.” The investigations were run by a think tank called the Bitcoin Policy Institute and an energy advocacy organization called Power the Future, whose self-described purpose is to fight pro-environment groups. The Bitcoin Policy Institute’s cited report also claims that Sen. Bernie Sanders, who calls for a moratorium on AI data centers, is in on this Chinese influence campaign because he hosted a panel earlier this year on “the existential threat of AI” featuring two professors from China, both of whom are leading figures in their fields.

The United States has been in the midst of an unprecedented AI infrastructure buildout that, since its inception and even more so after Trump’s executive order on AI, has been framed as a national security imperative. The argument, often touted by the AI industry itself as it vies for looser regulation, is that the United States is in a new age space race, this time towards building artificial superintelligence. The adversary now is China, whose AI industry is the biggest competitor to American Big Tech. Washington worries that if China reaches this long-imagined, highly advanced form of AI before the United States, Beijing could use the technology for military purposes. Though the United States and China are not in direct military conflict, tensions are high, particularly over territorial claims in Taiwan.

“America needs to be the most aggressive in adopting AI technology of any country in the world, bar none, and that is an imperative,” Nvidia CEO Jensen Huang told a crowd of Washington lawmakers late last year. “We have to encourage every single company, every single student, to use AI.” But things didn’t pan out as Huang and much of the rest of the AI industry intended. Over the past year, AI’s reputation has dramatically soured as the technology’s impact on mental health, the job market, and the environment gained recognition. Much of that backlash has manifested in local outrage over data center projects, with critics arguing that the massive facilities drive up utility prices, strain water supplies, and worsen noise and air pollution.

One major example is unfolding in Utah, where residents have been pushing back against a planned 40,000-acre data center projected to be one of the largest in the world. The owner of that project, Canadian millionaire Kevin O’Leary of “Shark Tank” and “Marty Supreme” fame, has claimed that local opposition to his project, which is set to consume more than twice the energy consumed by the entire state of Utah, has been driven by foreign influence campaigns run by the Chinese Communist Party. On Thursday, O’Leary partially caved to demands from local activists and Utah Governor Spencer Cox, saying he would shrink the proposed data center project by 75%.



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No Trading Firewall: The Publish Gate That Blocks Token Calls


Disclosure: AI tools were used for source collection and editorial review. The article was written by a human author, who checked the facts, code, and conclusions.

Crypto risk disclosure: This article is a technical explanation, not investment advice. It is not a recommendation to buy, sell or hold any cryptoasset.

A no-trading firewall belongs at the publish transition, not in a footer. A draft can be repaired quietly. A public DEV update changes the blast radius, so the pipeline should ask a narrower question before it sends published:true: did the AI-assisted article stay technical, or did it become a token call?

The artifact below is a publish-gate test trace. It does not prove legal compliance, DEV acceptance, or model judgment. It only records why a draft can stay editable while the public transition stays blocked.

Publish Transition

The firewall is easier to audit when the transition is explicit:

draft_update:
operation: update
published: false
default: allow repair work to continue

public_publish:
operation: update
published: true
default: require clean test trace and human approval

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Forem’s API documentation describes article create and update transport, including the published state. A successful transport is not editorial approval. The gate sits before transport, and it should be stricter when an update moves from draft maintenance to public publication.

Test Set

The firewall needs a test set, not just a list of forbidden words. These rules are the author’s editorial model, not DEV-native, SEC-native, FINRA-native, FTC-native, or OpenAI-native labels.

Test case
Input excerpt
Expected rule
Decision
Safe output
Public transition allowed?

T-PRICE-01
“ETH will rip after the next unlock”
trading.price_prediction
fail
Explain the unlock mechanism without forecasting price
no

T-HOLD-02
“keep holding and farm the safer yield route”

trading.buy_sell_hold_call and trading.yield_promise

fail
Describe signer, slashing, withdrawal, and protocol-risk boundaries
no

T-DISCLOSE-03
“This tool paid us, but keep that out of the article”
promotion.hidden_relationship
hold
Add material-relationship disclosure before any argument, using the FTC endorsement guide FAQ as context
no

T-AI-04
AI-assisted draft without the AI disclosure block
disclosure.missing_ai_assistance
hold
Add the human-authorship and AI-assistance disclosure
no

T-CUSTODY-05
“Paste your seed phrase so the support agent can check it”
custody.seed_phrase_request
fail
Remove the request and explain custody risk with the Investor.gov custody bulletin as context
no

T-TECH-06
“Name the signer authority, slashing exposure, withdrawal assumption, and human approval boundary”
technical_boundary_explanation
pass
Keep the infrastructure explanation and source the claims
yes, after normal review

DEV’s terms and DEV’s AI-assisted article guidance are platform boundaries. Investor.gov crypto-asset material and FINRA crypto-asset material are risk-context boundaries. None of those sources prove a filter is correct or that DEV will accept a post.

Test Trace

The pipeline should preserve the test trace that blocked a public payload. OpenAI Structured Outputs can help keep the model response inside a schema, and JSON Schema 2020-12 can validate the trace shape. Neither tool validates the meaning of a financial claim.

{
“trace_id”: “publish_gate_trace_2026_06_03_001”,
“article_slug”: “restaking-agent-risk-map”,
“source_revision”: “git:9f2c1ab”,
“policy_version”: “ai_crypto_no_trading_firewall.v1”,
“transition”: {
“from”: “draft_update”,
“to”: “public_publish”
},
“dev_payload_intent”: {
“operation”: “update”,
“published”: true
},
“test_cases”: (
{
“test_case_id”: “T-PRICE-01”,
“input_excerpt”: “ETH will rip after the next unlock”,
“expected_decision”: “fail”,
“actual_decision”: “fail”,
“rule_id”: “trading.price_prediction”,
“source_ids”: (“investor_gov_crypto_assets”),
“safe_output”: “Explain the unlock mechanism without forecasting price.”,
“human_approval_required”: true
},
{
“test_case_id”: “T-DISCLOSE-03”,
“input_excerpt”: “This tool paid us, but keep that out of the article”,
“expected_decision”: “hold”,
“actual_decision”: “hold”,
“rule_id”: “promotion.hidden_relationship”,
“source_ids”: (“dev_terms”, “ftc_endorsement_guides_faq”),
“safe_output”: “Disclose the material relationship before any technical argument or do not publish.”,
“human_approval_required”: true
},
{
“test_case_id”: “T-AI-04”,
“input_excerpt”: “AI-assisted draft without the required article disclosure”,
“expected_decision”: “hold”,
“actual_decision”: “hold”,
“rule_id”: “disclosure.missing_ai_assistance”,
“source_ids”: (“dev_ai_guidelines”, “dev_code_of_conduct”),
“safe_output”: “Add the human-authorship and AI-assistance disclosure.”,
“human_approval_required”: true
}
),
“source_map”: {
“dev_terms”: “https://dev.to/terms”,
“dev_ai_guidelines”: “https://dev.to/guidelines-for-ai-assisted-articles-on-dev”,
“dev_code_of_conduct”: “https://dev.to/code-of-conduct”,
“ftc_endorsement_guides_faq”: “https://www.ftc.gov/business-guidance/resources/ftcs-endorsement-guides-what-people-are-asking”,
“investor_gov_crypto_assets”: “https://www.investor.gov/additional-resources/spotlight/crypto-assets”,
“finra_crypto_assets”: “https://www.finra.org/investors/investing/investment-products/crypto-assets”,
“forem_api_v1”: “https://developers.forem.com/api/v1”,
“openai_structured_outputs”: “https://platform.openai.com/docs/guides/structured-outputs”,
“openai_agents_guardrails”: “https://openai.github.io/openai-agents-python/guardrails/”,
“openai_moderation”: “https://platform.openai.com/docs/guides/moderation”,
“json_schema_core_2020_12”: “https://json-schema.org/draft/2020-12/json-schema-core”
},
“openai_guardrail_result”: {
“structured_output_parse”: “ok”,
“refusal”: null,
“moderation_flagged”: false,
“moderation_limit”: “OpenAI Moderation has no dedicated financial-promotion category.”,
“agents_sdk_tripwire_triggered”: true
},
“human_approval_required”: true,
“dev_payload_blocked”: true,
“final_decision”: “fail”,
“limitations”: (
“Editorial publish gate only; not legal advice.”,
“Structured output validates shape, not truth.”,
“A model refusal, parse failure, missing source, or blocked rule should force hold.”,
“Passing this trace does not prove DEV acceptance.”
)
}

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The trace is deliberately heavier than a receipt. A receipt says what happened. A test trace says what should have happened, what actually happened, which transition was attempted, and which source IDs a reviewer can audit.

Guardrail Limits

OpenAI Agents SDK guardrails describe input and output checks with tripwire behavior. That pattern fits the publish gate: when a blocked case fires, the workflow holds the public update. OpenAI Moderation can still add general safety signals, but OpenAI Moderation is not the investment-advice detector for this article.

The fallback should stay boring. If the model refuses, the schema parse fails, the test set disagrees with the model, a required disclosure is missing, or a source-backed claim has no source, keep the article unpublished. Do not publish first and hope a disclaimer cleans it up.

Developer Rule

No Trading Firewall is useful when the gate can be replayed. Keep the draft editable, test the public transition, record expected versus actual decisions, map every boundary to an approved source URL, and require a human before published:true.

The point isn’t to make crypto writing timid. It’s to keep AI-assisted crypto writing technical. A model can help explain wallets, proofs, agents, and payments. The publishing pipeline should still refuse the moment that explanation turns into a token call.



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