Loading…
Explore the challenges of authenticity and trust in AI for 2025, including deepfakes and AI-written content.
A recent Reddit thread captures a growing unease with generative AI. The poster worries about priests using ChatGPT to draft sermons and about hyper‑realistic AI images and videos eroding trust in anything we see online.
“Imagine going to a church and you’re basically worshipping to the words of an AI.”
The concern is understandable. Two trends are converging: AI‑written text in places where authenticity matters, and synthetic media (deepfakes) that can convincingly imitate reality. Both challenge how we judge credibility, intent and authorship.
For a UK audience, this isn’t abstract. Our institutions – churches, schools, councils, newsrooms – rely on trust, and our information environment is already strained by misinformation. The question is not whether AI is used, but how it’s used, disclosed and governed.
Clergy, teachers, civil servants and journalists are all experimenting with AI tools as drafting aids. The ethical issues are similar across these roles: stewardship of authority, respect for audiences and accurate attribution.
When a person speaks from a position of trust, we expect them to be the author. If AI contributed materially – for structure, arguments or full paragraphs – disclose it. A simple note such as “Drafted with AI assistance; reviewed and edited by [Name]” preserves honesty without banning useful tools.
AI can help brainstorm or de‑jargonise, but it cannot know the context, congregants or pastoral needs. Final responsibility should remain with the human. That means verifying facts, checking tone, and ensuring the message reflects lived experience rather than generic text.
Generative models can “hallucinate” – produce fluent but incorrect statements. They also reflect biases in their training data. For any public‑facing content (sermons, lectures, briefings), fact‑checking and sensitivity review are non‑negotiable.
“Deepfakes” are AI‑generated or heavily edited images, audio or video made to look authentic. Advances in model quality and the scale of online data mean synthetics are cheaper, faster and more believable.
Automated detectors can help, but there’s no perfect tool. As generation improves, detection models play catch‑up. That arms race favours attackers over time.
Instead of hunting for visual glitches, look for provenance – who captured it, when, and with what device – and corroboration from trusted sources. The C2PA standard adds cryptographic “content credentials” at creation to show edit history. You can inspect these using the official verifier where available.
The UK’s approach to AI governance is regulator‑led rather than one big AI law. Several bodies already have relevant powers.
Internationally, the EU AI Act includes a disclosure duty for deepfakes; many UK organisations will align to that standard to operate across borders. Meanwhile, industry‑backed provenance via C2PA is gaining traction in cameras, newsrooms and creative tools.
Outright bans rarely work. Practical, transparent norms are better. For teams and institutions, consider adopting these rules:
One easy win is to log prompts and outputs for anything you publish. It helps with accountability and training. If you already live in spreadsheets, you can wire AI outputs into Google Sheets and keep a record for audit. Here’s a practical guide: Connect ChatGPT and Google Sheets (Custom GPT).
Trust is a public good. Whether you’re a priest, a press officer, a developer or a content creator, your audience will increasingly ask two questions: did a human stand behind this, and can I verify it? Meeting that expectation doesn’t mean rejecting AI; it means documenting and disclosing how you used it, and building provenance into your workflow.
“It just feels like AI is being used for all the wrong reasons at the moment.”
It can be used for the right ones too – making complex topics understandable, speeding up research, and improving accessibility. The line is simple: when authenticity matters, be transparent; when evidence matters, show it.
Related
Software engineers and AI: more output, not more value? A recent Reddit thread from a distinguished engineer in an AWS vertical struck a nerve. The claim is simple: AI has clearly increased visible activity – more documents, more code commits, more test harnesses – but not the value that users actually feel. “I see a [...]
JoshuaJuly 5, 2026
The AI adoption gap is real: what a blunt Reddit post gets right A recent Reddit thread tells a familiar story. A marketing-tech founder demos “AI agents” to a senior stakeholder at a big brand. The exec is sceptical, calls them “wrappers”, then asks for help setting up a WhatsApp broadcast channel. The punchline isn’t [...]
JoshuaJuly 5, 2026
Making a 3D RPG with AI only: what was built and why it matters A Redditor has shared an ambitious “AI-only” game dev experiment: a third-person 3D RPG prototype created without writing code, driven entirely by prompts to the muranyi-3 model from Tesana AI. You can read the full thread here: Making a RPG game [...]
JoshuaJuly 5, 2026
Last updated
Category
aiViews
23 viewsLikes
No ratings yet
No comments yet - start the conversation.