Foundations

The principles that guide how Immortal AI investigates, verifies and explains stories about artificial intelligence.

1. Evidence before narrative

We begin with what can be established. We do not stretch incomplete evidence to produce a stronger headline or a cleaner story.

2. The human question comes first

Technology matters because of what it does in the world. We ask how a system changes a person’s choices, opportunities, relationships, privacy, safety or power.

3. Follow power and incentives

We examine who designs the system, who controls it, who profits from it, what pressures shape decisions and whether the people carrying the risk have meaningful influence over those decisions.

4. Accountability cannot disappear into the algorithm

When AI contributes to a consequential decision, responsibility still belongs somewhere. We ask who authorised the system, who supervised it, who could intervene and who ultimately owns the outcome.

5. Protect people who are vulnerable

Children, older people, people in crisis and people with limited technical knowledge may face greater exposure to manipulation, deception or dependency. Reporting should examine the design and governance failures around them rather than blaming them for being affected.

6. State uncertainty plainly

Confirmed fact, allegation, expert interpretation and our own inference are not interchangeable. We label the difference.

7. Avoid both hype and panic

AI can produce real benefits and real harms. We do not minimise either. We reject simplistic narratives that portray every advance as salvation or every risk as catastrophe.

8. Corrections are part of credibility

When material information is wrong, incomplete or materially changed by new evidence, we correct the record clearly.

Our standard: human question → source → evidence → incentives → accountability → uncertainty.