AI Safety Intelligence Telemetry

AI Catastrophic Risk & Safeguard Timeline Explorer

Interactive 10-year existential hazard pacing model assessing Evan Hubinger’s >10% decadal risk warning and Anthropic researcher departure dynamics.

Source context: CNBC report on Anthropic safety researcher warnings and lab resignation alerts.
Model Parameters 10-Yr Horizon
10%
Evan Hubinger's estimate: >10% chance AI could kill all humans within a decade.
82
Frequency of safety researcher departures protesting reckless speed over safeguards.
45
Internal Responsible Scaling Policy (RSP) enforcement and deployment pause triggers.
1.2x
Ratio of compute/talent dedicated strictly to alignment vs raw frontier capability.
Cumulative 10-Yr Risk
14.2%
Baseline + compound deficit
Safeguard Deficit Index
28.4
Pacing gap score (>25 alert)
Safety Researcher Benchmark
Evan Hubinger
Anthropic Research Team
System Risk Assessment
High Risk Threshold Exceeded
Recommended Mitigation: Mandatory pause on autonomous recursive self-improvement loops

Decadal Cumulative Hazard Curve (Years 1 to 10)

D3.js dynamic projection
Projected Hazard Trajectory
10% Hubinger Warning Baseline
14% Critical Danger Threshold

10-Year Annual Risk Progression Table

Horizon Year Annual Increment Cumulative P[Doom] Safeguard Deficit Containment Status

Risk timeline: linear interpolation is not hazard evidence

Read the explanation

The timeline begins with ten percent risk supplied by the user and constructs an assumed safeguard deficit. Half of resignation pressure eighty two minus a quarter of governance forty five minus one point two times one point one two five gives twenty eight point four. It then adds point fifteen times deficit to initial risk and subtracts point three times the investment multiplier above one, yielding fourteen point two. Bars encode deficit and risk at ten pixels per number, explicitly different units rather than measured comparable quantities. Coefficients and classifications are authored assumptions. The referenced warning is not independently verified in this offline audit and does not validate how resignation pressure maps to extinction probability. Changing governance from forty five to one hundred lowers raw deficit to fourteen point six five, rounded fourteen point seven. The later risk equation uses that rounded deficit, giving twelve point one after another rounding step. Bars compare fourteen point two and twelve point one at twenty pixels per caption point. Threshold fourteen is inclusive for high status and ten is inclusive for elevated status; policy labels follow these bands without independently predicting intervention efficacy. Inputs are not probabilities with an enforced zero-to-one bound: valid minimum initial risk one, resignation zero, governance one hundred and multiplier three produce a negative three point nine percent caption. This exposes why the output should be treated as a heuristic score rather than a calibrated probability. The ten yearly rows are a straight interpolation from twenty percent of initial risk to the computed endpoint, not a survival-probability or hazard model. Defaults use starting value two and step one point two two, so first year is three point two two rounded three point two and tenth year fourteen point two. Bars compare rounded first and final values at ten pixels per point. Calendar labels run twenty twenty seven to twenty thirty six and are fixed, not tied to the current date. The table annual increment column is risk divided by year times point eight, so its label does not equal the actual adjacent-row difference. Original D3 absence stops the chart after table and metrics, but native sliders and JSON download operate. Four native widths preserve the whole controls/result grid, original SVG and all footer placement, with local playback separate from exhaustive or public completion.

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