AI Alignment Timeline Debate Position Map
Sort caller-supplied AI-alignment debate positions by year and report the earliest, latest, and mean positions.
Description
A forecast-position timeline organizes supplied labels and years.
A forecast-position timeline organizes supplied labels and years. Its arithmetic mean is not a probability-weighted consensus forecast.1
The returned values include Earliest position year, Latest position year, Mean position year, Timeline entries. The How section below explains the calculation, input rules and interpretation.
When to use AI Alignment Timeline Debate Position Map
Use AI Alignment Timeline Debate Position Map when you need to evaluate the supplied records under the calculation and evidence rules below. No debate positions are fetched, verified or assigned probabilities.
Define the question, evidence and scenario assumptions first. Supply the chosen score scales, time horizons or reference selection explicitly. Interpret generated text as a discussion template and screen labels as the stated rules.
How to use AI Alignment Timeline Debate Position Map and understand its results
- Define the question, evidence and scenario assumptions first. Supply the chosen score scales, time horizons or reference selection explicitly. Interpret generated text as a discussion template and screen labels as the stated rules.
- Enter positionLabels, positionYears using the field table and calculation rules, then run the tool.
- Read earliestPositionYear, latestPositionYear, meanPositionYear, timelineEntries. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| positionLabels | Position labels | list of string | Required |
| positionYears | Position years | list of number | Required |
Require aligned nonempty labels/finite nonnegative years and unique trimmed nonblank labels. Stable-sort by increasing year; return timeline strings, earliest/latest and unweighted mean. Fractional years are allowed.
mean=sum(years)/positionCount Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| earliestPositionYear | Earliest position year | number; minimum: 0 |
| latestPositionYear | Latest position year | number; minimum: 0 |
| meanPositionYear | Mean position year | number; minimum: 0 |
| timelineEntries | Timeline entries | list of string |
{
"input": {
"positionLabels": [
"Near-term systems",
"Long-term systems"
],
"positionYears": [
2045,
2030
]
},
"output": {
"earliestPositionYear": 2030,
"latestPositionYear": 2045,
"meanPositionYear": 2037.5,
"timelineEntries": [
"2030: Long-term systems",
"2045: Near-term systems"
]
}
}Limitations and assumptions
No debate positions are fetched, verified or assigned probabilities.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Core numeric and string lists are limited to 100,000 entries; text entries are subject to the general large-text limit. Follow any smaller calculation limits above. Missing fields without a declared default, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use AGI Forecast Survey Median Calculator: A survey can contain a row of respondent median years for each forecast question. Pooling all entries differs from averaging the per-question medians. For a complementary task, use Singularity Kurzweil Date Claim Verdict Lookup: Citation metadata can screen whether a dated prediction has supporting references. Support for a claim is separate from its eventual truth.
References
Similar or alternative tools
- AGI Forecast Survey Median Calculator
A survey can contain a row of respondent median years for each forecast question. Pooling all entries differs from averaging the per-question medians.
- Singularity Kurzweil Date Claim Verdict Lookup
Citation metadata can screen whether a dated prediction has supporting references. Support for a claim is separate from its eventual truth.