Researcher at the Quantified Uncertainty Research Institute
Published
Edited
May 5, 2022
1 fork
clusterNames = [
"abstract AI alignment research",
"prosaic AI alignment research",
"AI governance",
"influence-seeking interventions",
"clarity-seeking interventions"
]
elements = [
"Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)",
"Machine Intelligence Research Institute — AI Safety Retraining Program",
"Ought — General Support (2018)",
"Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer",
"Oxford University — Research on the Global Politics of AI",
"UC Berkeley — AI Safety Research (2018)",
"Open Phil AI Fellowship — 2018 Class",
"Wilson Center — AI Policy Seminar Series",
"AI Impacts — General Support (2018)"
]
clusters = ({
"abstract AI alignment research": [
"Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)",
"Machine Intelligence Research Institute — AI Safety Retraining Program"
],
"prosaic AI alignment research": [
"Ought — General Support (2018)",
"Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer"
],
"AI governance": [
"Oxford University — Research on the Global Politics of AI"
],
"influence-seeking interventions": [
"UC Berkeley — AI Safety Research (2018)",
"Open Phil AI Fellowship — 2018 Class",
"Wilson Center — AI Policy Seminar Series"
],
"clarity-seeking interventions": ["AI Impacts — General Support (2018)"]
})
md`Below, replace the "x to y"s with a numeric range instead`
Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.
relativeValuesInClusters = ({
"abstract AI alignment research": {
"Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)":
"1",
"Machine Intelligence Research Institute — AI Safety Retraining Program":
"x to y" // replace with "number to number"
},
"prosaic AI alignment research": {
"Ought — General Support (2018)": 1,
"Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer":
"x to y"
},
"AI governance": {
"Oxford University — Research on the Global Politics of AI": 1
},
"influence-seeking interventions": {
"UC Berkeley — AI Safety Research (2018)": "1",
"Open Phil AI Fellowship — 2018 Class": "x to y",
"Wilson Center — AI Policy Seminar Series": "x to y"
},
"clarity-seeking interventions": {
"AI Impacts — General Support (2018)": 1
},
"general comparisons": {
"one year of Paul Christiano's work": 1, // reference value only
"abstract AI alignment research": "x to y",
"prosaic AI alignment research": "x to y",
"AI governance": "x to y",
"influence-seeking interventions": "x to y",
"clarity-seeking interventions": "x to y"
}
})
getRelativeValues("Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer", "Open Phil AI Fellowship — 2018 Class")
getRelativeValuesAndDisplay("Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer", "Open Phil AI Fellowship — 2018 Class")
getRelativeValues("Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer", "Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer")
function getRelativeValues(item1, item2) {
if(item1 == item2) return ({
squiggleString: "1",
shortGuesstimateString: "1",
array90CI: "1",
})
// using simpleSquiggle
let clusterNames = Object.keys(relativeValuesInClusters);
let getCluster = (item) =>
clusterNames.filter((clusterName) =>
Object.keys(relativeValuesInClusters[clusterName]).includes(item)
);
let cluster1Name = getCluster(item1)[0];
let cluster2Name = getCluster(item2)[0];
let relativeValueCalculation;
if (cluster1Name == cluster2Name) {
let relativeValue1 = relativeValuesInClusters[cluster1Name][item1];
let relativeValue2 = relativeValuesInClusters[cluster1Name][item2];
relativeValueCalculation = `${relativeValue1}/${relativeValue2}`;
} else {
let relativeValueCluster1 =
relativeValuesInClusters["general comparisons"][cluster1Name];
let relativeValueCluster2 =
relativeValuesInClusters["general comparisons"][cluster2Name];
let relativeValueOfClustersCalculation = `${relativeValueCluster1}/${relativeValueCluster2}`;
let relativeValueWithinCluster1 =
relativeValuesInClusters[cluster1Name][item1];
let relativeValueWithinCluster2 =
relativeValuesInClusters[cluster2Name][item2];
relativeValueCalculation = `( ${relativeValueWithinCluster1} * ${relativeValueCluster1} )/( ${relativeValueWithinCluster2} * ${relativeValueCluster2} )`;
}
let relativeValueCalculationOutput = simpleSquiggleCalculate(
relativeValueCalculation
);
/*
let relativeValueDisplay = simpleSquiggleDisplay(
relativeValueCalculationOutput
);
*/
return relativeValueCalculationOutput; // value1/value2
//console.log([cluster1Name, cluster2Name])
}
data = {
let elementsSliced = elements;
let results = [];
let getInnerDisplay = (x) =>
x > 100
? BigInt(Math.round(x.toPrecision(2))).toString()
: x.toPrecision(2).toLocaleString();
let getDisplayString0 = (relativeValues) =>
!!relativeValues.array90CI
? `${getInnerDisplay(relativeValues.array90CI[0])} to ${getInnerDisplay(
relativeValues.array90CI[1]
)}`
: relativeValues.squiggleString;
let getDisplayString = (relativeValues) => relativeValues.shortGuesstimateString
for (let elementi of elementsSliced) {
let object = { name: elementi };
elementsSliced.forEach(
(elementj) =>
(object[elementj] =
elementi == elementj
? 1
: getDisplayString(getRelativeValues(elementi, elementj)))
);
results.push(object);
}
return results;
}
format = {
let result = ({})
elements.forEach(element => result[element] = cell)
return result
}
Inputs.table(data)
simpleSquiggleImport = import('https://cdn.skypack.dev/@forecasting/simple-squiggle@1.3.1')
Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.
simpleSquiggleCalculate = (string) =>
simpleSquiggleImport.calculator(string)
simpleSquiggleDisplay = (string) => cell(simpleSquiggleCalculate(string).squiggleString)
simpleSquiggleCalculate("1 to 10")
simpleSquiggleDisplay("1 to 10")
cell("lognormal(1,0.1)")
function sparkbar(max) {
return (x) => htl.html`<div style="
background: lightblue;
width: ${(100 * x) / max}%;
float: right;
padding-right: 3px;
box-sizing: border-box;
overflow: visible;
display: flex;
justify-content: end;">${x.toLocaleString("en")}`;
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
