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src/routes/scorecard/categories.ts

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@@ -5,24 +5,58 @@ export const categories: Category[] = [
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name: 'Acknowledge',
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key: 'acknowledge',
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explanation:
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// 10: Pushing the conversation forward, making it more mainstream
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// 8: Has devoted substatial resources to public communication of AI risks
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// 7: Has made an attemt to communicate concerns to the public
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// 6: Has acknowledged xrisk, but no attempt to highlight these concerns
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// 5: E.g.no acknowledgement of risks, but also no denial.
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// 4: Active downlplaying of concerns, but in reasonable way
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// 3: Minimization of risk, dismissal, but not explicitly denying or attempt to move the conversation
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// 0: Actively denying the risks of AI, not discussing in good faith, attacking advocates on a personal level
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// How likely are they saying the risks are to happen?
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'How well does the company acknowledge the risks of AI? Do they acknowledge all the risks? How long did it take them to acknowledge the risks?'
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},
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{
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name: 'Lobby',
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key: 'lobby',
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// 10: Actively introducing draft legislations / concrete proposals that harm their internal business model but that are good for AI safety
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// 5: No lobbying, no attempt to influence regulation in any direction
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// 1: Using personal connections, money or financial incentives to influence regulation in a way that is very harmful to AI safety.
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// 0: Criminal lobbying, using illegal means to prevent meaningful AI safety regulation.
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explanation:
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'How much does the company lobby for AI regulation? Do they lobby for deregulation or for stricter regulation?'
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},
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{
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name: 'Deployment',
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key: 'deployment',
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explanation:
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// What principles drive your decisions about what (not) to deploy?
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// To what degree do you control access to your technology?
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// And do you monitor usage?
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// Are you willing to introduce new capabilities that others have not?
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// What are you open sourcing?
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// What are your plans
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// 0: Releases model weights of frontier models regardless of the risks.
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// 2: Releases frontier model weights, but only after testing for safety.
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// 3: Open model weights for models that are behind the state of the art, where comparable models have demonstrated to be (catastrophically) safe.
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// 5: No open source,
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'How long does the company wait before deploying a new model? Do they wait until they have a good understanding of the risks of the model? Are their models tested thoroughly?'
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},
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{
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name: 'Research',
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key: 'research',
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explanation:
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'Is the company doing research on AI safety? Are they doing research on how to mitigate the risks of AI?'
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// 10:
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// 5:
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// 0:
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'Is the company doing research on AI safety or alignment? Are they doing research on how to mitigate the risks of AI?'
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}
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// Frontier column
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// Are you pushing capabilities forward or are you following others to provide services?
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// This is where OpenAI scores 0 points.
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// To what extent do their future plans advance the state of the art?
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// Culture column
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// To what extent do you have a culture of safety?
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// Do the employees have a good understanding of the risks of AI?
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]

src/routes/scorecard/companies.ts

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@@ -66,8 +66,9 @@ const companiesSource: Company[] = [
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},
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deployment: {
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explanation:
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// Never released open source models.
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"Microsoft released an unfinished, sometimes even unhinged Bing (based on OpenAI's GPT-4) in April 2023. It was embarrassing and dangerous. OpenAI urged Microsoft not to do this - they did it anyway.",
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score: 0
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score: 4
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},
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research: {
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explanation:
@@ -157,8 +158,8 @@ const companiesSource: Company[] = [
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},
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lobby: {
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explanation:
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'They actively lobbied against the EU AI Act, almost causing it to not include frontier model regulations.',
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score: 2
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'Used an ex-minister to actively lobby against the EU AI Act, almost causing it to not include frontier model regulations.',
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score: 0
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},
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deployment: {
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explanation: 'They released their models without any safety work as torrents.',

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