Diyana on Nostr: HRF and gladstein 🫶🏻👇🏻🫂 If you're working at the intersection of AI ...
HRF (nprofile…t5ph) and gladstein (nprofile…89xw) 🫶🏻👇🏻🫂
If you're working at the intersection of AI and individual human rights, EleutherAI’s research on bias can be incredibly useful in several ways:
1. Identifying & Reducing AI Discrimination
AI systems influence decisions in hiring, policing, lending, and healthcare. Understanding how biases form in AI (as EleutherAI's Pythia project explores) can help you build models that don’t unfairly disadvantage certain groups.
2. Designing Fairer AI Models
Their research shows that fine-tuning with neutral data can reduce bias. If you're building AI systems for human rights advocacy, this means you can train models with carefully selected, diverse, and neutral datasets to make them more fair and ethical.
3. Holding AI Accountable
Since EleutherAI focuses on open-source AI, their models allow researchers and activists to inspect AI systems instead of relying on black-box models from big tech. This transparency helps in advocating for AI accountability in areas like censorship, surveillance, and algorithmic discrimination.
4. Fighting AI-Driven Oppression
Authoritarian regimes and oppressive institutions can use biased AI to control narratives, suppress dissent, or profile certain groups. Studying bias in AI can help activists detect and challenge these abuses, ensuring AI respects fundamental rights like freedom of speech and privacy.
5. Strengthening Digital Rights & Decentralization
Since you’re brainstorming how Nostr and Bitcoin could support a regenerative civilization, EleutherAI’s work aligns with this by promoting decentralized AI research. This means AI won’t be controlled by a few corporations or governments, making it more resistant to censorship and manipulation.
In short, their work can help you build AI tools that protect human rights instead of harming them, by making AI fairer, more transparent, and resistant to abuse. Would you want to explore specific applications of this in your work?
If you're working at the intersection of AI and individual human rights, EleutherAI’s research on bias can be incredibly useful in several ways:
1. Identifying & Reducing AI Discrimination
AI systems influence decisions in hiring, policing, lending, and healthcare. Understanding how biases form in AI (as EleutherAI's Pythia project explores) can help you build models that don’t unfairly disadvantage certain groups.
2. Designing Fairer AI Models
Their research shows that fine-tuning with neutral data can reduce bias. If you're building AI systems for human rights advocacy, this means you can train models with carefully selected, diverse, and neutral datasets to make them more fair and ethical.
3. Holding AI Accountable
Since EleutherAI focuses on open-source AI, their models allow researchers and activists to inspect AI systems instead of relying on black-box models from big tech. This transparency helps in advocating for AI accountability in areas like censorship, surveillance, and algorithmic discrimination.
4. Fighting AI-Driven Oppression
Authoritarian regimes and oppressive institutions can use biased AI to control narratives, suppress dissent, or profile certain groups. Studying bias in AI can help activists detect and challenge these abuses, ensuring AI respects fundamental rights like freedom of speech and privacy.
5. Strengthening Digital Rights & Decentralization
Since you’re brainstorming how Nostr and Bitcoin could support a regenerative civilization, EleutherAI’s work aligns with this by promoting decentralized AI research. This means AI won’t be controlled by a few corporations or governments, making it more resistant to censorship and manipulation.
In short, their work can help you build AI tools that protect human rights instead of harming them, by making AI fairer, more transparent, and resistant to abuse. Would you want to explore specific applications of this in your work?
quoting nevent1q…ddfaThank you... Checking it out:
EleutherAI has recently made significant contributions to open-source AI research:
Pythia Model Suite: Designed to facilitate scientific research on large language models, Pythia offers 154 partially trained model checkpoints, fully public training data, and reproducible training sequences. This suite enables studies on verifiable training, social biases, and memorization.
OpenFold: In collaboration with Stability AI, NVIDIA, and biologists from Columbia and Harvard Universities, EleutherAI contributed to training OpenFold, an open-source replication of DeepMind's AlphaFold2. This project aims to advance protein structure prediction and democratize access to such tools in the scientific community.
These initiatives underscore EleutherAI's commitment to advancing open-source AI research and promoting accessibility within the scientific community.