Not necessarily overfitting, but lack of transparency and easy editing are the major things. See previous thread:
ETHICS
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Organizational AI adoption challenges and malicious threat mitigation
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Yeah, and don't get me wrong, this is very cool work! And I know you folks know these things. But
1. I think there's a lot of people who don't and just hope for a "silver bullet" and
2. Getting organizational buy-in seems tricky, particularly with malicious parties out there. -
Misinformation and Truth in AI Era: Eli Lilly Stock Story
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What even is truth any more? Apparently that Eli Lilly stock story itself may be more misinformation https://
x.com/mikepqr/status
/mikepqr/status/1591198852279066624
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Open Source AI Models and Regulatory Frameworks Need Society Agreement
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I'm also cautious about rogue model designers who don't play by the rules. At least for the time being, it seems like the community is very good at making open source alternatives to proprietary models. We'd need to agree as a society that certain things should be off limits.
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Model Designers and Users Share AI Safety Responsibility
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Definitely! With cooperation from model designers, there's hope. But like I said, if all the burden is on the users alone? Then I'm not so hopeful.
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Rich People Power and Organizational Resistance Strategies
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Let's say no in case one of them is listening 😉 More seriously whether you're a for-profit, non-profit, public or private, the truth is that rich people can always mess with you. Hopefully they won't and we'll try to resist if they do!
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Federated Learning: Training ML Models While Protecting User Privacy
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While most #ML models are trained by collecting data on a central server, federated learning makes it possible to train models without any user's raw data leaving their device. Check out the latest AI Explorable on how federated learning protects privacy→ https://t.co/5hDzyWomiO pic.twitter.com/xwd4xrn4Wi
— Google AI (@GoogleAI) 11 novembre 2022While most #ML models are trained by collecting data on a central server, federated learning makes it possible to train models without any user's raw data leaving their device. Check out the latest AI Explorable on how federated learning protects privacy→ https://
pair.withgoogle.com/explorables/fe
derated-learning/
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Image Sanitization Safety Against Advanced AI Models
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Nice article by @KyleBarr5
. I gave my perspective (really, the perspective of Radiya-Dixit et al. https://
arxiv.org/abs/2106.14851): users sanitizing and releasing their own images seems hopeless. It may be safe today, but it probably won't be safe against a smarter model a year from now. -
When We Realize We’re Just Stochastic Parrots
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what happens when we realize we were just stochastic parrots all along?
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AI Impersonation Service Creates Identity Fraud Problems
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Who could have possibly predicted that selling the ability to impersonate anyone for a few hours for $8 would result in problems with "impersonation issues"?