this post was submitted on 05 Jul 2024
28 points (100.0% liked)
Gaming
2520 readers
22 users here now
The Lemmy.zip Gaming Community
For news, discussions and memes!
Community Rules
This community follows the Lemmy.zip Instance rules, with the inclusion of the following rule:
You can see Lemmy.zip's rules by going to our Code of Conduct.
What to Expect in Our Code of Conduct:
- Respectful Communication: We strive for positive, constructive dialogue and encourage all members to engage with one another in a courteous and understanding manner.
- Inclusivity: Embracing diversity is at the core of our community. We welcome members from all walks of life and expect interactions to be conducted without discrimination.
- Privacy: Your privacy is paramount. Please respect the privacy of others just as you expect yours to be treated. Personal information should never be shared without consent.
- Integrity: We believe in the integrity of speech and action. As such, honesty is expected, and deceptive practices are strictly prohibited.
- Collaboration: Whether you're here to learn, teach, or simply engage in discussion, collaboration is key. Support your fellow members and contribute positively to shared learning and growth.
If you enjoy reading legal stuff, you can check it all out at legal.lemmy.zip.
founded 1 year ago
MODERATORS
Crowdsourcing who remembers crowdsourcing?! Before we put AI in fucking everything.
Now that you mention it, isn't AI essentially worse crowdsourcing?
It's not quite that simple. Crowdsourcing has many of the drawbacks that AI has too.
While it can have a higher reliability in detecting nonsensical inputs or inputs that it's simply unfit in processing, that comes at an intrinsic cost in scalability. Some tasks can't be effectively crowdsourced for, either because of volume or urgency.
Machine Learning systems learn to approximate decision making and thus can attempt at learning from crowdsourcing efforts. It is notable though that depending on the use case, model and training method, machine learning algorithms can potentially be better than the data it was trained on. Or much worse, it's very fickle.
It is definitely still the case that crowdsourcing is a really important tool and oftentimes machine learning relies on it's efforts. And it naturally can solve tasks that we don't have a viable automated approach for.