Submitted by SoulGuardian55 t3_10ro4hc in singularity
Not long time ago, engaged in dispute about using AI in every part of our life. For clarity, the debate was among ordinary people and in a country (from Russia*) where the topic of AI is not so vividly discussed in society. But the results pretty similar anyway. Here what they said to me. To do justice, all of these words presented by one man:
- The main emphasis is placed on the fact that neural networks cannot be trusted, even taking into account very rapid progress, they will remain neural networks, and other architectures will not replace them. Obviously, such an incomplete understanding of the topic is caused by a lack of information. It got to the point that narrow AI was referred to as general AI.
- "We don't need general AI, we've been doing well ourselves for the last 40,000 years without it."
- Neural networks and machine learning will only lead us to the wrong results, because they themselves cannot identify positively the problem without a human.
- You cannot be sure of the truthfulness of AlphaFold's predictions (and predictions of AlphaFold-like systems), because it's only trained on the available data, and did not install proteins on his own, in real time.
- In five years if someone ends up in hospital, remember it's because your doctor used AI-systems to help him earn a degree and finish diploma.
(*No matter what you think about current conflict between Russia and Ukraine, please, in the name of healthy dispute don't bring up politics and war.)
Nadeja_ t1_j6wtvef wrote
Although neural networks (the human brain too) tend to “hallucinate” and to make things up (your own memory isn’t 100% reliable either) that’s why we help our memory with pictures, taking notes, journals, record numbers and so on (not just because we forget, but also because we might not remember correctly). If you want to retrieve accurate info from a nn, then you have it to understand your question and come up with the probable answer, then find the source on the net or in a database, then, if found, a quote function returns the exact quote/info. However, trust-wise, there is the alignment problem, but that’s another story.
Yeah, that sounds like “we don’t need the wheel, because we did fine without it in the past 300,000 years”.
“Would only”, “would never”… is reasoning in absolutist terms, witch ends up in faulty predictions such as “heavier than air machines would never fly”. For now, with the current models, you still have to to review the results: the generated answer or may contain inaccurate or made up info, the generated code may have bugs or not work at all, the generated image comes with weird stuff that you notice when you zoom in or the hands look funny, and so on. But it’s pretty likely that eventually we will have reliable models that understand the context better, that know how a hand is supposed to be and how it works, that return accurate sourced info, that code like the best professional. Our brain is the example that’s doable, unless you believe (based on no evidence) it’s because of something magical.
You can hardly be 100% be sure of anything, if you ask to a philosopher, and there may be some issue, but there are also peer reviewed papers.
Or maybe the opposite happens and there would be fewer wrong diagnoses. In the medical field there is already who uses machine learning. Still, students shouldn’t delegate their learning, reasoning and writing to language models and other models (not yet at least, I’m not sure how I would feel when an ASI will be around), but use them to improve (e.g. you ask ChatGPT to improve your essay and you learn how to write better).