Joined 9 years ago
* TimeTracker (https://time-tracker.hosgeldin.click/) because I needed a privacy friendly freelancing tool that I needed personally.
* A simple exercise tracker that my wife requested from me (https://daily-menu.hosgeldin.click/) - later I will build a menstruation tracker that is connected to the Daily Menu.
* My magnum opus, "MyApps" (https://myapps.ideasofhakki.com/) - This is no less than an OS running in your browser, equipped with whatever "Apps" written in it. I am building it with GunDB and Svelte and foundationally it will be a web of apps running completely in your device (i.e. offline first), with privacy and data security built-in.
* Cram school management SIS for Turkish education system (https://edusis.hosgeldin.click/)
Has anybody had similar experiences? Does anybody have any advice for me? I have a faint hope that such things might actually gain traction on HN and even lead to a solution, which means a _human being_ from LinkedIn steps in and offers a solution, or at least, an explanation.
Here we go.
I also have a similar suspicion. Feels like if you have billions of dollars of investment in AI, then crashing things in the internet that criticize you, can easily be solved for a few millions. If this is the case, for me, it is the biggest proof that AI won't live up to the hype.
I will give you modern examples:
- facial recognition software used in cameras in public spaces
- mass monitoring phone calls, text and processing them
- predictive policing (has been criticized heavily, currently this is a popular topic in ethics of policing to train young philosophers on the issue. Last I heard, police departments in US have claimed to have opted out of this. Maybe they have better ways now?)
All these examples are from the west. If you never heard about any of this, you would be terrified at what they do in China, for instance.
Usually you would need to process data you collected and rely on some primitive indications to identify dissidents to the system. LLMs are a game changer on this aspect. When you know, you know :) ...
You might ask, was industrial revolution's impact on environment unethical, despite where it brought us? Of course it was unethical! If we had the opportunity to go back in time and make it better, we would! Except of course profit hungry people would still find ways to circumvent our new policies, and gain an economic edge over competitors by consuming more energy and thus, again, harming the environment. The same is happening with LLMs. People who seek profit are even building their own grids which generate electricity by burning fuel, just to run their data centers. They don't care about the impact it has on the environment in which we all live, and that is unethical.
And what if the need of power will bring about new tech that will allow green energy much more efficiently? Like fusion reactors that work. Sure, nobody is stopping you to develop those! But you cannot take a bet on people's, animals' and plants' well being and "have confidence" that it will all work out in the end! You cannot take a bet on people's lives for a promised future. Who has such a right? What an entitlement...
There is only one way to make this ethical: Will you take accountability on your shoulders, if it all fails? Then go be my guest. But no, if it all goes down, and instead we end up with a dystopian AI that can mass control everybody, and washed up shores and a world that became a desert, then every single person who has been responsible for the mess will go be free, while some innocent scapegoats will take the toll. So no, personally I am not giving consent for profit seeking people to take a bet on my planet's future.
2. If you can see the data with your eyes, then you should be able to train an AI with it. However when you commercialize your AI and chant non-stop about how all the writers and artists who contributed to your AI model were nothing other than a stepping stone for you to create your model, it turns into an attitude that is unethical.
But the owners of the model spend billions of dollars to train the models, so shouldn't they have the right to sell it? Well, if they had any _morals_, they could train smaller models patiently that could be build on nothing other than a research's fund. Then we could have developed bit quantization to make it cheaper. Then we could have come up with better models by distilling them to make the LLMs better and so on. But no, there are profits to be made and no time to loose! These needless ethics shall not hinder the progress (of making as much money as possible as soon as possible)...
3. Progress in tech will inevitably bring about disrupting changes to the society. I also see no problem with this. However I must point that, pro-AI people have a disrespect for people's hard earned skills. I sense a grudge in these people that they really want AI's to nullify people's skills, skills that they themselves are too lazy to develop. In AI marketing, I also sense a similar strategy, i.e. their selling point is "now everybody can become an artist"... No, they can't. In my opinion this point has less to do with ethics. Overtime we will all see whether these models live up to the hype. At the end the natural cycle of life will sort itself out.
4. I don't see your point. I think it is both a fundamental problem and an ethical issue. Let me explain.
Imagine that there is an ultimate Truth to something. We don't know what it is, but we have an idea about it. Now imagine that you are a bad actor who wished ill on people. You develop smart sounding propaganda to steer public opinion away from the Truth.
An LLM with bias is exactly that. So it is an ethical problem.
It is also a fundamental problem, that is, whether AI gives correct or incorrect answer. If it is giving incorrect answers, then it is unremarkable. Currently, as far as my observations go, LLM's generate both (1) grammatically correct sentences and (2) sentences that seem contextually accurate. Whether the content of their saying are correct or not, really seems to be depending on how much of the requested Truth already exists in the Internet. So great, we invented a system that can recycle what is said on the Internet.
Don't get me wrong: I do think that it is a great advance in information processing, linguistics and machine learning. But for some reason, we don't seem to be ready to acknowledge it's shortcomings as a serious problem. Instead, there seems to be a general opinion that "it will get better". No, the thing is that, if it hits a point in development where it generates enough value for the commercial companies, we will end up with a smart sounding propaganda machine that can control uninformed masses in a scale that was unimaginable even for the most pessimistic person.
5. -> Seems like close-to-state-of-the-art LLMs will be commodified, etc.
The reason why I don't like your attitude is because of this. Yes, indeed, models will be developed by the open source crowd and will be in the hands of many. Surely progress in tech will bring about this.
And yet. This has nothing to do with what the author is saying. She is saying that _these LLMs_ made by _these companies_ (you know which ones we are talking about) will be used to concentrate power. Commodification of other models does not negate her point.
-> If it really becomes important I don't see why you couldn't just rustle up some donations for a truly open model or whatever.
I will shut up about this point when _it happens_. Until then, people who agree with me must keep bringing these issues to people's attention. AI has been used for controlling masses long before LLMs. Now it has been supercharged by LLMs because they can interpret human language pretty well. Therefore I think the blog post's author has a good point on this issue.
Overall I see hand waiving and weak dismissal of her points.
I wonder if the most recent data from internet that ended up in the training data makes chatgpt lean towards randomly picking that name. [1] https://www.momjunction.com/baby-names/elara/#popularity-ove...
What does von Neumann mean here? Why is it bad that it will develop along the line of least resistance? Does von Neumann advice that working on "harder" problems is more beneficial for TCS? Could not one argue that we should be solving away low hanging fruits first?
I am not sure if I am understanding von Neumann's quote nor this article properly. I would love to hear some simpler explanation (I am a new BSc. CS graduate).
