This is a most excellent place for technology news and articles.
I was talking to someone who does software development, and he described his experiments with AI for coding.
He said that he was able to use it successfully and come to a solution that was elegant and appropriate.
However, what he did not do was learn how to solve the problem, or indeed learn anything that would help him in future work.
I feel you, but I've asked it why questions too.
The one thing that I learned when talking to chatGPT or any other AI on a technical subject is you have to ask the AI to cite its sources. Because AIs can absolutely bullshit without knowing it, and asking for the sources is critical to double checking.
I've found questions about niche tools tend to get worse answers. I was asking if some stuff about jpackage and it couldn't give me any working suggestions or correct information. Stuff I've asked about Docker was much better.
The ability of AI to write things with lots of boilerplate like Kubernetes manifests is astounding. It gets me 90-95% of the way there and saves me about 50% of my development time. I still have to understand the result before deployment because I'm not going to blindly deploy something that AI wrote and it rarely works without modifications, but it definitely cuts my development time significantly.
Well that is obvious why, isn’t it!?
I consider myself very average, and all my average interactions with AI have been abysmal failures that are hilariously wrong. I invested time and money into trying various models to help me with data analysis work, and they can't even do basic math or summaries of a PDF and the data contained within.
I was impressed with how good the things are at interpreting human fiction, jokes, writing and feelings. Which is really weird, in the context of our perceptions of what AI will be like, it's the exact opposite. The first AI's aren't emotionless robots, they're whiny, inaccurate, delusional and unpredictable bitches. That alone is worth the price of admission for the humor and silliness of it all, but certainly not worth upending society over, it's still just a huge novelty.
It makes HAL 9000 from 2001: A Space Odyessy seem realistic. In the movie he is a highly technical AI but doesn't understand the implications of what he wants to do. He sees Dave as a detriment to the mission and it can be better accomplished without him... not stopping to think about the implications of what he is doing.
I mean, leave it up the one of the greatest creative minds of all time to predict that our AI will be unpredictable and emotional. The man invented the communication satellite and wrote franchises that are still being lined up to make into major hollywood releases half a century later.
Microsoft LLM whatever the name is gives sources, or at least it did to me yesterday.
The definition of critical thinking is not relying on only one source. Next rain will make you wet keep tuned.
Microsoft said it so I guess it must be true then 🤷♂️
Linux study, finds that relying on MS kills critical thinking skills. 😂
Damn. Guess we oughtta stop using AI like we do drugs/pron/ 😀
Unlike those others, Microsoft could do something about this considering they are literally part of the problem.
And yet I doubt Copilot will be going anywhere.
Quickly, ask AI how to improve or practice critical thinking skills!
Improving your critical thinking skills is a process that involves learning new techniques, practicing them regularly, and reflecting on your thought processes. Here’s a comprehensive approach:
1. Build a Foundation in Logic and Reasoning
• Study basic logic: Familiarize yourself with formal and informal logic (e.g., learning about common fallacies, syllogisms, and deductive vs. inductive reasoning). This forms the groundwork for assessing arguments objectively.
• Learn structured methods: Books and online courses on critical thinking (such as Lewis Vaughn’s texts) provide a systematic introduction to these concepts.
2. Practice Socratic Questioning
• Ask open-ended questions: Challenge assumptions by repeatedly asking “why†and “how†to uncover underlying beliefs and evidence.
• Reflect on responses: This method helps you clarify your own reasoning and discover alternative viewpoints.
3. Engage in Reflective Practice
• Keep a journal: Write about decisions, problems, or debates you’ve had. Reflect on what went well, where you might have been biased, and what could be improved.
• Use structured reflection models: Approaches like Gibbs’ reflective cycle guide you through describing an experience, analyzing it, and planning improvements.
4. Use Structured Frameworks
• Follow multi-step processes: For example, the Asana article “How to build your critical thinking skills in 7 steps†suggests: identify the problem, gather information, analyze data, consider alternatives, draw conclusions, communicate solutions, and then reflect on the process.
• Experiment with frameworks like Six Thinking Hats: This method helps you view issues from different angles (facts, emotions, positives, negatives, creativity, and process control) by “wearing†a different metaphorical hat for each perspective.
5. Read Widely and Critically
• Expose yourself to diverse perspectives: Reading quality journalism (e.g., The Economist, FT) or academic articles forces you to analyze arguments, recognize biases, and evaluate evidence.
• Practice lateral reading: Verify information by consulting multiple sources and questioning the credibility of each.
6. Participate in Discussions and Debates
• Engage with peers: Whether through formal debates, classroom discussions, or online forums, articulating your views and defending them against criticism deepens your reasoning.
• Embrace feedback: Learn to view criticism as an opportunity to refine your thought process rather than a personal attack.
7. Apply Critical Thinking to Real-World Problems
• Experiment in everyday scenarios: Use critical thinking when making decisions—such as planning your day, solving work problems, or evaluating news stories.
• Practice with “what-if†scenarios: This helps build your ability to foresee consequences and assess risks (as noted by Harvard Business’s discussion on avoiding the urgency trap).
8. Develop a Habit of Continuous Learning
• Set aside regular “mental workout†time: Like scheduled exercise, devote time to tackling complex questions without distractions.
• Reflect on your biases and update your beliefs: Over time, becoming aware of and adjusting for your cognitive biases will improve your judgment.
By integrating these strategies into your daily routine, you can gradually sharpen your critical thinking abilities. Remember, the key is consistency and the willingness to challenge your own assumptions continually.
Happy thinking!
You can either use AI to just vomit dubious information at you or you can use it as a tool to do stuff. The more specific the task, the better LLMs work. When I use LLMs for highly specific coding tasks that I couldn't do otherwise (I'm not a [good] coder), it does not make me worse at critical thinking.
I actually understand programming much better because of LLMs. I have to debug their code, do research so I know how to prompt it best to get what I want, do research into programming and software design principles, etc.
You mean an AI that literally generated text based on applying a mathematical function to input text doesn't do reasoning for me? (/s)
I'm pretty certain every programmer alive knew this was coming as soon as we saw people trying to use it years ago.
It's funny because I never get what I want out of AI. I've been thinking this whole time "am I just too dumb to ask the AI to do what I need?" Now I'm beginning to think "am I not dumb enough to find AI tools useful?"
Idk man. I just used it the other day for recalling some regex syntax and it was a bit helpful. However, if you use it to help you generate the regex prompt, it won't do that successfully. However, it can break down the regex and explain it to you.
Ofc you all can say "just read the damn manual", sure I could do that too, but asking an generative a.i to explain a script can also be as effective.
what got regex to do with critical thinking?
researchers at Microsoft and Carnegie Mellon University found that the more humans lean on AI tools to complete their tasks, the less critical thinking they do, making it more difficult to call upon the skills when they are needed.
It's one thing to try to do and then ask for help (as you did), it's another to just ask it to "do x" without thought or effort which is what the study is about.
So the study just checks how many people not yet learned how to properly use GenAI
I think there exists a curve from not trusting to overtrusting than back to not blindly trusting outputs (because you suffered consequences from blindly trusting)
And there will always be people blindly trusting bullshit, we have that longer than genAI. We have enough populists proving that you can tell many people just anything and they believe.
yes, exactly. You lose your critical thinking skills
Sounds a bit bogus to call this a causation. Much more likely that people who are more gullible in general also believe AI whatever it says.
This isn't a profound extrapolation. It's akin to saying "Kids who cheat on the exam do worse in practical skills tests than those that read the material and did the homework." Or "kids who watch TV lack the reading skills of kids who read books".
Asking something else to do your mental labor for you means never developing your brain muscle to do the work on its own. By contrast, regularly exercising the brain muscle yields better long term mental fitness and intuitive skills.
This isn't predicated on the gullibility of the practitioner. The lack of mental exercise produces gullibility.
Its just not something particular to AI. If you use any kind of 3rd party analysis in lieu of personal interrogation, you're going to suffer in your capacity for future inquiry.
All tools can be abused tbh. Before chatgpt was a thing, we called those programmers the StackOverflow kids, copy the first answer and hope for the best memes.
After searching for a solution a bit and not finding jack shit, asking a llm about some specific API thing or simple implementation example so you can extrapolate it into your complex code and confirm what it does reading the docs, both enriches the mind and you learn new techniques for the future.
Good programmers do what I described, bad programmers copy and run without reading. It's just like SO kids.
Well no shit Sherlock.
Corporations and politicians: "oh great news everyone... It worked. Time to kick off phase 2..."
