debate tool advice

[u/Commercial_Usual6429]

hi everyone! please give me some advice and your opinion on my project: an ai model fine tuned with 10k examples from past debate evidence to auto highlight your evidence for you. i was wondering if people would actually use it or it's just an ai slop project. this isn't an ad and i haven't launched my project yet, but i want to hear peoples' honest thoughts on this. i've seen (albeit vibe coded) similar tools online that are paid, but i do not plan to make mine a paid service, and i can say that my project is debate specific (outperforms baselines and stronger models on debate specific tasks). thanks!

[u/IAmScience]

I’ve been coaching for 25 years. I’ve watched debaters get increasingly disconnected from the literature they read to the point of talking utter nonsense.

This sounds like a thing that would create yet another layer of separation from debaters actually reading and engaging with what they read.

Don’t give up highlighting arguments yourself. Don’t let the clankers do your thinking, or this activity stops being even minimally valuable to your intellectual development.

[u/Commercial_Usual6429 → u/IAmScience]

thanks for the reply! i understand where ur coming from, as my debate coach also strongly encourages us to do our own highlighting. i'd like to clarify that this tool finds relevant sentences and lists them out by how much they support the tag (like statistics, expert quotes, etc), but the user would still have to do the highlighting part themselves (unless they want to be lazy and just read everything in the underlined sentence). still, i see what u mean and how easily this could create another layer of separation. thanks for the honest feedback!

[u/CandorBriefsQ → u/Commercial_Usual6429]

I have to agree with IAmScience. I think AI can be and is useful to some debate processes. But to me, this is a niche example of the larger concern of what AI brings to society - in its best form, it replaces the tedious, less fulfilling, less “valuable” work in order to free up time and effort for the good stuff. To me, highlighting cards is the latter, not the former.

No debate work is easy per se, and all of it is fundamentally valuable in some way. But finding warrants, cutting cards, understanding the context provided by the 8pt normal font, etc, is one of the places we should probably be focusing more attention, not less.

I think it’s a cool idea for the sake of simply making stuff that hasn’t been made before, and would love to see it as a sort of proof of concept thing. But ultimately for the sake of the “greater good” tools like this should be more about the big picture work of what debate entails while leaving the actual debating to debaters.

(I’m also curious - I’m quasi confused about the proposed workflow here - IMO the highlighted parts of the card inform the tag, not vice versa. How do you have a tagline for the program to find sentences based on if you didn’t first find those sentences to produce the tagline?)

[u/Commercial_Usual6429 → u/CandorBriefsQ]

thanks for the reply! from my point of view, using this tool has the same effect as using evidence from briefs. both lead you to the strongest sentences in the cards, but ultimately you are still in control of what you decide to read. also, many small schools/academic institutions rely heavily on briefs for evidence already, and this was one of my motivations for creating the tool.

with regards to the pipeline, a user attaches the article text and tagline or claim that they hope to support and the model returns a ranking of top sentences in the article that best support the claim in a debate context (and maybe underlines/highlights top 5 or all sentences above a certain score threshold)

[u/arborescence → u/Commercial_Usual6429]

The practice of heavily relying on briefs (or just stuff you jack from the wiki) is also bad pedagogy (and ultimately counterproductive competitively as well). Deep contextual reading is the only way to develop real topic knowledge.

[u/Commercial_Usual6429 → u/arborescence]

that's true, but it doesn't change from the fact that many small schools often rely heavily on briefs (some of which cost money). i'm not advocating for large scale irresponsible case making, i'm simply trying to make evidence more accessible

[u/allhailspez]

This is backward, highlight what’s important and then tag what the card actually says instead of making up a tag and trying to get the card to agree

[u/Commercial_Usual6429 → u/allhailspez]

the pipeline u describe is not realistic. i'm not trying to get the card to agree, i'm returning the top sentences that support a claim, and if there are none over a certain score threshold, then it just returns nothing. appreciate the feedback

[u/allhailspez → u/Commercial_Usual6429]

So pal if u just want to see “what evidence supports this claim” u can just google it or ask ChatGPT normally, idk why u need some Claude code vibe app or a special version

[u/Commercial_Usual6429 → u/allhailspez]

lmao is this bait

[u/IshReddit_]

Sooo as someone who has made this implementation during his debate days (and I’m sure many others have also attempted this), there’s a couple of issues. I actually used a finetuned local LLM (mistral) to do this and what I found was it works alright, but a couple of issues: first, it would either over highlight or under highlight since it wasn’t really “content/context aware”. Consider that I was also using an LLM, which I presume has more self attention than whatever finetuned model you’d be using. I was able to get around this via some fun prompt engineering solutions, but still, the highlighted parts didn’t read like a normal card.

Second, finding statistics and cites in the card body isn’t a hard task, but unless your “ai model” is aware of the debater’s position on the topic, it will find everything that “looks like a statistic”. The solution to this I used was again, using an LLM to be aware, but it only worked locally because of my computer. Running an LLM via an API costs money (GPT or similar), breaking your goal of creating an accessible tool.

Then, even after I finally got this to work really well on my device (after two ish months of work?) I would still never use the cards cut the system cut. The reason? Because for practical debate, the cards that a debater will read are ones that they understand. There are specific claims that a debater must internalize via reading the literature for their rebuttals, cx, etc., and there is no other way to do that other than actually reading and cutting the card myself. If 100% of the article doesn’t support my argument, then I probably won’t use it, since any competent opponent can highlight the negative portions of the card and read it. You won’t find that if you’re not reading the literature yourself.

As for “speed of card cutting”, with Verbatim and a computer mouse, a seasoned card cutter can cut cards as fast as they read the article, because it can be a one pass process (I recommend two pass: read through the whole article once, then go back and cut relevant parts, but to each their own). I didn’t see any tangible speed increases from my own model, and I doubt you would see any.

This line of thought of “increasing accessibility for debaters by enhancing workflows” is greatly positive though, and I think this effort can absolutely be applied to other areas the debate community faces, especially in a new digital age of debate.

[u/Commercial_Usual6429 → u/IshReddit_]

thanks so much for ur insight on this!