This Postplagiarism article was really interesting because it brought up some great points, some I agree with and some I disagree with. I think the conversation surrounding relinquishing control but not responsibility is really important. You can choose to use AI all you want, but at the end of the day you are responsible for the work you used it to produce. AI is not always accurate, nor is it unbiased. Blindly trusting it without ensuring that it actually aligns with what you are trying to say is dangerous. When fingers start pointing the defense “well AI said it not me” is invalid because it was incorporated into work that YOU produced therefore you are responsible for it. What I slightly disagree with is the fact that human creativity is not threatened by AI. Yes AI can be used to create the foundations for great ideas, but I believe that when one is dependent enough on it the ability to critically think is diminished. When you can´t come up with ideas on your own anymore it becomes a threat to the creativity that you once possessed. 

As someone whose native language is not available on google translate or any other online resource, I think Story Weaver is a great idea in theory. So many countries speak beautiful languages that, unfortunately, do start to die out throughout generations because they are “underserved” and “under-resourced”. I think StoryWeaver is a great idea in theory. Personally, I am still traumatized from AI read aloud apps thanks to the one we saw during our Childhood Development vs AI presentation, but I am not against it. I think if it´s done correctly it could be the life line for a lot of native and indigenous people whose languages are on the back burner. There are so many children and even adults who lack a connection to older people in their families because of language barriers and this is something that could rebuild connections within families, within cultures and even communities. I think if AI is going to continue to be shoved down our throats, this is something that might be worth opening ourselves up to. 

Reading Sarah Elaine Eaton’s piece on postplagiarism made me think about how fast schools are trying to hold on to old definitions in a world that has already changed. What stood out to me most is her argument that we may be moving into a time where plagiarism, at least as we have traditionally understood it, no longer fully explains what is happening. And honestly, that feels true.

For a long time, plagiarism was treated like something clean and easy to spot. Copy, paste, steal, submit. But AI has complicated that. Students are no longer always submitting something they copied word for word from a source. Now they can prompt, revise, remix, paraphrase, and turn in something that is technically “new” but still may not reflect their own learning. That is why Eaton’s idea of a postplagiarism world feels important. It forces us to ask a better question. Not just, Did the student plagiarize? but Did the student actually think? Did they learn? Can they stand beside this work and explain it?

That is the part that connects most to what I keep seeing in the classroom. I have said before that the problem is not just cheating. It is that students can hand over their thinking so quickly. AI gives them polished language, structure, and confidence before they have even wrestled with the ideas themselves. And then teachers are left trying to figure out where the student ends and the machine begins. Eaton basically says that may soon be pointless, and I agree. If hybrid human-AI writing is becoming normal, then chasing detection may be a losing game.

What I appreciated is that she does not just throw her hands up and say integrity is dead. She shifts the conversation. Humans may give up some control over the writing process, but they do not give up responsibility. That feels like the real issue. Students are still responsible for what they submit. Teachers are still responsible for creating assessments that make actual learning visible. Schools are still responsible for defining integrity in ways that make sense now, not twenty years ago.

I also found myself thinking about voice. Eaton says human creativity is not threatened, and I want to believe that. But I think what is threatened is students’ trust in their own messy process. The drafting, the struggling, the trying to find the right words. AI makes it very easy to skip over that part. And as someone who cares deeply about writing, that worries me. Because sometimes the point of writing is not just the final product. Sometimes the point is becoming the kind of person who can sit with uncertainty long enough to say something real.

Her point about attribution also stayed with me. I liked that she moves beyond citation as just a technical requirement and frames it more as respect, stewardship, and intellectual appreciation. That connects to so many larger conversations about whose knowledge gets valued, whose voices get cited, and whose ways of knowing are still pushed to the margins. If we are really entering a postplagiarism era, then maybe we also need a deeper conversation about knowledge care, not just rule-following.

The part that feels most unsettling, though, is the move toward neurotechnology and invisible forms of assistance. Once she got into brain-computer interfaces and implantable or invisible tech, I could feel the article pushing beyond AI as a classroom tool and into something much bigger. It made me think about how schools are always one step behind technology, constantly reacting instead of preparing. First online learning. Then AI. Next something even less visible, even harder to detect. Her point is not to be dramatic. It is to say that if we keep centering academic integrity around catching students, we are going to lose.

And honestly, I think that is already happening. The “arms race” language feels accurate. Schools keep trying to build better detection, students keep finding new workarounds, and somewhere in the middle the real question gets buried: what does ethical learning look like now?

For me, this reading confirms that we cannot solve AI by acting like the old framework is enough. We need to think beyond plagiarism as a simple rule violation and move toward bigger ideas of ethics, responsibility, authorship, and learning. Because in a world where students can generate polished work in seconds, the real issue is no longer just whether the words are original. It is whether the thinking is.

Reading 2

“An A.I. Translation Tool Can Help Save Dying Languages. But at What Cost?” made me sit with two truths at the same time. AI translation tools are powerful, and they are also complicated. On one hand, they can help preserve languages that are disappearing or not widely recognized. On the other hand, they depend on the labor, knowledge, and culture of real people who are often not being paid what they deserve.

What I really appreciated in this piece is how it shows the human side of this work. People like Sanjib Chaudhary are not just “data workers.” They are preserving their language, their history, their identity. That is meaningful work. But at the same time, being paid less than a cent per word for that kind of labor does not sit right. It raises a bigger question about value. If these languages are important enough to build AI systems on, then why are the people behind them treated as invisible?

This also made me think about my own classroom. These tools are not just important for “dying” languages. They are just as important for languages that are very much alive but do not get the same recognition in schools or in tech. Haitian Creole is a perfect example. It is widely spoken, culturally rich, and present in so many of our students’ lives, but when I use tools like Kami, it is not even an option. Meanwhile, there are features for translation and read-aloud in other languages.

So what does that say? It makes me wonder if companies are actually thinking about inclusion or just about what is most profitable or easiest to support. Have they ever hired someone who speaks Haitian Creole to build that into the platform? Or is it a matter of not wanting to pay people what their knowledge is worth?

In practice, teachers end up doing the extra work. Copying and pasting text into other tools, trying to translate materials, trying to support ESL students the best we can. And even then, it is not always done in the most effective way. In ESL settings, it is often better to have both languages side by side, like what StoryWeaver does, so students can actually learn and connect meaning across languages. That kind of thoughtful design matters, but it is not always prioritized.

What this article really pushed me to think about is value. How much is a language worth? How much is culture worth? How much is the knowledge of native speakers worth to these companies that are making millions off of AI?

Because at the end of the day, these tools do not work without people. They do not exist without the voices, translations, and lived experiences of native speakers. And while many people contribute to this work out of pride, preservation, and love for their language, that should not mean they are underpaid or overlooked.

If these companies are going to build systems using people’s languages and cultures, then they should also be willing to invest in those people. Not just in recognition, but in real compensation. Otherwise, it starts to feel like preservation on the surface, but exploitation underneath.

Week 11 Blog

With  the rapid evolution of technology and multiple A.I Translating Tools along the way, it’s easy to assume that access to these resources has reached everyone. However, this article has opened my eyes to the harsh reality that many of these languages are still underserved, and often excluded from these tools. Even though platforms such as Google Translate, one of the most widely used A.I. translation platforms, provide translations for over 243 languages, the fact remains that some languages are still left out. As a Bilingual Teaching Assistant, I often observe  how the students are able to translate their classwork assignments, and tests. I often reflect on my past experiences, and wonder how was I able to complete my assignments and even managed to test out of English as a Second Language (ESL) which is currently referred to as Multilingual Learners (MLs) without the assistance of any of these technologies. 

Fortunately, platforms like Story Weaver have taken the steps and made it possible not simply to translate simple conversation, for children to gain access to thousands of books they would otherwise miss out on, but also contributing to preserving languages that are at risk of disappearing due to their speakers being diminished. I also like the fact that human input is being used in the translation process, because I believe that humans are more accurate. I sometimes play with Google Translate just to analyze its accuracy, and I occasionally feel disappointed, because the translations often sound too robotic. Certain words and expressions are deeply rooted in the language culture, and only a person from that culture can understand and relay their specific meaning. The only downside in this situation is the issue of hard labor, and lack of  recognition. Whether as a volunteer, or employee, human translators invest a significant amount of time, and energy to make the mission possible. 

Adamari:​
“Howard (2000) proposed that plagiarism is “inherently indefinable” (p. 473), that it “eludes definition” (p. 474), and that we ought to discard the term entirely”. I feel like that is crazy to say. There is no way it can’t be defined. I think it can be simplified to not giving credit when using information from other people and passing off someone else’s work as your own. I think the examples define it well. I wouldn’t say it is indefinable, that is a little much. Even if you don’t fully know all the different things that fit under plagiarism, it still can be defined.

“There is no absolute or universally accepted definition of plagiarism. Cultural and contextual factors play a role in how we define and address misconduct.”Okay see this makes a little more sense. That some cultures see different things as plagiarism. But then, does respectful have a definition? Cultures have different ways of being kind and showing respect to each other. Can anything that involves what humans do be defined? I am asking the wrong questions, this isn’t really what the paper is about, but I think it is interesting to question definitions this way.

“The bounded nature of plagiarism definitions can serve as an impediment to deeper reflection about what it means to engage in ethical decision-making in and beyond the classroom. Academic integrity
serves as a foundation for ethical decisions at school, at work, and in life.” I guess so. Raising good people can start with academic integrity. Though sometimes you really are struggling with one section in a class and don’t want to fail, so you cheat because that one section was super hard. Doesn’t mean you will be a terrible person in life because you cheat once or twice. All the time, yeah you probably will suck as a human. I think there is a level to it. I also think cheating with AI is way worse than cheating back then. You had to be pretty creative and now it just takes quick searches. It is lazy now and way too easy. And doesn’t teach you anything at all. At least back then you learned how to be sneaky or something. Now it is so lame. Cheating now with AI makes you lame and lazy. I think cheating now will cause you to be lame and lazy in life, constantly using AI for things.

“Text generated by artificial intelligence tools is not static. It can be edited, revised, reworked, and
remixed. The result can be a product that is neither fully written by a human, nor by an AI, but one that is hybrid. Trying to determine where the human ends and where the artificial intelligence begins is pointless.” See this is why it makes you lame and lazy. I have forgotten to include this in my many yaps, but people CAN edit the AI junk they get. Which makes things funny. I have heard so many professors complain that they get the random “if you want I can do this to the prompt” type of AI stuff at the bottom of assignments. They are so bad at cheating they don’t even edit the bottom AI garbo. Back when I was in middle school and high school, when people cheated off of each other you heard the common “change the words around”. Sometimes you would hear a “I’m not an idiot, of course I am changing how things are said”. Maybe even a “I will get some wrong on purpose”. People were more creative with their cheats. Doesn’t make it right, but at least people knew to change things around. It is like people don’t even care if they get caught. They fully can change the words, use some of it but not all of it, yet they are so lazy it just gets submitted as a whole.

“This comes on the heels of numerous news stories about students being falsely accused of academic misconduct after teachers had used so-called AI textgeneration detection tools on students’ academic work.” This was a huge problem in the writing center, maybe still is. Entire classes were being failed because of it and they had to come to us. So many tutors had to sit and watch the students type and then send an email to the professor to prove it was done by the student and not AI. So much work for the students and tutors to prove that the kids didn’t use AI.

“Another tenet of postplagiarism is that human creativity is enhanced, not threatened by artificial intelligence. Humans retain their ability to be inspired and inspire others. We may even be inspired by artificial intelligence, but our innate human ability to imagine and create remains boundless and inexhaustible.” So we finally get some good news that humans will keep inspiring others. That is great to hear! I dislike hearing that we may also be inspired by AI. Except those people who are inspired to do AI things themselves. The people copying AI art and making it human is cool to me. Glad to know our future isn’t as doomed as we thought. Maybe still doomed, but not that doomed.

“Past generations have worried that technologies such as radios or smartphones would diminish our ability to think, but there is no empirical evidence to support such an assertion. There are complexities and nuances to human intelligence, creativity, and relationships that may never be captured by artificial intelligence”. That is a good point, that every generation thinks the next one is too different with their technology. However, I think this is the biggest jump. Answers were easier to get before than past generations, but now with the ChatGPT nonsense we are really in a tough spot. Brainrot is real guys. I see that the older generations were concerned about the same things, but this is a little bit crazier to me. And, it should be noted that the tech keeps advancing. Yeah sure they were concerned about sound machines (radios) impacting our thinking. But we got bots now so…

“Overcoming barriers and advancing equity are fundamental to postplagiarism precisely because ethics and integrity are of utmost importance”. I agree. It is nice to overcome barries but it should be done in the right way. Or in the best way possible. Nothing will ever go smoothly or to plan, but we can always try our best to not be rude rats. We should overcome barriers with ethics in mind and not just do it to do it.

“Humans can retain control over what they write, but they can also relinquish control to artificial intelligence tools if they choose. Although humans can relinquish control, they do not relinquish responsibility for what is written”. SO TRUE. Retweet. This goes to the editing thing. You have a lot of say in what you submit. The AI might give you the words, but you turn the assignment in. You press the submit, and that is no accident. You need to take responsibility for that. I think once people know about the dangers of AI it is on them if they use it. Bad on you of course cause it is terrible, you need to take some responsibility for it though. As you put the prompt into the AI, you copied, you pasted, you submitted. However, this is like a drug right. SO, I think higher ups needs to be blamed too. For making it easy access, open to all, in everything we use. It is on them too, not just the users, for some people out there aren’t aware of how bad it is. Not everyone is in our class.

“If students cannot demonstrate their own learning, then there may be reason to question whether academic integrity has been violated. In turn, educators have a responsibility to develop assessment tasks that
provide students with opportunities to demonstrate their learning”. I agree with this, though it is hard to get them to demonstrate their own learning. In my World Literature class here at Kean, my classmates said I was getting bullied by the professor. She was ON my case for my in person stuff being different than my at home stuff. She didn’t really give us any time to work on things in class, but at home I could get as much time as possible. I could also type at home, in class had to be done on paper. Every class she would come real close to my desk and talk to me about my work. This was before I knew about ChatGPT, so don’t think I cheated on my at home stuff. I would never, I love writing. But that is my point, that the students might work better in different conditions and that doesn’t mean they are cheating. People just work differently. I work better at home than I do at school. I hate working on things in the class, I prefer my usual work space at home. So, it will be hard to see if students have learned, for they might be so used to one setting and not the other.

“If history is any indication, when neuro ed tech arrives at our classrooms, it is reasonable to expect that neither educators, nor policy makers will be able to curtail or control its use, at least to the extent that they might desire.” Also very true. No one really knew what to do with AI for the longest time. I still think the rules are a little up in the air, it depends on the professor and the class. All of that is a little scary though, for this has shown there isn’t much stopping newer tech from taking the world by storm before people realize it is bad and have time to stop it.

Keslande:
“Users can explore the repository by reading level, language, and theme, and once they select a story, they can click through illustrated slides (each as if it were the page of a book) in the selected language (there are also bilingual options, where two languages are shown side-by-side, as well as download and read-along audio options)”. This sounds super cool. I think seeing the two languages at once could help some families that speak multiple languages.

“A.I.-assisted translation elements incorporated in digital libraries like StoryWeaver can bring more languages into conversation with one another—but the tech is still new, and it depends on data that only speakers of underserved languages can provide. This raises concerns about how the labor of the native speakers powering A.I. tools will be valued and how repositories of linguistic data will be commercialized.” A good point to make, that it depends on someone who speaks the language to help the translation elements. This makes me wonder if there are human errors or some things that can’t be translated well. I have always questioned how much could be translated. I don’t think cultural things translate well, like some stories that are unique to a culture or memes. There was a Star Trek episode on this (I was forced to watch for a class) that went over a culture that only spoke in references, so their universal translator “worked” but they didn’t understand since it was all unique references. Goes to my yap on discourse analysis, if a discourse has specific lingo it can be hard to understand if you aren’t in that discourse.

“Instead, it assists humans with hints in the language they’re translating into. For example, if you begin typing, “It is raining” in the target language, the model working on the back-end supplies “tonight,” “heavily,” and “cats and dogs” as options for completing your sentence, based on the context and the previous word or set of words.” So, like the AI things we have now. The auto completes on texts or emails. They just put that into the translation thing.

“However, both these sources—according to Microsoft’s researcher Bali—are too specific, and do not encompass a wide enough range in terms of topics and vocabulary to be properly representative of human speech. (This is why StoryWeaver isn’t a good source for training data, either, because sentences in children’s books are fairly simple and the reading corpus only goes up to fourth-grade reading levels.)” And there is one of the problems. It can’t do how people speak. It will cover the basic stuff I think but it won’t really cover the language. I think another problem with this is how people write stories isn’t how people speak. Story structures are different than everyday talking to people. I think that can play a factor in this too, that kid stories are told in a specific way and languages might not easily translate to that structure or format, or that the kids will learn the language in that kid story way but not the talking way.

“But they were paid only $243 for the project, or less than 1 cent per English word, divided three ways. According to Microsoft’s Bali, models need 100,000 paired sentences to start generating acceptable translations.” The other problem with this. The people aren’t getting paid well. Though, that is a problem that could be found anywhere. However, I think with the native speakers being so important to how this works, and that this is mostly for their kids or family, they should really work on getting the money they deserve for this project is nothing without their language.

“If our language dies, we will lose them. I want to collect these words before they disappear.” And that is the sad part about languages and cultures. If there aren’t enough people carrying it on, it goes away. And with how America is, making everything “American”, things get lost easily. On my father’s side, his great grandmother was fully Polish. Didn’t speak any English. She even lived in his house. But he doesn’t speak any Polish. As kids, my grandmother (his mom) would try to teach us very simple phrases. I don’t remember the like three things she told us. An entire language side of my family was gone so quickly because no one practiced or really taught anyone. Languages do die, and that is one of the very sad things about the world.