Students Not Turning In Homework Believe Masini Libre
Anastacia Iacono
The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.
In the United States, the best opportunity for reducing inequity is to improve education, particularly making sure that students succeed at math. The evidence shows that having basic math skills sets students up for success, no matter what career they choose. But achievement in math is going down across the country, especially for Black, Latino, and low-income students. AI can help turn that trend around.
Developing AI and AGI has been the great dream of the computing industry. For decades, the question was when computers would be better than humans at something other than making calculations. Now, with the arrival of machine learning and large amounts of computing power, sophisticated AIs are a reality and they will get better very fast.
I think back to the early days of the personal computing revolution, when the software industry was so small that most of us could fit onstage at a conference. Today it is a global industry. Since a huge portion of it is now turning its attention to AI, the innovations are going to come much faster than what we experienced after the microprocessor breakthrough. Soon the pre-AI period will seem as distant as the days when using a computer meant typing at a C:> prompt rather than tapping on a screen.
Although humans are still better than GPT at a lot of things, there are many jobs where these capabilities are not used much. For example, many of the tasks done by a person in sales (digital or phone), service, or document handling (like payables, accounting, or insurance claim disputes) require decision-making but not the ability to learn continuously. Corporations have training programs for these activities and in most cases, they have a lot of examples of good and bad work. Humans are trained using these data sets, and soon these data sets will also be used to train the AIs that will empower people to do this work more efficiently.
Company-wide agents will empower employees in new ways. An agent that understands a particular company will be available for its employees to consult directly and should be part of every meeting so it can answer questions. It can be told to be passive or encouraged to speak up if it has some insight. It will need access to the sales, support, finance, product schedules, and text related to the company. It should read news related to the industry the company is in. I believe that the result will be that employees will become more productive.
For example, many people in those countries never get to see a doctor, and AIs will help the health workers they do see be more productive. (The effort to develop AI-powered ultrasound machines that can be used with minimal training is a great example of this.) AIs will even give patients the ability to do basic triage, get advice about how to deal with health problems, and decide whether they need to seek treatment.
Similarly, governments and philanthropy should create incentives for companies to share AI-generated insights into crops or livestock raised by people in poor countries. AIs can help develop better seeds based on local conditions, advise farmers on the best seeds to plant based on the soil and weather in their area, and help develop drugs and vaccines for livestock. As extreme weather and climate change put even more pressure on subsistence farmers in low-income countries, these advances will be even more important.
Today I got accused by my professor of cheating and copying two reports I submitted. I had a formal meeting with the professor where he tried to push me into admitting I cheated by showing me the surprising similarities. Even though I continuously denied it, he went forward to go to a formal hearing in the university where a panel will judge the outcome. I am currently freaking out. I know I did not cheat from anybody and I feel like the similarity could be due to a similar thought process (which sounds ridiculous). Should I just say that I did not cheat and stick with it? Or should I ask if I can redo the reports (though it sounds suspicious)? The reports were 68 percent similar and I feel like the odds are against me even though I did not do anything.
Edit: the software used was turnitin and I do not hav access to the original files to get time stamps. I literally can only deny the allegations. The only reasonable explanation is that the professor taught us in a similar manner and our report writing manner was similar due to the fact we have taken the same courses a year apart and had the same professors who molded our report writing skills.
Offering to redo the reports won't work unfortunately - at this point, it's about academic integrity, not about the grade you get. It's likely advisable to get advice from someone familiar with your department and the academic integrity process, e.g. a faculty member you trust, or student counselors if available.
Firstly, use version control. It's quite likely that you've produced your report in either MS Word, Libre Office or Google Docs. All of these programs store old revisions, although Google Docs stores all of the revisions while Word and Libre Office only a limited number. If you're able to produce evidence of partial work, it'll be clear you've produced the report yourself instead of copying it from previous work.
See for example -office/word/view-older-version-word-2016-document/ for accessing old versions of a Word document. Warning: only a limited number of revisions are stored, so don't save the document again as it will overwrite the oldest versions! If you exported your work as a PDF multiple times, look in the Trash Bin - there may be additional files there.
If you used LaTeX, you might have to use a digital forensics program, such as Autopsy, to recover deleted PDFs and scrub through a sea of deleted documents it recovers to find a previous version of this document.
Secondly, remember that you're innocent until proven guilty. It's the professor who needs to convince the panel that you cheated and not the opposite. Do not accept the professors framing of the situation.
I've read the above answers, and they seem to give pretty good advice, but I have some more for you that isn't about procedures of college, but on personal etiquette and experience when being questioned by those who have authority.
When you go into this, have your facts ready, and find some way to keep your calm. If you are freaking out as you say, this can easily be misconstrued as acting in a guilty manner. When you are in front of them, treat it like a soldier would at a military board. Listen to their questions carefully, do not interrupt them, answer their questions truthfully, support your statements if possible, and correct any inconsistencies in their facts as you find them.
Also, remember, if one of them yells first or gets upset, you've won the argument. You kept your cool, and now have a means to attack their argument, or show that it is not logically sound, but emotionally driven.
Find an advocate to support you. Some universities have an office (ombudsman) for this. In other places a student organization provides help. You may even need a lawyer if you are able to afford one. Another professor who trusts you might be able to help.
Papers were similar. It happens. I assume that whoever did the previous work had the same teacher, with the same lectures, and the same written materials (books, etc). Students were actually encouraged to think in a certain way.
68% similarity is a high number, and unlikely to happen by pure coincidence. I suggest you examine your process of writing your lab reports with a fine tooth comb, and be ready to convey this process to the hearing board.
In preparation for the hearing, you should ask for the document which you are accused of copying in order for you to prepare. As I said, 68% is a high number, but there could be explanations. For example, if both papers cite the same sources, then the citations in the bibliography could boost the similarity percentage, and the prof did not examine the similarities carefully enough to see this issue.
Another possibility is that you didn't copy the older lab report, but that both you and the student who wrote the old report used the same sources for their preparation, and there was insufficient citation of the sources you used. In this case, both you and the student you're accused of copying from plagiarized from the same source, and the hearing board will likely still find you responsible for a violation of an honesty policy.
If this is the case, and you insufficiently cited the same sources that the other student used, I'd encourage you to have the information in-pocket for your hearing. There is subtle difference between finding an old lab report and copying it, or boosting text from a wikipedia listing without citing it, because you don't understand how to do it correctly. Both are violations, but convey different intention and might differ in terms of severity.
You may also be faced with whether the two reports are treated as TWO violations or pooled together as one violation. If the case is improper citation, and not copying from an old report, you might ask for some mitigation of penalty for the second offense, as it would have been dandy if the prof could have identified your issue before you repeated it.
I am a professor. Even if you don't have any "hard" evidence that you wrote it yourself, one thing that would be convincing to me, if I was on this committee, was that you knew the material you handed in. E.g. you could take an oral exam on the material. So, make sure you really know what you handed in and why you wrote it the way you did.
And you tell them: Yes, it's extremely likely if you're looking at just two report-writers. But in both this and the previous semester we had at least n students taking this lab; so actually, we have n * n pairs of students. And whenever some pairs of students all have non-similar reports, that only increases the probability of the remaining pairs to produce similar reports. Thus the probability of finding at least one pair of students with similar reports is in fact much much higher.
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