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Chat GPT stands now as one of the most used generative AI tools on the planet. Its reach encompasses all classes; from students in their schools to even the labor force in their places of work. Nevertheless, this broad use of Chat GPT technology comes with its downsides. AI-generated texts are being used more and more for writing on social platforms such as Reddit, Facebook, and Twitter. Because of the rising cultural reliance on information and online contact, fraudulent actors have emerged that utilize Chat GPT to produce and disseminate messages on these platforms while propagating misinformation and disinformation (Najee-Ullah et al.,2022). The case that stands out the most is within the context of education. Nowadays, in the majority of schools of the world students are using for the first time Generative AI to complete written assignments and in some cases even online exams if the proper security methods are not applied by the institution.

In this context, I wanted to provide my personal experience as well. Before coming to Rotterdam to pursue my master’s in information management I met a student (whose identity I won’t reveal due to the content of this story) who completed his Bachelor’s Thesis in International Business by using (I’m marking his words) Chat GPT to complete 80% of his final university assignment. Later, I was told that he was successful in passing his thesis and obtained a moderate but enough 6 as his final grade.

Surely, this might come as a surprise since Maastricht University (the one where my friend was studying) just like any other university currently has in its arsenal various anti-AI plagiarism tools to avoid such situations (Akram, A, 2023). Marveled, by the outcome I asked him how he managed to accomplish such a result and not be detected. The answer was simple. He told me that he used what he called the “Laundry” process. This process consists of inputting texts in AI paraphrasing tools repeatedly in order to “clean” the texts as if they were clothes. The result is a text completely undetectable by anti-AI plagiarism tools.

I decided to put it to the test by asking Chat GPT to answer our first preparation question of the Information Strategy course situated in Module 1. The result is the following text: 

As you can observe in the image, I have only asked for 125 words since the paraphrasing tools that I will later use for the “Laundry” method only allow you to input 125 words if you don’t want to pay the premium version.

Then I decided to input the text, which answers our first preparation question, into 2 of the most known and effective free anti-AI plagiarism tools in the market (Izzo, 2023). These ones are Winston.AI and GPT Zero. The results are the following:

As you can see in the two images above, the results are according to the expectations. Both tools detect a generative AI being used. Winston.AI confirms it with 100% probabilities and GPTZero with 60% probabilities, a quite solid number.

But now I’m going to start the “Laundry” procedure. For this blog article, I utilized the following paraphrasing AI tools in the following order: (1) Using QuillBot in the initial answer text produced by ChatGPT (2) ahrefs paraphrasing tool on the previously paraphrased text (3) re-paraphrasing with paraphrasing.io (4) Repeating another QuillBot paraphrasing (within this tool this method works better if you paraphrase one sentence at a time instead of the whole text) (5) Prepostseo paraphrasing tool in “Fluency” method (6) Last Quillbot (8) Finish with Grammarly suggestions.

The result of all these operations applied to the initial answer provided by ChatGPT on our preparation question 1 under session 1 is the following new text:

Now it is time to repeat the anti-AI plagiarism test with the same exact tools used previously (GPT Zero and Winston.AI). The results are the following:

As you can see the results are shocking and they confirm the “Laundry” process. For Winston.AI the text has a 95% probability of having been written by a human. On the other hand, GPTZero has a low 20% probability of having been written with the help of a Generative AI tool such as ChatGPT. Surprisingly, 20% is also the limit benchmark for many universities currently on their plagiarism policy.

In light of the above mentioned, in this blog post, it could be seen that Generative AI tools and more concretely Chat GPT cannot be fully controlled. The process of hijacking the anti-AI plagiarism detectors has resulted to be quite easily with the utilization of other generative AI paraphrasing tools. Thus, further raising awareness for the ethical implications of generative AI can suppose in contexts such as education, since as of now cheating with generative AI is an easy path to follow.

References:

‌ Akram, A. (2023). An Empirical Study of AI-Generated Text Detection Tools. Adv Mach Lear Art Inte, 4(2), 44-55. 

Najee-Ullah, A., Landeros, L., Balytskyi, Y., Chang, SY. (2022). Towards Detection of AI-Generated Texts and Misinformation. In: Parkin, S., Viganò, L. (eds) Socio-Technical Aspects in Security. STAST 2021. Lecture Notes in Computer Science, vol 13176. Springer, Cham. 

Izzo, V. (2023, May 22). Best Plagiarism Checkers For AI-Generated Content. WordLift Blog. https://wordlift.io/blog/en/best-plagiarism-checkers-for-ai-generated-content/

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During the Covid-19 pandemic, me and my tiny group of international friends decided to stay in Maastricht instead of going back home to our respective families. At that moment, we decided to start getting serious about playing Chess out of boredom. More concretely, we all started playing in Chess.com which is one of the most famous apps for playing chess all around the world. The app has as its members some the most famous personalities in the chess community. Ding Liren, Hikaru Nakamura, and even Magnus Carlsen who is considered the best player in history are amongst them.

After loads of practice, I started becoming better and better at chess. Within Chess.com a variety of functionalities can be played. Such as 10-minute games (rapid), 1-minute games (bullet), or even 1+ days games (diary). But amongst all of them, I grew a particular interest in puzzles.

In Chess a puzzle is the scenario that occurs when a player is presented with a completely random position in the board where one and only one good move exists. These puzzles demand more than simply moving pieces across a board; they also call for ingenuity, problem-solving abilities, and awareness of intricate patterns (Generating Chess Puzzles with Genetic Algorithms, 2022). Every time a player succeeds in completing a puzzle within Chess.com your rating (Elo) increases but if you get it wrong it decreases. An Elo is basically a renowned system in which the overall strength of a chess player is expressed. You can see in the image below my Elo rating in puzzles. This one is considered as medium-high in the chess community (2036) and I’m also currently positioned in the 96,8 percentile of all Chess.com players doing puzzles.

Nevertheless, as you can see in the graph my rating (Elo) progression in puzzles has stagnated. One of the main factors for that is that I keep encountering very different puzzles in terms of thematic which are not appropriate for my characteristics as a player. What I mean by that is that Chess.com doesn’t provide me with a tailored training plan for completing puzzles. For example, If I’m struggling with end-game situations (when there are not a lot of pieces on the board) Chess.com should constantly provide me with variations of those end-game puzzles until I understand their intrinsic dynamics. Instead, because puzzles in Chess.com are primarily curated from real games played by humans in the app, this one just provides me with random puzzles that are considered to be in my current level of difficulty or Elo. But it doesn’t tailor them by thematic or player personal needs and weaknesses. In other words, a huge stack of puzzles is stored in the Chess.com database and later sent to all players going through puzzles. Currently, there are more than 570,000 puzzles stored. Chess.com also increases daily its puzzle database by means of an algorithm that “walks” the positions in all the games played within the app until it finds a position that can be thought of as a tactical puzzle. (Team (CHESS.com), 2023)

The integration of generative AI could open new possibilities for puzzle creation and customization, ultimately enhancing the learning and training experience for chess enthusiasts of all Elo levels. As a chess enthusiast, I could benefit greatly from these generative AI tools. They could allow me to practice and improve my game by offering personalised challenges and insights. More concretely the use of generative AI for the puzzle games could provide: (1) More customised puzzles tailored to individual player’s preferences, and weaknesses or areas for improvement. (2) Infinite puzzle variations which would be generated by generative AI based on each player’s style of play, so there would be no need to rely on a limited database (3) Specific aspects of chess and skills would be targeted, such as tactics, endgames, opening positions, etc. (4) Generative AI applied to puzzles in Chess.com could also adjust difficulty more dynamically per subject instead of by Elo, consequently ensuring that players are continually challenged and motivated to progress.

Nowadays, generative AI has already been used within the realm of chess. The introduction of generative AI in Chess was demonstrated with Alpha Zero. An AI that generated new playing positions and forms of understanding the game never encountered before. Therefore, if generative AI was already applied in Alpha Zero, why cannot it be implemented within the puzzles department of the renowned application Chess.com? Why cannot generative AI be used to create new puzzles tailored to each individual player’s needs and that at the same time showcases originality while still adhering to the strategic foundations and aesthetic allure of chess? (Generative AI in the Chess World, n.d.)

Considering the above-mentioned, Chess.com, the prominent platform for chess enthusiasts, could integrate generative AI to enhance user experience. Through AI-powered analysis and puzzle generation, Chess.com could assist players in improving their skills. It could provide tailored puzzles based on a player’s past mistakes and style of playing while continuing to be delivered according to a player’s level in terms of difficulty or Elo level. All in all, generative AI tools could be used to augment the puzzle creation process based on an individual’s gameplay such as in the case of Alpha Zero.

REFERENCES:

Generating Chess Puzzles with Genetic Algorithms. (2022, October 13). PropelAuth Blog. https://www.propelauth.com/post/generating-chess-puzzles-with-genetic-algorithms

Team (CHESScom), C. com. (2023, January 10). How We Built A Puzzle Database With Half A Million Puzzles. Chess.com. https://www.chess.com/blog/CHESScom/how-we-built-a-puzzle-database-º     with-half-a-million-puzzles#:~:text=Our%20database%20of%20puzzles%20has

‌Chole, V; & Gadicha, V. (2020). A review towards human intuition based chess playing system using AI & ML. Turkish Journal of Computer and Mathematics Education Vol.11 No 2 (2020), 792-797

Generative AI in the Chess World. (n.d.). Sigma Technology. Retrieved October 21, 2023, from https://sigmatechnology.com/articles/generative-ai-in-the-chess-world/

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