My Experience with AI-Assisted Writing: Chronicles of a First-Time Author

As I sit down to write my book, I find myself questioning my own understanding of writing itself, working on a piece of work out of my mind and thinking about the whole authorship concept, just after the first spark, the very first introspective moment of creativity triggered by what I describe, with a smile in my face, a new child toy and reflecting on the act of creation and the concept of authorship.

?

Why did I decide to use a computer-aided writing (CAW) tool like ChatGPT, and actually call it this way, as an assistant in the writing process? Am I still the true author of this work, or does the use of technology somehow diminish my role as the creator? This introspection was sparked by memories of a book I read in my teenage years, "The Story of Philosophy", by Bryan Magee, which combined elements of philosophy and history in a way that deeply resonated with me.?

?

So, what is my role as a writer and the potential to explore this technology in enhancing my own abilities and creativity as an author, a first-time book writer?

?

These questions led me to explore the different perspectives on authorship throughout history, from the classical Greek concept of "divine inspiration" to the modern focus on the individual who physically creates the work. And I realized that my use of CAW tools, such as ChatGPT, as an assistant in the writing process is not that different from the collaborations that have always existed in the creation of art and literature.

?

I am still the one who physically creates the work, making decisions on the content and meaning of the work, and the AI is just a tool that supports me in the process but has no consciousness. It is important to note that AI does not replace my role as the author, but rather enhances it. This is, in a way, inspired by the classical Greek view of authorship as a gift from the gods, as AI gives me access to a new level of creativity and efficiency.

?

In the classical Greek concept of authorship, the focus was on the individual, who possessed the gift of genius, rather than on the physical act of creating the work. In this context, a writer without arms who used a pupil to write, or a sculptor without arms who used an apprentice to sculpt, could still be considered the author of the final piece produced, as long as they possessed the gift of genius and were the source of inspiration for the work.

?

I know that this concept of authorship was not universally held in ancient Greece and there were debates about what it meant to be an author and who should be credited for a piece of work, especially through time.

?

The work of art, its expression in a certain context, and its interpretation by the performer are all closely related concepts that are essential to understanding the full significance of a piece of art.

?

A work of art is the creative output of an artist, whether it be a painting, sculpture, performance, or another medium. The expression of the work is how the artist chooses to convey their message or idea through the work. The context in which the work is presented also plays a crucial role in shaping the expression and meaning of the work.

?

For example, the modern interpretation of the work by the performer, in the case of a musical composition, is also an important aspect to consider. The performer brings their own interpretation and personal touch to the work, which can greatly influence how the work is received by the audience. But let's get back to the classic concepts, and writing.

?

Ancient Greek society was very different from ours, making it hard to draw a direct comparison, but so is the modern concept. In modern authorship, the primary author is generally considered to be the individual who physically creates the work, for example, the book writer. However, I acknowledge and value the contributions of editors, reviewers, and proofreaders as they play a role in the final product. They are not considered co-authors of the book, and this is well-accepted nowadays.

?

The concept of co-authorship is typically used to refer to situations where multiple individuals have made significant intellectual contributions to a work and are listed as authors on the final product. For instance, when multiple researchers collaborate on a scientific paper, they may all be listed as co-authors. However, this is different from the role of editors, reviewers and proofreaders, who are usually seen as supporters or collaborators of the author.

?

This can take many forms, from a group of writers working together on a novel or screenplay to multiple researchers collaborating on a scientific paper. Co-authorship can provide several benefits, such as the ability to pool resources and expertise, as well as the potential for a wider range of perspectives and ideas.

?

Creative collaboration refers to the process of working together to generate new ideas, solutions, or products. This can take many forms, from brainstorming sessions to joint artistic projects. Creative collaboration can provide many benefits, such as the ability to generate new ideas and solutions, as well as the potential for increased creativity and productivity.

?

In traditional writing processes, co-authorship and creative collaboration typically involve face-to-face interactions between writers, editors, and other team members. This allows direct communication and the ability to provide feedback and make revisions in real-time. However, this process can also be time-consuming and may not always be feasible, particularly when working with writers in different locations.

?

With the emergence of new technologies, such as computer-aided writing (CAW) and AI-generated content, the process of co-authorship and creative collaboration is changing, and the use of a CAW tool, such as ChatGPT, could be considered similar to the contributions of editors, reviewers, and proofreaders in modern authorship.?

?

I use CAW tools to assist me in generating text and providing suggestions for wording, structure, and style, but the final decision on the content and meaning of the work is still made by me, the human author.

?

In this sense, CAW platforms are considered a tool that plays a role in the final product, but not as a co-author.?

?

I, the human, am still the primary author who physically creates the work, and the use of a CAW tool is acknowledged as a support in the writing process.

?

These technologies have the potential to automate certain aspects of the writing process, such as editing and proofreading, and may allow for more efficient and cost-effective collaboration between authors and other team members. However, these technologies also raise new ethical questions and dilemmas related to authorship, authenticity, and intellectual property rights. Now, 25 years after the publication of "The Story of Philosophy", by Bryan Magee, we are facing a new era when history is being written live and fast, transforming the human path, and we need to consider how to navigate these new challenges and ensure that authorship and ethics are properly acknowledged and discussed.

?

One of the main ethical questions related to authorship is determining who should be credited as the author of AI-generated content, if solely considered. In the case of CAW tools, the AI algorithm is responsible for generating the output content as an algorithm response, but the human user is responsible for providing input and making decisions about the desirable output content. For some people, determining authorship in these cases can be complex and may require a re-evaluation of modern notions of authorship, going back into classic approaches to building a new doctrine that guides us in understanding and addressing issues related to authorship, authenticity, and intellectual property rights.

?

Another ethical question related to authorship is determining the level of creative control that should be given to AI algorithms. While AI algorithms can generate content that is similar to human-written content, they cannot make intentional creative choices. This raises questions about the authenticity and originality of AI-generated content.

?

The use of AI algorithms in the creation of content also raises questions about intellectual property rights. In some cases, the AI algorithm may be considered the creator of the content and entitled to the same intellectual property rights as a human author. However, in other cases, the human user may be considered the creator and entitled to the rights.?

?

Determining the ownership of AI-generated content, itself, in parts or the whole output, as assistant or primary generation output, can be complex and may require new legal frameworks, as it is a new chapter being written, a blank canvas.

?

Additionally, AI-generated content may perpetuate and amplify societal bias present in its training data, this raises ethical questions about the implications of AI-generated content, particularly in fields such as news, education and healthcare, and many others.

?

GPT is an acronym that stands for "Generative Pre-training Transformer". It is a type of an artificial-intelligence model that has been developed for natural language processing tasks, such as language translation, text summarization, and question answering.

?

GPT models are based on the Transformer architecture, which was introduced in a paper by Vaswani et al. in 2017. The paper, "Attention Is All You Need," described the Transformer model, a neural network architecture that uses self-attention mechanisms to process sequences of data, such as text. GPT models are built on this architecture and use a similar approach to generate human-like text.

?

As part of any machine learning, there is a training or learning phase and testing. Machine learning is a way for computers to learn and improve by themselves, without being explicitly programmed.?

?

Imagine you are learning how to play a new video game. First, you have to practice, or "train," so you get better at the game and know how to play it well. This is like the machine learning part, the training where actually the learning happens. Then, you have to test it yourself to see if you really understand the game and can play it correctly. This is like the testing part of machine learning. The computer in the case of CAW using AI is like a student who is learning how to write and speak like a human, and it needs to practice and test itself to make sure it is doing a good job.

?

So, to study, it uses a technique called pre-training, in which the generative model is first trained on a large dataset of text in order to learn general language patterns and structures.?

?

Once the model has been pre-trained, it can then be fine-tuned for specific language tasks by providing it with additional training data and adjusting the model parameters, then preceding the test and output as a result of a testing prompt.

?

GPT models have achieved state-of-the-art results on several natural language processing benchmarks and have been widely used in a variety of applications, and this is the AI tool I used in this work, via the chatGPT interface.

?

It can be difficult to determine with certainty whether a text was written by a human or a machine, such as the language model I employed here. However, there are a few clues that may indicate that a text was written by a machine, as they have a lack of errors, machine-generated texts tend to have fewer errors, such as spelling or grammatical mistakes, compared to texts written by humans, before any revision. During my journey as a first-time writer using CAW, I could see that, many times.

?

Another big aspect of the output regardless of the prompt is the repetition. Machine-generated texts may repeat certain phrases or ideas more frequently than texts written by humans, a recurrent redundancy, a lot of noise and a little of a new signal.

?

Sometimes you can feel a lack of nuance, some texts may lack the subtlety that is often present in texts written by humans, as machines may not be able to fully understand, yet, the context and meaning of certain words and phrases especially with outstanding creation above average common sense, having a uniform tone, as they may not be able to convey different emotions or tone as effectively as a human unless asked otherwise in the prompt, but even emotions in prompted outputs are kind of more uniform than true human emotions expressed in writing.

?

Language models are constantly improving, and they are becoming increasingly difficult to distinguish between machine-generated and human-generated texts, which gets even more difficult when compared with average human writing, a common sense as a control volume.?

?

However, with the state of the art by now, at the moment I'm writing this, those clues above may help identify whether a text was likely written by a machine or a human.

?

The language model does not have a specific "text signature" that can be used to track its output, some algorithms are running, imposing a fingerprint for a chatGPT output with low confidence and high error, so yet this is true.?

?

Language models are designed to generate human-like text based on the input and parameters that are provided to them. They do not have a specific identity or personality, and their output is not tied to any particular individual or entity, and this is one of the starting points for the new approaches.

?

But, let's look into the human creations themselves, there might have been many examples of texts, paintings, manuscripts, and drawings that were not attributed to a known author during their lifetime, but were later identified as the work of a specific individual based on stylistic traits that can be considered as a kind of "fingerprint" of the artist.

?

For instance, in the field of literature, the discovery of unknown works by famous authors, such as Shakespeare, J.R.R. Tolkien and Jane Austen, which were found in archives and private collections, have made headlines in recent years. Similarly, in the field of art, many previously unknown paintings by famous artists, such as Van Gogh, Monet, and Rembrandt, have been discovered and attributed to them based on the artist's unique style and technique.

?

Manuscripts and drawings are similar, many of them have been found in ancient libraries and private collections, and they have been attributed to famous authors and artists based on their expected signatures.

?

These discoveries have been of great importance to scholars and researchers, as they have provided new insights into the lives and works of these famous authors and artists and have also enriched our cultural heritage.

?

An author might use a pseudonym or a pen name before they become well-known, or they might create something and forget about it, only for it to be discovered later without any identification, and many works of art have been found in attics or storage rooms and attributed to an artist based on their way to make and create, even though they were never signed or identified by the artist. If we can do it, it's also possible and expected to do the same when considering some levels of authorship assisted by a CAW tool.

?

And here is the “Infinite Monkey Theorem”, which is a mathematical concept that states that a monkey randomly typing on a typewriter, for an infinite amount of time, will eventually produce a specific text, such as the complete works of William Shakespeare. The theorem is often used as a metaphor for the concept of random chance and the likelihood of unlikely events occurring over a long enough period. It's also used to demonstrate the concept of "computational irreducibility" or "algorithmic randomness", meaning that certain processes or systems cannot be simplified or predicted, even with an infinite amount of computational power or time.

?

Could the Infinite Monkey Theorem also apply to AI-generated text, given an infinite amount of time and data? Could an AI eventually produce a remarkable form of literature or poetry, similar to one of a human author?

?

In my opinion, the concern here is all about it, since it's almost impossible to get a remarkable form out of pure randomness. When you have some kind of output from AI resembling a remarkable form, the only possible explanation is bias. While the possibility of an AI producing a remarkable form of text through the application of the Infinite Monkey Theorem is intriguing, it raises several ethical and authorship concerns, AI algorithms may not only perpetuate and amplify societal bias present in its training data, leading to the dissemination of inaccurate or harmful information and also generate an output so close to a remarkable form and at the same time so "unique" that we are going to need to review our plagiarism concepts and leaving to the author who uses a CAW to take total control of the situation and the responsibility to check and confirm every output.

?

As trained on large datasets of text, their output is based on the patterns and structure of language that they have learned from this training data, a circular routing. As a result, the output of a language model may be similar to that of other language models that have been trained on similar datasets. However, it is not possible to track the output of a language model or identify it specifically based on its text alone, a context felt missing.

?

Despite not having a specific identity or personality, language models are able to generate a wide range of text on various topics and in different styles.

?

One of the benefits of using a language model is that it can generate text quickly and accurately, without the need for human intervention. This can be useful for tasks that require a large amount of written content, or for situations where it is not practical or feasible for a human to write the text.

?

However, it is important to keep in mind that language models are not perfect, and they, at least now, are not able to fully replicate the creativity (or will ever be?) and nuance of the human-generated text. They may also produce errors or inconsistencies, and they may not always understand the context or the intended meaning of the text they are generating.

?

Despite these limitations, language models have the potential to greatly improve the efficiency and accuracy of various text-based tasks, and they will likely continue to play a significant role in the field of artificial intelligence in the future.?

?

As technology continues to advance, language models will likely become even more sophisticated and capable of producing text that is more closely aligned with human language and thought, as pupils from a writer without arms or an apprentice to sculpt a masterpiece described by the genius with the antique divine inspiration, the true author.

?

Artificial intelligence does not have the ability to create original content or to hold any legal rights as an author. It is simply a tool that can assist in generating text based on input and instructions it receives.

?

If artificial intelligence is used to generate text, the output will be a combination of the input and instructions provided and the knowledge and abilities it has been trained on. In this case, the user would be the author of the output text, as they would have played a significant role in shaping and creating it.

?

It is important to remember that, while artificial intelligence can assist in the writing process, it is ultimately up to the user to ensure that any text that is generated is accurate, appropriate, and properly attributed to its sources.

?

Artificial intelligence has become an increasingly useful tool in the field of language processing, with applications ranging from text generation to translation and summarization.?

?

The ultimate responsibility for the accuracy, appropriateness and proper attribution of the generated text lies with the user who prompts.

?

In addition, it is important to properly attribute any text that is generated by AI to its sources.?

?

This includes acknowledging the contributions of the AI system, as well as any other sources of information or ideas that have been used in the creation of the text, as references included in the training dataset. Failing to properly attribute text can result in issues of plagiarism and intellectual property infringement, which can have serious consequences, but sometimes even the nature of the training dataset is uncertain to the AI who runs the model, the problem of a deadlock when you try out a test using a training group, it's all noise.

?

Overall, while AI can be a useful tool in the writing process, users need to remember that they have a responsibility to ensure the accuracy and appropriateness of the generated text.

?

As the use of these technologies becomes more prevalent, it will be important for society to consider the ethical implications and develop new frameworks for addressing these issues. It will be important for the legal systems, academics, and industry experts to collaborate and come up with a common understanding of how to approach these issues.?

?

Furthermore, it will be important for companies and organizations using CAW and AI-generated content to be transparent about the use of these technologies and to consider the ethical implications of their use, a whole new level of compliance.

?

Ghostwriting is a common practice in the publishing industry and is generally considered acceptable as long as it is done ethically and transparently. When a human ghostwriter is used, there is typically a clear understanding of the authorship of the content and the process by which it was created, again acting merely as a tool but quite never as co-author.?

?

Using a ghostwriter without disclosing it to the audience can be considered a form of deception, as it leads readers or consumers to believe that the content was written by the credited author, when in fact it was written by someone else.?

?

This can lead to confusion and mistrust when the truth is eventually revealed and may also raise questions about the authenticity and credibility of the content, but only when revealed, before that is a great mystery, not to say a great lie. Additionally, it could be considered as a breach of the intellectual property rights of the ghostwriter, as they are not being acknowledged as the true author of the work unless authorized otherwise, turning into a real nameless ghost.

?

On the other hand, using AI generative text is also a form of deception if it is not transparently disclosed to the audience. I feel that way and deciding to write this is the fact that I'm not only fully disclosing but also describing the feeling and experience of the process.?

?

However, the main difference is that AI-generated content is created by an algorithm rather than a human, and the ethical and legal issues surrounding authorship and intellectual property rights are different, not even properly discussed yet.?

?

Again, the use of AI-generated content raises questions about authorship, authenticity, and intellectual property rights, as previously discussed, and companies and organizations need to be transparent about the use of AI in the content creation process so that readers and consumers can understand how the content was created, and also to ensure that the content is being used ethically and responsibly.

?

In both cases, transparency is crucial in order to build trust with readers and consumers and to ensure that the content is being used ethically and responsibly. Transparency also allows readers and consumers to understand the creative process behind the content and make their own judgments about its authenticity and credibility.?

?

I'm not here to say what is written or wrong, I'm here to state that and leave it to the crowd to make their own judgments of it.

?

The idea of transparency concerning computer-aided writing (CAW) was one inspiration for my book "Indestructible Commitment: deliver the best speech of your life every day", which is a passionate project of mine. I have always been interested in public speaking and I wanted to create a resource that could help people understand and improve this important aspect of their lives in an informative way.

?

When I first discovered ChatGPT and the advancements in GPT-3, I was excited about the potential for this technology to improve my writing process. However, one of the first things that came to mind was the potential for this tool to be used without transparency and even hidden from the audience.?

?

As someone passionate about technology, I was determined to use ChatGPT and GPT-3 ethically and transparently. I wanted to ensure that the content generated by the AI was clearly labeled as such and that readers and consumers could understand the creative process behind it.?

?

This approach helped me to build trust with my audience and to ensure that the content was being used responsibly and ethically as inspiration for more authors to do so, leading a trend to be, soon.

?

So here is part of the creative process and challenges I faced during the writing process.

?

I started writing this book many years ago, actually, I outlined everything that should ideally be in this book during my career. The first step was to get this out of the way, starting some short sentences about each point and expanding.

?

Then, on December 26th, after a week deeply immersed into ChatGPT, I started to write effectively, driven by the desire to make this book come true.

?

The point here was that I'm used to some computer-aided tools, such as CAD for drawing, when I first asked some friends, colleagues and professors about the use of CAW without demoting authorship the very first answer was: "AI should be considered a co-author", and immediately, after this answer, I questioned them: "How about a drawing using CAD?", and the discussion started.?

?

At that point, many other branches opened in every single discussion, such as "are we talking about a continuous or discrete space?", "what are we accepting as output?", "does the AI have consciousness or is it just an algorithm that serves the author based on the author's prompt?

?

And here is the "click", the "WOW" moment. It is an unexplored field, and I love it!

?

We must go deep and understand ethics, the concept of genius, author, art and many other concepts and include the generative AI composition into this matter now, and my point of view is all about an iterative process, a back-and-forth game between the author and the AI, and think that AI will return to you as an output of the best high-level common sense possible, about every prompt you use.

?

I also asked them about the use of "grammar correctness" and "autocomplete writing suggestions". People are used to it, such as Google Docs, MS Word, and regular writing tools. Well, if you accept the suggestion of a grammar checker or autocomplete, what this means is that you are already using a computer-aided writing tool for minor uses.?

?

We can go deeper into this and see, for example, a translated version of a book, not done by the authors themselves but by some professional translators, is the output an absolute and unequivocal text fully written by the author in the original language? You can go far into this point and see that the author, in this other language, never wrote or said a single word, and we accept that as full authorship with just a small credit for the translator. How about an AI translator?

?

Let's get back to the CAD example. Consider authorship using Computer-Aided Writing (CAW) for iterative text composing and the use of Computer-Aided Design (CAD) for a drawing share some similarities in that both are tools that assist the creator in the creative process, rather than fully generating the final product. So, we must pay attention to the nature of the creative process, the level of human intervention and creative control, and the final product.?

?

There is a difference between text composing and drawing, but the output in both cases is a result of the prompt input.?

?

In both cases, authorship and intellectual property rights raise similar ethical questions, as the final product is a collaboration between the human creator and the technology. It is important to be transparent about the use of the technology and to ensure that the rights of any human authors involved in the process are protected.?

?

But I don't see any engineer or architect that I talked to denying the authorship from a drawing made with CAD, but all of them have issues with CAW. The human is responsible for providing input and making decisions about the content in both cases.

?

As the AI algorithm generates content that is similar to human-written content, it can be difficult to distinguish between the two, leading to questions about the authenticity and originality of the content, the same way a well-trained ghostwriter could write as someone else also in a way difficult to distinguish between the ghostwriter and author. There are some papers and many other studies evaluating the way an author writes as a fingerprint. If a human can do that way and some authors use this as a competitive advantage to publish a series of books or plays without revealing the ghosts, should we do the same with AI, or why should we think AI-aid is a bad thing?

?

In my opinion, AI-aid is there and will be the next big revolution in human history, transforming people's lives entirely in a way never seen before.

?

As in this discovery process, I learned another benefit of using CAW and AI-generated content: the amplification of vocabulary. The suggestions provided by the AI algorithm can help to expand an author's vocabulary and improve the quality of their writing. Additionally, the human ability to learn and adapt to these suggestions is also impressive, as it allows authors to incorporate new words and phrases into their writing, which in my case was indeed something impressive.

?

Another advantage of using CAW is the ability to maintain one's own writing style and voice. How the prompt is designed, and the output is generated can help to ensure that the final product reflects the author's own voice and style. Again, if a human ghostwriter can do it, AI can do it too, and better.

?

If you play your role as an author using some kind of AI CAW, Furthermore, it allows you to generate text with a more natural and human-like language, it also can help to create a more coherent and consistent narrative, as well as a more accurate and precise piece of information.

?

The precision of the information generated should be the primary focus when using CAW and AI-generated content. As with any algorithm, if the input is poor quality, the output will also be poor quality. It's crucial to ensure that the AI is trained on accurate and unbiased data to avoid the output being a random generation of text, lacking real meaning or core message. This is like the saying "garbage in, garbage out". If you give it bad information, you will get bad information in return.

?

Proper curation of the output is essential to ensure the quality and accuracy of the information generated. Without it, the text generated may not be fit for purpose or may not convey the intended message. This is a time-consuming task but is necessary to produce a high-quality final text, again this is a part of the iterative process, also it's crucial to ensure that the AI is trained on accurate and unbiased data, or knows the bias to be sure what to expect as output, review and curate the output to ensure that the information is accurate and meaningful, a simple acceptance it's not what we expect ethically in my point of view.

?

What we are living now is leading to the rise of "Prompt Engineering", changing candles for light bulbs, in various fields and industries. A new concept improving and professionalizing the act of writing specific prompts or inputs to guide the output of these models in order to generate specific text, speech or other forms of data. This will be applied in an enormous number of situations and environments, from natural language processing and language translation to chatbots and virtual assistants, to creative writing and content generation, allowing prompt engineering for a more targeted and personalized output, and it can be used to improve efficiency and productivity in various tasks.

?

It can also be used to generate new forms of creative content, such as poetry, fiction, and even music, and this leads us to see creations never expected by humans. I bring up the case of the ancient game of Go, in 2016, when Fan Hui, a three-time European Go champion who is highly respected in the Go world and who has dedicated his life to mastering the ancient game and is considered one of the best players in the world, was faced with a new opponent, AlphaGo, an artificial intelligence developed by Google.

?

Fan Hui was confident going into the match, but he was completely gobsmacked when AlphaGo made a move that he had never seen before. "It's not a human move. I've never seen a human play this move," he said. But as he looked closer, he realized that the move was not only unexpected but also beautiful. "So beautiful. So beautiful".

?

That move changed the path of the game, and AlphaGo went on to win the second game. It then won the third game, claiming victory in the best-of-five match after a three-game sweep. But Fan Hui knew that this was not just a victory for a machine, it was a demonstration of the mysterious power of modern artificial intelligence. He could see how it was not only driving one machine's ability to play this ancient game at an unprecedented level, but also simultaneously reinventing all of Google, and other companies, such as Facebook, Microsoft, Twitter, Tesla, and SpaceX.

?

Fan Hui became an advisor to the team that built AlphaGo, and he spent the next five months playing game after game against the machine. He came to recognize its power, but he knew that there was another player who had an even greater understanding of this move, AlphaGo itself.

?

But the most striking aspect of this story is the fact that a game with over 2,500 years of history, originating in China, and considered one of the oldest board games in the world, can still hold surprises for even the most seasoned players. A player of Fan Hui's caliber, comparable to a grandmaster in chess, was able to recognize and appreciate the beauty of a move that he had never seen before and deemed impossible for a human to make. It reminds me of the historic match between IBM's Deep Blue and chess grandmaster Garry Kasparov that took place during my childhood.

?

But I want you to understand, and realize the importance of his combination of words "So beautiful", a pure, natural, spontaneous and by itself also beautiful reaction, comparable to being amazed by some masterpiece created by a genius.?

?

In the case of the use of CAW, there are some similarities we expect to see and maybe observe an impressive increase in the overall quality of work produced by the massive combination of people using this assistance.

?

In conclusion, the use of Computer-Aided Writing (CAW) and AI-generated content presents both opportunities and challenges. As an author, I found that using CAW tools helped me to improve my writing and to deliver a high-quality final product.?

?

During the process of writing this book, I used AI as a simulated collection of human answers to situations in which I expected to have real human behavior. The answers provided by the AI were often surprising in their common sense and similarity to real human responses.

?

For this, I sometimes considered AI as one of my real students answering some questions, after bringing AI an exercise made by me, and asking them to answer that question, expanding the given example, the AI did that as a normal classroom full of students in my major would do it.?

?

Remarkably, the common sense applied in the answers was somehow what I truly expected. I put it to a test using a real class example and at least one answer for the question, a simulated scenario, was extremely close to the collaborative real human response. What I could conclude about this is that you can use the CAW as a simulated collection of human answers to situations whereas you truly expect to have real human behavior.?

?

You will see at some points in this book some tables with examples. There are answers collected by humans and some collected by AI. I hope you identify that it is a simple and funny test, I hope you readers reach me with your guessing.

?

By the end of this journey, the experience I had was "remarkable", an indisputable moment for humankind evolving ethics, authorship, the conception of art in the aegis of artificial intelligence, and all consequences of what is yet to come. With the work present in this book, I hope you get involved, learn a lot about this subject (public speaking) which I love, start a discussion with your friends and colleagues about this new world, and, of course, send me your best review about this work.?

?

Overall, the experience of using CAW and AI-generated content highlights the need for continued discussion and exploration of the ethical and authorship implications of these technologies.?

?

I hope that this book serves as a starting point for further discussion and that readers share their own perspectives and insights on this important topic. As we continue to evolve in this new world of artificial intelligence, we must approach it with a sense of consciousness and a commitment to ethical practices. Go ahead and jump your lines here, bring your point of view, make this discussion deeper and solid, help our species to evolve in this new world, and explore the intersection of Artificial Intelligence and authorship, safely.

?

Enjoy!