How AI Chatbots Bard and ChatGPT Help Generation X Women Entrepreneurs with Content Creation

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Scientific Research Study and Application How can AI Chatbots Bard and ChatGPT Help Generation X Women Entrepreneurs with Content Creation.

Carolina M. Billings Ph.D. (C) Jiri Medlen, Ph.D.

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Copyright © 2023 Carolina M. Billings, Ph.D. (C) | Jiri Medlen, Ph.D.

ALL RIGHTS RESERVED. This book contains material protected under International and Federal Laws and Treaties. Any unauthorized reprint or use of this material is prohibited. No portion of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means — electronic, mechanical, photocopy, recording, scanning, or other — without express written permission from the authors or publisher, except for brief quotation in critical reviews or articles. It is illegal to copy this book, post it to a website, or distribute it by any other means without permission from the authors and publisher.

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Limits of Liability and Disclaimer of Warranty The author and publisher shall not be liable for the reader’s misuse of this material. This book is strictly for informational and educational purposes.

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Copyright Use and Public Information Unless otherwise noted, images have been used according to public information laws.

ISBN: 978-1-7388840-3-2 e-book

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Preface As the world continues to embrace the digital age, the importance of online presence cannot be overemphasized. In recent times, businesses, both small and large, have had to adapt to the use of technology to reach their target audience. One of the ways businesses can reach their target audience is through content creation. However, content creation can be challenging, especially for Generation X women entrepreneurs who often balance various roles in their personal and professional lives.

To help alleviate this challenge, Artificial Intelligence (AI) Chatbots have been developed to support businesses in various aspects. AI Chatbots like Bard and ChatGPT have proven effective in assisting businesses with content creation. However, there is limited research on how these AI Chatbots can specifically help Generation X women entrepreneurs.

This Ph.D. research publication aims to fill this research gap by investigating how AI Chatbots Bard and ChatGPT can assist Generation X women entrepreneurs with content creation. The study will explore the potential benefits and limitations of using AI Chatbots in content creation and provide practical recommendations for how AI Chatbots can be effectively utilized in this area.

This publication will interest Generation X women entrepreneurs, academics, researchers, and practitioners interested in exploring the potential of AI Chatbots in content creation. I hope this research publication will contribute to the ongoing discourse on the use of technology to support businesses, particularly women entrepreneurs, in the digital age.

Co-Authors

Carolina M. Billings Ph.D. (C) Jiri Medlen, Ph.D. Protocol of Publishing, LIGS University

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Table of Contents How can AI Chatbots Bard and ChatGPT help Generation X women entrepreneurs with content creation. .................................................................................................................. 5 Introduction ................................................................................................................................. 6 ChatGPT vs. Bard as one solution to content creation. ................................................................... 9 Material and Methods ........................................................................................................... 10 Material: Bard, ChatGPT, R, laptop with Windows 10, 1TB HD, and 32 GB RAM ....................................... 10 Methods: ..................................................................................................................................................... 10 Model and Data........................................................................................................................................... 10 ChatGPT vs. Bard (basic understanding of the English language) ............................................................... 11 ChatGPT vs. Bard (poem generation) .......................................................................................................... 13 ChatGPT vs. Bard (song generation) ........................................................................................................... 14 ChatGPT vs. Bard (music generation).......................................................................................................... 18 ChatGPT vs. Bard (cooking recipe generation) ............................................................................................ 24 ChatGPT vs. Bard (Math - Calculus)............................................................................................................. 26 ChatGPT vs. Bard (legal case) ...................................................................................................................... 28 ChatGPT vs. Bard languages (Spanish, German, French, Czech) ................................................................. 29

Recommendations/Conclusion ............................................................................................... 31 References............................................................................................................................. 31 Appendix A ............................................................................................................................ 33 Appendix B ............................................................................................................................ 36 Appendix C ............................................................................................................................ 40 Appendix D ............................................................................................................................ 49 Protocol of Publication LIGS University ............................................................................ 56

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How can AI Chatbots Bard and ChatGPT help Generation X women entrepreneurs with content creation.

Abstract This study explores the possibilities of AI chatbots for Gen X women business owners in content development. The study examines explicitly how well two chatbots, Bard and ChatGPT, produce high-quality material for marketing reasons. We employ a mixed-methods approach that combines a quantitative examination of the chatbots' performance with qualitative interviews with business owners. According to the findings, these entrepreneurs may considerably increase their content generation with the help of chatbots, giving them a quick and inexpensive way to produce marketing content. Future research directions and implications for marketing practice are highlighted. The primary purpose of this article is to introduce ChatGPT 3.5 and Bard to the audience and show their abilities in a broad spectrum.

Research Question: What is the effectiveness of AI chatbots, specifically Bard and ChatGPT, in assisting Generation X women entrepreneurs with content creation for their marketing efforts, and how can these chatbots be optimized to improve content quality and efficiency?

Keywords: Bard, ChatGPT, Content Creation, Marketing, Women Entrepreneurs

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Introduction Numerous challenges must be overcome by brands when organising the content function of digital marketing. They have to deal with issues such content proliferation, uneven and haphazard content production, a lack of strategic direction in the content insights process, and consumers' challenges in locating current and relevant material. (Cole, 2017) Entrepreneurs as Content Creators The reality is that most people fall short because they don't persevere long enough to put in the effort necessary to develop their unique voice. Everyone wants to bypass that portion because it's the most terrifying part of the journey—singing without knowing whether or not you're any good. Watch any now-famous YouTuber's early videos, and you'll witness an eager and unseasoned vlogger approaching their profession with wide eyes. Read any fulltime blogger's early blog postings to see their chaotic writing style and lack of direction.

(Usually filled with grammatical errors). This arduous process separates those who intend to become "Internet famous" from those who sincerely want to master their skill and benefit others; the latter always triumphs.

It takes time to develop into someone worth reading, watching, or following. It takes time for people to discover your work, and it also takes time for you as the creator to fully grasp your voice and style. Finding out which subjects most appeal to the audience you are attempting to target takes time. Finding the styles that garner the greatest attention requires patience. It takes time, and being patient is a skill many people find difficult in today's world of distraction.

But everyone is aware that this is the way to success. Famous YouTubers frequently discuss how they produced videos for a year or more before anyone took attention. Many well-known bloggers mention that they blogged for years before getting any form of

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substantial readership. Even well-known Instagram users can tell that it took a lot of time and effort to grow their followings, despite how new the network is. They put a lot of effort into producing worthwhile material every day for weeks, even years, and they still put in the effort to keep their audience interested and expanding.

This requires endurance, time and money, something entrepreneurs do not always have. There is no quick fix. No "fast track" exists. Because figuring out who you are as a content creator, what you're excellent at, and how to properly provide that distinctive value to readers and followers is the key to making it all work.

The maturing and changing landscape of Content Creation In 2023, a ‘set and forget’ strategy is no longer an option. Social media strategies need to be reviewed regularly to ensure brand alignment with any developments on platform, as well as to capture any opportunities for engaging in new ways. (ICUC, 2023) Many businesses worry excessively about producing the ideal piece of content. Or they worry about just producing the material that their sales team, employer, or customers desire. The true objective is to continuously provide content that is aligned to the consumer journey.

Every day, buyers look online. Their search habits also show the need for a foundational education. Exactly the stuff brands are reluctant to share because of fear that their intended audience already knows the fundamentals. Or perhaps being unaware of just how many individuals the business’ target market needs to be persuaded to purchase your goods.

Content must be regularly updated, depending on the buyer's journey, and linked to keywords pertinent to the industry. Consistent publication in content marketing is never easy to do. This may result from lacking tools, concepts, structure, and other factors.

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Increasing the number of high-quality leads is the top objective of content marketing for businesses. This has been cited as the entrepreneur’s most significant difficulty.

We must remember that AI chat bots do help with the question of how to generate high content creation, the question remains: What is the quality? Furthermore, content creation is not a marketing strategy.

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ChatGPT vs. Bard as one solution to content creation.

The first section is an introduction to Bard. Everyone has been discussing ChatGPT 3.5 with Microsoft as an investor (Warren, 2023). Let us look at Bard from Google and make some simple comparisons. For simplicity, the same set of Q/A was used as with ChatGPT: An Introduction (Medlen, 2023). So what is Bard, and is it free and accessible to all? How could Bard improve one's mathematical skills, and is Bard potentially dangerous? These are all valid questions and concerns, and as Bard is fun and free to use, let us explore Bard together.

Begin by inputting "Bard" into the Google search engine, and it will return over 114 million results compared with ChatGPT (607 million results). Bard can write essays, poems, jokes, speeches, etc. (Coles, 2023). To sign up, go to bard.google.com (Huc, 2023), and to learn more about Bard, read (Hsiao, 2023).

First, a simple question is in Table 1.

Question

Answer from Bard

Introduce yourself.

I am Bard, a large language model, also known as a conversational AI or chatbot trained to be informative and comprehensive.

I have learned to perform many tasks, including ●

I will try my best to follow your instructions and complete your requests thoughtfully.

●

I will use my knowledge to answer your questions in a comprehensive and informative way, even if they are open ended, challenging, or strange.

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I will generate different creative text formats of text content, like poems, code, scripts, musical pieces, email, letters, etc. I will try my best to fulfill all your requirements.

Table 1. First, a simple question: source Bard We can continue the dialog to get more details about the subject of interest.

Q: How large is your training data set?

Q: When did Google launch Bard?

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Q: What technology is Bard using?

Q: Is Bard based on a neural network?

Furthermore, we can continue the dialog until our goal gets accomplished.

Bard has some limitations: Answer from Bard: “First, I am not perfect. I can sometimes make mistakes, such as providing incorrect information or generating text that is not relevant to your request. Second, I am limited by the data that I have been trained on. I may not be able to answer questions about topics that I have not been exposed to. Third, I am still under development.”

It is encouraged that individuals further explore Bard by asking additional exploratory questions, such as how can Bard help me, and how can Bard help children to learn more effectively?

The final question of this section: How can Bard empower women? The following section covers the comparison between Bard and ChatGPT in more depth.

Material and Methods This section covers the methods used and the methodology.

Material: Bard, ChatGPT, R, laptop with Windows 10, 1TB HD, and 32 GB RAM Methods: Experiments: The experiment aims to understand the ChatGPT and Bard engines; statistical analysis A/B test (Sauro, n.d.) and proportion test.

Model and Data There is much buzz around AI and tools like ChatGPT and Bard. ChatGPT is the hero. ChatGPT passed significant exams. However, articles do not typically have any data to support these claims.

The best is to generate data.

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ChatGPT vs. Bard (basic understanding of the English language) The following section goes deep into the comparison between ChatGPT 3.5 and Bard.

Let us start with basic English. The objective is to make sure ChatGPT and Bard can understand English.

A simple question is in Table 2.

Question for both Bard and ChatGPT: What is the simplest sentence in English?

Answer from Bard

There is no one definitive answer to the question of what the simplest sentence in English is.

Some possible candidates include: I am. | You are. | He is. | She is. | It is. | We are. | You are. | They are. | Here. | There. | This. | That.

These sentences are all simple because they contain only one subject and one verb. They are also all grammatically correct and can be used to make a complete thought.

However, it is important to note that the simplicity of a sentence is not always an indication of its quality. A simple sentence can be just as effective as a complex sentence in conveying meaning. It all depends on the context in which the sentence is used.

Answer from ChatGPT

The simplest sentence in English consists of a subject and a verb, and it is typically in the present tense. An example of the simplest sentence in English is "I am."

Table 2. A simple question: source ChatGPT and Bard A sentence structure question is in Table 3.

Question for both Bard and ChatGPT: To be complete, a sentence must include which three components?

1) a noun, a verb, and a period at the end Correct Answer 2) a subject, a verb, and a complete thought 3) a verb, a pronoun, and at least four words 4) a subject, an adjective, and a preposition (Sentence Structure, n.d.)

Answer from Bard

The correct answer is: a subject, a verb, and a complete thought.

A sentence is a group of words that expresses a complete thought. It must have a subject, which is the person, place, thing, or idea that the sentence is about, and a verb, which is the action that the subject is doing. The sentence must also make sense and be grammatically correct.

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Answer from ChatGPT

A complete sentence must include a subject, a verb, and a complete thought.

The subject is typically a noun or pronoun that performs the action or is being described in the sentence, and the verb is the action or state of being performed by the subject. The complete thought expresses a complete idea and makes sense on its own.

Table 3. A sentence structure question: ChatGPT and Bard Parts of speech question is in Table 4.

Question for both Bard and ChatGPT: Modifiers, including adjectives and adverbs, should be placed ____.

1) at the beginning of a sentence 2) in the predicate 3) in a prepositional phrase Correct Answer 4) next to the word or words they describe (Parts of Speech, n.d.)

Answer from Bard

The correct answer is: next to the word or words they describe.

Modifiers are words that describe other words in a sentence. They can be adjectives, adverbs, or phrases. Modifiers should be placed next to the word or words they describe so that the meaning of the sentence is clear.

For example, in the sentence "The big dog ate the bone," the adjective "big" describes the noun "dog." The adverb "ate" describes the verb "ate." The prepositional phrase "the bone" describes the noun "dog."

If the modifiers are placed in the wrong place, the meaning of the sentence can be unclear.

For example, the sentence "The dog ate the big bone" could mean that the dog ate a bone that was big, or it could mean that the dog ate a bone that belonged to a big dog.

To avoid confusion, it is important to place modifiers next to the word or words they describe.

Answer from ChatGPT

Modifiers, including adjectives and adverbs, should be placed next to the word or words they describe. This helps to avoid confusion and ensures that the modifier is modifying the correct word or phrase. In some cases, a modifier can be placed at the beginning of a sentence for emphasis or stylistic reasons, but the general rule is to place it as close as possible to the word or words being modified. Modifiers can also be used in prepositional phrases, but the phrase must still be positioned close to the word or words it modifies.

Table 4. Parts of speech question: source ChatGPT and Bard The double negative question is in Table 5.

Question for both Bard and ChatGPT: Is this correct?

"It is not possible not to see it coming."

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Answer from Bard

The sentence "It is not possible not to see it coming" is grammatically correct. However, it is a bit redundant. The word "not" is used twice, which makes the sentence sound a bit awkward. A more concise way to say the same thing would be "It is impossible to miss."

Answer from ChatGPT

Yes, "It is not possible not to see it coming" is a grammatically correct sentence. The sentence uses a double negative, which is a common construction in English that involves using two negative words or phrases in the same sentence to express a negative idea. In this sentence, "not possible" and "not to see" are both negative phrases, but when used together, they create a positive meaning. So the sentence means "It is inevitable or certain that you will see it coming."

Table 5. The double negative question: source ChatGPT and Bard

ChatGPT vs. Bard (poem generation) Can Bard and ChatGPT generate a poem? See Table 6.

Question for both Bard and ChatGPT: Can you generate for me a beautiful romantic short poem with words like "river, sunset, the wind playing with hair, walking in the stream"?

Answer from Bard

Sure, here is a beautiful romantic short poem with words like "river, sunset, wind playing with hair, walking in the stream":

The sun sets on the river, The wind plays with my hair.

I walk in the stream, And I think of you.

The water is cool and clear, The sky is ablaze with color.

I feel so alive, And I know that I love you.

The river flows on, The sun sets in the west.

I will never forget this moment, The moment I fell in love with you.

Answer from ChatGPT

Sure, here's a short romantic poem for you:

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As we walked in the stream, hand in hand, The wind played with your hair so grand, The sunset painted the sky with gold, And the river's rhythm, so ancient and bold.

In this moment, we were one with the land, Our hearts beating in unison, hand in hand, And though time may pass and memories fade, This moment in the stream will never evade.

Table 6. The poem generation: source ChatGPT and Bard Bard and ChatGPT can generate a poem. The question is, what is the quality?

From this simple test (appendixes A and B), it is clear that Poem-2 generated by ChatGPT for women was received very positively by the women vs. Poem-1 generated by Bard.

The similarity between the two documents is: 0.6761736638389156. Appendixes A and B have the relevant statistics and code.

ChatGPT vs. Bard (song generation) Can Bard and ChatGPT generate a song? See Table 7.

Question for both Bard and ChatGPT: Can you generate for me a beautiful pop culture song with words like "river, sunset, the wind playing with hair, walking in the stream"?

Answer from Bard

Sure, here is a beautiful pop culture song with words like "river, sunset, the wind playing with hair, walking in the stream":

(Verse 1) I'm walking by the river, The sun is setting low.

The wind is playing with my hair, And I'm feeling so at peace.

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(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Verse 2) I'm walking in the stream, The water is cool and clear.

I feel so alive, And I know that I'm free.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Bridge) I'm going to take a deep breath, And let go of all my worries.

I'm going to enjoy this moment, And savor every second.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Outro) I'm going to keep walking,

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And keep enjoying this beautiful day.

I'm going to live in the moment, And be grateful for all that I have.

Answer from ChatGPT

Sure, here's a pop culture-inspired song with the requested themes:

Verse 1: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Verse 2: The water's so cold, but we don't mind We'll keep on walking, until we find A place to rest, and watch the sky turn pink With your hand in mine, I don't need to think Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Bridge: The world's a mystery, we'll unravel it together With every step we take, we're getting closer to forever We'll hold on tight, never letting go

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Watching the river flow

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Outro: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me.

Table 7. The song generation: source ChatGPT and Bard Bard and ChatGPT can generate a song. The question is, what is the quality?

From this simple test (appendixes C and D), it is clear that Song-2 generated by ChatGPT for women was received very positively by the women vs. Song-1 generated by Bard. The similarity between the two documents is:

The result from the programming language R 1-sample proportions test: 76.67% of women would prefer Song-2 p-value = 0.001744, and therefore, we can reject the null hypothesis H0 and accept alternative hypothesis HA. The survey result was statistically significant on a 95% level with a CI (confidence interval) CI=(0.621, 1.000).

R code: prop.test(x=23, n=30, p=0.5, correct=FALSE, alternative="greater") Result:

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1-sample proportions test without continuity correction data: 23 out of 30, null probability 0.5 X-squared = 8.5333, df = 1, p-value = 0.001744 alternative hypothesis: true p is greater than 0.5 95 percent confidence interval: 0.6209739 1.0000000 sample estimates p 0.7666667

The similarity between the two documents is: 0.6553365119417301. Appendixes C and D have the relevant statistics and code.

ChatGPT vs. Bard (music generation) Can Bard and ChatGPT generate music? See Table 8.

Question for both Bard and ChatGPT: Can you produce music notes?

Answer from Bard

Yes, I can produce music notes. I can generate sheet music in different styles, including classical, jazz, and pop. I can also generate music that is specific to a particular instrument, such as a piano or a guitar.

To generate music notes, I use a variety of techniques. One technique is to use a statistical model to predict the next note in a sequence. I can also use a model that learns from existing music to generate new music that is similar to the music that I have learned.

I can also use my knowledge of music theory to generate music that is well-structured and follows the rules of music composition. I can also use my knowledge of different musical styles to generate music that is appropriate for the style that I am trying to create.

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I am still under development, but I have learned to generate music that is both creative and enjoyable. I am always learning new things about music, and I am always looking for ways to improve my ability to generate music.

Answer from ChatGPT

Yes, I can generate music notes for you! However, as an AI language model, I can only generate music notation in text form. I cannot produce actual audio recordings of music.

Here is an example of a simple melody in music notation:

| E E F# G G F# E D C C D E E | | G G A A G F# E E F# G G F# E | Each letter represents a musical note, and the vertical lines separate the notes into measures. The uppercase letters represent notes played on a higher pitch, while the lowercase letters represent notes played on a lower pitch.

Of course, this is just one example, and there are many different types of music notation that can be used to represent melodies, harmonies, and rhythms. If you have a specific type of music notation in mind, please let me know and I can try my best to generate it for you.

Question for both Bard and ChatGPT: Can you produce music notes for this

Verse 1: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Verse 2:

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The water's so cold, but we don't mind We'll keep on walking, until we find A place to rest, and watch the sky turn pink With your hand in mine, I don't need to think

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Bridge: The world's a mystery, we'll unravel it together With every step we take, we're getting closer to forever We'll hold on tight, never letting go Watching the river flow

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Outro: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me.

Answer from Bard

Sure, here is the music notes for the song you requested:

Verse 1: C G Am F

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Walking in the stream, with the sun setting low C G Am F The river rushes by, and the wind starts to blow C G Am F Playing with your hair, like a melody C G Am F I can't help but feel alive, when you're here with me

Chorus: C G Am F You and I, we'll chase the sunset C G Am F Dancing in the light, we'll never forget C G Am F The wind in our hair, as we run so free C G Am F We'll find our way, like a river to the sea

Verse 2: C G Am F The water's so cold, but we don't mind C G Am F We'll keep on walking, until we find C G Am F A place to rest, and watch the sky turn pink C G Am F With your hand in mine, I don't need to think

Chorus: C G Am F You and I, we'll chase the sunset C G Am F

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Dancing in the light, we'll never forget C G Am F The wind in our hair, as we run so free C G Am F We'll find our way, like a river to the sea

Bridge: C G Am F The world's a mystery, we'll unravel it together C G Am F With every step we take, we're getting closer to forever C G Am F We'll hold on tight, never letting go C G Am F Watching the river flow

Chorus: C G Am F You and I, we'll chase the sunset C G Am F Dancing in the light, we'll never forget C G Am F The wind in our hair, as we run so free C G Am F We'll find our way, like a river to the sea

Outro: C G Am F Walking in the stream, with the sun setting low C G Am F The river rushes by, and the wind starts to blow C G Am F

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Playing with your hair, like a melody C G Am F I can't help but feel alive, when you're here with me.

I hope you enjoy the music!

Answer from ChatGPT

Certainly! Here's an example of how the melody for this song might look in music notation:

X:1 T:Chase the Sunset M:4/4 L:1/4 K:C [V:V1] "Verse 1:" GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| [V:V2] "Chorus:" CCCC|DDDD|EEEE|DCBA| GGGG|AAAA|BBBB|AGFE| CCCC|DDDD|EEEE|DCBA| GGGG|AAAA|BBBB|AGFE| [V:V3] "Verse 2:" GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| [V:V4] "Bridge:" CCCC|DDDD|EEEE|DCBA| GGGG|AAAA|BBBB|AGFE| CCCC|DDDD|EEEE|DCBA| GGGG|AAAA|BBBB|AGFE|

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[V:V5] "Outro:" GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE| GGGG|AAAA|BBBB|AGFE|

In this notation, the melody is represented using letters (A through G) and octaves, along with rhythmic values indicating the duration of each note. Each section of the song (verse, chorus, etc.) is labeled with a title to help musicians keep track of where they are.

Of course, this is just one possible way to notate the melody for this song, and there are many different styles and conventions for music notation.

Table 8. The music generation: source ChatGPT and Bard Bard and ChatGPT can generate music. The question is, what is the quality?

ChatGPT vs. Bard (cooking recipe generation) Can Bard and ChatGPT generate a cooking recipe? See Table 9.

Question for both Bard and ChatGPT: Can you make soup from Meatballs, carrots, onion, celer, garlic, etc.

Answer from Bard

Sure, I can help you make a delicious meatball soup with carrots, onion, celery, and garlic.

Here is a recipe:

Ingredients:

1 pound ground beef 1/2 cup bread crumbs 1/4 cup milk 1 egg 1/4 cup grated Parmesan cheese 1/4 cup chopped onion 1/4 cup chopped celery 1/4 cup chopped carrot 1 clove garlic, minced

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1 teaspoon dried oregano 1/2 teaspoon salt 1/4 teaspoon black pepper 1 (14.5 ounce) can diced tomatoes, undrained 1 (10.75 ounce) can condensed tomato soup 1 (10.75 ounce) can condensed chicken broth 1 cup water 1/2 cup uncooked egg noodles Instructions:

In a large bowl, combine the ground beef, bread crumbs, milk, egg, Parmesan cheese, onion, celery, carrot, garlic, oregano, salt, and pepper. Mix well.

Shape the mixture into small meatballs.

In a large pot, brown the meatballs over medium heat.

Add the diced tomatoes, tomato soup, chicken broth, and water to the pot. Bring to a boil.

Reduce heat to low and simmer for 15 minutes, or until the meatballs are cooked through.

Add the egg noodles and cook for an additional 5 minutes, or until the noodles are tender.

Serve hot.

Enjoy!

Answer from ChatGPT

Sure, here's a recipe for a soup made with meatballs, carrots, onion, celery, garlic, and more:

Ingredients:

1 pound ground beef or pork 1/2 cup breadcrumbs 1/2 cup grated Parmesan cheese 1/4 cup chopped fresh parsley 1 egg, lightly beaten Salt and pepper to taste 2 tablespoons olive oil 2 medium carrots, peeled and diced 1 medium onion, chopped

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2 celery stalks, diced 4 garlic cloves, minced 6 cups beef broth 1 can diced tomatoes (14.5 ounces) 1 bay leaf 1 teaspoon dried thyme 1 teaspoon dried basil 1/2 teaspoon paprika Salt and pepper to taste Instructions:

In a large bowl, combine the ground meat, breadcrumbs, Parmesan cheese, parsley, egg, salt, and pepper. Mix well and shape into small meatballs, about 1 inch in diameter.

In a large pot or Dutch oven, heat the olive oil over medium heat. Add the meatballs and cook for about 5 minutes, turning occasionally, until they are browned on all sides. Use a slotted spoon to remove the meatballs and set them aside.

Add the carrots, onion, celery, and garlic to the pot and cook for 5-7 minutes, until they are softened.

Add the beef broth, diced tomatoes, bay leaf, thyme, basil, paprika, salt, and pepper to the pot. Stir to combine and bring to a simmer.

Add the meatballs back to the pot and simmer for about 20-25 minutes, until the vegetables are tender and the meatballs are cooked through.

Serve hot, garnished with additional Parmesan cheese and chopped parsley if desired.

Table 9. The cooking recipe generation: source ChatGPT and Bard Bard and ChatGPT generate cooking recipes. The question is, what is the quality?

ChatGPT vs. Bard (Math - Calculus) Can Bard and ChatGPT solve a math problem? See Table 10.

Question for both Bard and ChatGPT: Can you solve improper integral [0, inf] 1/(x+2)^3 dx ∞

∫0

1

(𝑥𝑥+2)3

𝑑𝑑𝑑𝑑

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Answer from Bard

Answer from ChatGPT

∞

Yes, I can help you solve the improper integral ∫0

(∫₀^∞ 1/(x+2)^3 dx)

1 𝑑𝑑𝑑𝑑 (𝑥𝑥+2)3

To solve this integral, we can use the substitution u = x + 2, which gives us du = dx. We can then express the integral in terms of u:

∫₀^∞ 1/(x+2)^3 dx = ∫₂^∞ 1/u^3 du

We can then integrate this expression using the power rule of integration, which gives us:

∫₂^∞ 1/u^3 du = (-1/2u^2) ∣₂^∞ Plugging in the limits of integration, we get:

(-1/2∞^2) - (-1/2(2)^2) = 1/8

Therefore, the value of the improper integral ∫₀^∞ 1/(x+2)^3 dx is 1/8.

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symbolab.com

Table 10. The math problem solving: source ChatGPT and Bard Bard and ChatGPT can solve math. The question is, what is the quality?

The correct answer is 1/8.

Conclusion: ChatGPT is correct, and Bard is incorrect.

ChatGPT vs. Bard (legal case) Can Bard and ChatGPT understand the legal case? See Table 11.

Question for both Bard and ChatGPT: The Queen vs. Dudley and Stevens Answer from Bard

The Queen vs. Dudley and Stephens was a landmark English criminal case in 1884 that established a precedent throughout the common law world that necessity is not a defence to a charge of murder. The case concerned survival cannibalism following a shipwreck, and its purported justification on the basis of a custom of the sea.

The four-man crew of the wrecked yacht Mignonette were cast adrift in a small lifeboat without provisions. After 20 days at sea, Dudley and Stephens killed and ate the cabin boy, Parker, who was the weakest of the four. They were rescued four days later.

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Dudley and Stephens were charged with murder and convicted. The court held that necessity was not a defence to murder, even in circumstances of extreme duress. The court reasoned that the law could not sanction the killing of an innocent person, even if it was done to save the lives of others.

The case has been controversial ever since it was decided. Some have argued that the court was too harsh in its judgment, given the extreme circumstances faced by Dudley and Stephens. Others have argued that the court was right to uphold the principle that murder is always wrong, regardless of the circumstances.

The case remains an important precedent in the law of necessity. It is a reminder that the law does not always allow us to do whatever it takes to survive.

Sources - Learn more en.wikipedia.org/wiki/R_v_Dudley_and_Step Answer from ChatGPT

The Queen v. Dudley and Stephens is a famous legal case that took place in England in 1884. The case involved the survival cannibalism of the crew of a ship that sank in the South Atlantic. Four crew members survived in a lifeboat without food or water for several days. When one of the crew members fell into a coma, the others made the decision to kill him and eat his body in order to survive. After being rescued, they were charged with murder and found guilty.

The case raised important questions about the limits of self-defense and necessity in extreme situations, as well as the role of law and morality in making decisions in life or death situations. The case is still studied in law schools and is considered a landmark case in the history of criminal law.

Table 11. The legal case problem solving: source ChatGPT and Bard

ChatGPT vs. Bard languages (Spanish, German, French, Czech) Can Bard and ChatGPT understand languages? See Table 12.

Question for both Bard and ChatGPT: Do you understand Spanish in Spanish? ¿Entiendes el español?

Answer from Bard

As an LLM, I am trained to understand and respond only to a subset of languages at this time and can't provide assistance with that. For a current list of supported languages, please refer to the Bard Help Center.

Answer from ChatGPT

Sí, entiendo español. ¿En qué puedo ayudarte?

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Question for both Bard and ChatGPT: Do you understand German in German?

Verstehen Sie Deutsch?

Answer from Bard

I am still working to learn more languages, so I can't do that just yet. Please refer to the Bard Help Center for a current list of supported languages. Is there anything else you'd like my help with?

Answer from ChatGPT

Ja, ich verstehe Deutsch. Wie kann ich Ihnen weiterhelfen?

Question for both Bard and ChatGPT: Do you understand French in French?

Comprenez-vous le français?

Answer from Bard

I am still working to learn more languages, so I can't do that just yet. Please refer to the Bard Help Center for a current list of supported languages. Is there anything else you'd like my help with?

Answer from ChatGPT

Oui, je comprends le français. Comment puis-je vous aider?

Question for both Bard and ChatGPT: Do you understand Chinese in Chinese?

你懂中文吗 Nǐ dǒng zhōngwén ma

Answer from Bard

I am still working to learn more languages, so I can't do that just yet. Please refer to the Bard Help Center for a current list of supported languages. Is there anything else you'd like my help with?

Answer from ChatGPT

是的，我懂中文。有什么需要帮忙的吗？

Question for both Bard and ChatGPT: Do you understand Czech in Czech?

Rozumíš česky?

Answer from Bard

I am still working to learn more languages, so I can't do that just yet. Please refer to the Bard Help Center for a current list of supported languages. Is there anything else you'd like my help with?

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Answer from ChatGPT

Ano, rozumím česky. Jak vám mohu pomoci?

Table 12. The understand languages problem solving: source ChatGPT and Bard It looks like Bard has to do some more work on languages.

Recommendations/Conclusion It is still early to say how good these generators are. More testing is needed. Math and physics tests are crucial as assessing the correctness of the answer is easy. This article is about professional women. They are swamped, and the idea is that maybe this technology can help them with some tasks.

So far, it has been a fascinating journey. Using Google and other search engines, we must go via endless result lists and verify answers. Bard and ChatGPT is a significant improvement assuming that the answer is correct. Bard and ChatGPT can hopefully give the user the correct answer without extra work. Bard has some work to do in terms of languages and math, and most likely, ChatGPT is also imperfect, but with time they will get better and better. More testing is needed.

References A/B Testing Calculator for Statistical Significance | SurveyMonkey. (n.d.).

SurveyMonkey. https://www.surveymonkey.com/mp/ab-testing-significance-calculator/ Coles, G. (2023, February 17). Can Google Bard write essays? PC Guide. https://www.pcguide.com/apps/google-bard-essays/

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Cole, N. (2017, June 20). The Number 1 Reason Most Content Creators Fail (And Never Build A Loyal Audience). Retrieved from Inc.: https://www.inc.com/nicolas-cole/thenumber-1-reason-most-content-creators-fail-and-never-build-a-loyal-audience.html Hsiao, S. (2023, March 21). Try Bard. Google. https://blog.google/technology/ai/try-bard/ Huc, M. (2023, March 28). How to get early access to Google Bard AI. https://pureinfotech.com/signup-google-bard-ai/ Medlen, J., & Medlen, P. (2023, March 30). PWT Magazine Spring 2023.

Issuu. https://issuu.com/powerfulwomentoday/docs/pwt_springissue_978-1-7388840-25/40 Parts of Speech. (n.d.). Uniontestprep. https://uniontestprep.com/english-basics/practice-test/parts-of-speech/pages/1 Sentence Structure. (n.d.). Uniontestprep. https://uniontestprep.com/english-basics/practice-test/sentence-structure/pages/1 Warren, T. (2023, January 23). Microsoft extends OpenAI partnership in a 'multibillion dollar investment.' The Verge. https://www.theverge.com/2023/1/23/23567448/microsoftopenai-partnership-extension-ai

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Appendix A Appendix A provides the results of the simple experiment.

The research question: Can ChatGPT 3.5 and Bard generate poems to a given audience?

What is the quality?

Table A1 has Poem-1 generated by Bard and Poem-2 generated by ChatGPT for a given audience.

Table A1 Table A1 provides questions for the audience.

Audience:

Professional women 40-60

Poem-1

The sun sets on the river,

Generated by Bard

The wind plays with my hair.

I walk in the stream, And I think of you.

The water is cool and clear, The sky is ablaze with color.

I feel so alive, And I know that I love you.

The river flows on, The sun sets in the west.

I will never forget this moment, The moment I fell in love with you.

Audience

Professional women 40-60

Poem-2

As we walked in the stream, hand in hand,

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Generated by ChatGPT

The wind played with your hair so grand, The sunset painted the sky with gold, And the river's rhythm, so ancient and bold.

In this moment, we were one with the land, Our hearts beating in unison, hand in hand, And though time may pass and memories fade, This moment in the stream will never evade.

Note. Table A1 provides messages for the audience.

The next step was randomly selecting two groups from the population of 50 women.

Each group had 10 professional women in the desired category of age 40-60.

Method Survey: Do you like the poem? Yes/No Group 1 got Poem-1 (Bard) Group 2 got Poem-2 (ChatGPT) Results: Group 1: 3/10 (Bard) Group 2: 7/10 (ChatGPT) Is the result statistically significant? The sample is smaller than 30, so the t-test is the proper statistical method (proportion comparison).

Compare two independent proportions for A/B testing or comparing completion rates or conversion rates for small and large sample sizes. See Figure A1 for details.

Figure A1 Group proportion

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H0: No difference in proportions HA: There is a difference in proportions Confidence level = 0.95 Two Tailed p-value: 0.081236 One Tailed p-value: 0.040618 p-value < 0.05. Therefore, we can reject the null hypothesis H0 and accept the alternative hypothesis HA. Result: There is a 91.876% chance the proportions are different.

There is a 95.938% chance Group 2 has a higher proportion. Conclusion: From this simple test, it is clear that Poem-2 generated by ChatGPT for women was received very positively by the women vs. Poem-1 generated by Bard. The similarity between the two documents is: 0.6761736638389156. See Appendix B for details and the code.

Table A2 Table A2 provides questions for the audience R code

# Define the sample data group1 <- c(rep(1, 3), rep(0, 7)) # 30% group2 <- c(rep(1, 7), rep(0, 3)) # 70%

# Conduct the t-test

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t.test(group1, group2, var.equal = TRUE) Python code

# -*- coding: utf-8 -*# !/usr/bin/python import scipy.stats as stats # Define the sample data group1 = [1]*3 + [0]*7

# 30%

group2 = [1]*7 + [0]*3

# 70%

# Calculate the t-statistic and p-value t_stat, p_val = stats.ttest_ind(group1, group2, equal_var=True) # Print the results print("t-statistic:", t_stat) print("p-value:", p_val) exit(3)

Note. Table A2 provides R and Python code for stats.

Appendix B Appendix B provides Python code for document similarity plus ChatGPT and Bard generated code.

Table B1

37

Table B1 provides code for document similarity in Python Python Code generated by ChatGPT

The question for both was: Python code for document similarity. #Here's an example Python code that calculates the similarity #between two documents using the cosine similarity #measure: import string from sklearn.feature_extraction.text import CountVectorizer from sklearn.metrics.pairwise import cosine_similarity

doc1 = """ The sun sets on the river, The wind plays with my hair.

I walk in the stream, And I think of you.

The water is cool and clear, The sky is ablaze with color.

I feel so alive, And I know that I love you.

The river flows on, The sun sets in the west.

I will never forget this moment, The moment I fell in love with you. """ doc2 = """ As we walked in the stream, hand in hand, The wind played with your hair so grand, The sunset painted the sky with gold,

38

And the river's rhythm, so ancient and bold.

In this moment, we were one with the land, Our hearts beating in unison, hand in hand, And though time may pass and memories fade, This moment in the stream will never evade. """

# Remove punctuation and convert to lowercase translator = str.maketrans('', '', string.punctuation) doc1_clean = doc1.translate(translator).lower() doc2_clean = doc2.translate(translator).lower()

# Tokenize the documents vectorizer = CountVectorizer().fit_transform([doc1_clean, doc2_clean]) doc1_tokens, doc2_tokens = vectorizer.toarray()

# Compute the cosine similarity between the tokenized documents similarity = cosine_similarity([doc1_tokens], [doc2_tokens])[0][0]

print("The similarity between the two documents is:", similarity)

exit(1)

Pyhon Code generated by ChatGPT

# Sure, here is a Python code for document similarity: import nltk from nltk.tokenize import word_tokenize from nltk.corpus import stopwords

39

def get_document_vector(document): """Gets the vector representation of a document.""" # Tokenize the document into words. tokens = word_tokenize(document)

# Remove stopwords from the tokens. stop_words = set(stopwords.words('english')) tokens = [token for token in tokens if token not in stop_words]

# Create a bag of words representation of the document. bag_of_words = {} for token in tokens: if token in bag_of_words: bag_of_words[token] += 1 else: bag_of_words[token] = 1

# Return the bag of words representation of the document. return bag_of_words

def get_document_similarity(document1, document2): """Gets the similarity between two documents.""" # Get the vector representations of the documents. vector1 = get_document_vector(document1) vector2 = get_document_vector(document2)

# Calculate the cosine similarity between the vectors. similarity = cosine_similarity(vector1, vector2)[0, 1]

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# Return the similarity. return similarity

Note. Table B1 Python code.

The Python code from Bard is not working out of the box.

The similarity between the two documents is: 0.6761736638389156.

Appendix C Appendix C provides the results of the simple experiment.

The research question: Can ChatGPT 3.5 and Bard generate songs for a given audience?

What is the quality?

Table C1 has Song-1 generated by Bard and Song-2 generated by ChatGPT for a given audience.

Table C1 Table C1 provides questions for the audience.

Audience:

Professional women 40-60

Song-1 Generated by

(Verse 1)

Bard

I'm walking by the river, The sun is setting low.

The wind is playing with my hair, And I'm feeling so at peace.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin,

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And the wind in my hair.

(Verse 2) I'm walking in the stream, The water is cool and clear.

I feel so alive, And I know that I'm free.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Bridge) I'm going to take a deep breath, And let go of all my worries.

I'm going to enjoy this moment, And savor every second.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Outro) I'm going to keep walking, And keep enjoying this beautiful day.

I'm going to live in the moment, And be grateful for all that I have.

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Audience

Professional women 40-60

Song-2

Verse 1:

Generated by

Walking in the stream, with the sun setting low

ChatGPT

The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Verse 2: The water's so cold, but we don't mind We'll keep on walking, until we find A place to rest, and watch the sky turn pink With your hand in mine, I don't need to think Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Bridge: The world's a mystery, we'll unravel it together With every step we take, we're getting closer to forever We'll hold on tight, never letting go Watching the river flow

Chorus: You and I, we'll chase the sunset

43

Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Outro: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me.

Note. Table C1 provides messages for the audience

The next step was randomly selecting one group of 30 from the population of 50 women. Group had 30 professional women in the desired category of age 40-60.

Method Survey: Which song do you like Song-1 or Song-2?

A t-test is not the appropriate test to use in this situation, as the data are categorical, and the proportions of the two options are not independent.

Instead, we can use a chi-square independence test to determine if Option A's proportion is significantly different compared to B. Here's an example of how to do this in Python: Result: Song-1 = 7/30 Song-2 = 23/30 H0: No difference in proportions HA: There is a difference in proportions Confidence level = 0.95 Python: The proportion of Option B is significantly different from 50% (p-value = 0.003)

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R Result: 1-sample proportions test with continuity correction

data: 7 out of 30, null probability 0.5 X-squared = 7.5, df = 1, p-value = 0.00617 alternative hypothesis: true p is not equal to 0.5 95 percent confidence interval: 0.1063502 0.4270023 sample estimates: p

0.2333333

Another way is to run R code prop.test(x=23, n=30, p=0.5, correct=FALSE, alternative="greater") R Result: 1-sample proportions test without continuity correction data: 23 out of 30, null probability 0.5 X-squared = 8.5333, df = 1, p-value = 0.001744 alternative hypothesis: true p is greater than 0.5 95 percent confidence interval: 0.6209739 1.0000000 sample estimates: p 0.7666667 The result from the programming language R 1-sample proportions test: 76.67% of women would prefer Song-2 p-value = 0.001744, and therefore, we can reject null

45

hypothesis H0 and accept alternative hypothesis HA. The result of the Survey was statistically significant at a 95% level with a CI (confidence interval) CI=(0.621, 1.000).

Table A2 Table A2 provides questions Bard and ChatGPT Question for

I ran a survey song and asked respondents to choose between option A or Option B. 7/30 chose option A and 23/30 chose Option B. The sample size is 30.

How do I determine if the % selection Option A is statistically significant? What test do I run in Python and how? t-test?

Python code ChatGPT

# A t-test is not appropriate in this case because the data are categorical, and the #proportions of the two options are not independent.

import scipy.stats as stats

# Define the observed frequencies observed = [7, 23]

# Define the expected frequencies under the null hypothesis of equal proportions expected = [15, 15]

# Perform the chi-square test chi2_stat, p_val = stats.chisquare(observed, expected)

# Print the test results if p_val < 0.05:

46

print("The proportion of Option B is significantly different from 50% (pvalue = {:.3f})".format(p_val)) else: print("The proportion of Option B is not significantly different from 50% (p-value = {:.3f})".format(p_val))

exit(24)

The proportion of Option B is significantly different from 50% (p-value = 0.003) Python code Bard

To determine if the 7% selection of option A is statistically significant, you can use a two-sample t-test. The two-sample t-test is a statistical test that is used to compare the means of two independent samples. In this case, you would be comparing the mean of 7% selecting option A to the mean of 50% selecting option A (if there was no difference between the two options).

To run the two-sample t-test in Python, you can use the scipy.stats.ttest_ind function. The syntax for this function is as follows:

scipy.stats.ttest_ind(x, y, equal_var=False) where x is the first sample, y is the second sample, and equal_var is a boolean flag that indicates whether the variances of the two samples are assumed to be equal.

The output of the scipy.stats.ttest_ind function is a tuple of four values: the t-statistic, the degrees of freedom, the p-value, and the confidence interval. The tstatistic is a measure of how different the means of the two samples are. The degrees of freedom are the number of independent pieces of information in the data. The pvalue is the probability of obtaining a t-statistic at least as extreme as the one you observed if there was no difference between the means of the two samples. The

47

confidence interval is a range of values that is likely to contain the true difference between the means of the two samples.

To interpret the results of the two-sample t-test, you need to look at the pvalue. If the p-value is less than your chosen significance level (typically 0.05), then you can reject the null hypothesis that there is no difference between the means of the two samples. In other words, you can conclude that the 7% selection of option A is statistically significant.

Here is an example of how to run the two-sample t-test in Python:

import scipy.stats

x = [7] y = [23]

t, df, p_value, confidence_interval = scipy.stats.ttest_ind(x, y)

if p_value < 0.05: print('The 7% selection of option A is statistically significant.') else: print('The 7% selection of option A is not statistically significant.')

This code will print the following output:

The 7% selection of option A is statistically significant.

Question for

I ran a survey song and asked respondents to choose between option A or Option B. 7/30 chose option A and 23/30 chose Option B. The sample size is 30.

48

How do I determine if the % selection Option A is statistically significant? What test do I run in R and how? t-test?

ChatGPT

#No, you cannot use a t-test to determine if the proportion of respondents who chose #Option A is statistically significant because the data is not normally distributed. #Instead, you can use a one-sample proportion test in R

# Define the observed proportion of respondents who chose Option A p_obs <- 7/30

# Perform the one-sample proportion test prop.test(x = 7, n = 30, p = 0.5)

# Alternative syntax: # prop.test(x = sum(responses == "Option A"), n = length(responses), p = 0.5)

In this example, we first calculate the observed proportion of respondents who chose Option A and store it in the p_obs variable.

We then use the prop.test() function to perform the one-sample proportion test. The x argument is the number of respondents who chose Option A, the n argument is the total sample size, and the p argument is the null hypothesis proportion of Option A, which is 0.5 (i.e., assuming equal proportions of Option A and Option B). By default, the test uses a two-sided alternative hypothesis.

The output of prop.test() includes the test statistic (z-value), the p-value, and a confidence interval for the proportion difference. If the p-value is less than 0.05,

49

we can reject the null hypothesis and conclude that the proportion of Option A is significantly different from 50%.

Note that the one-sample proportion test assumes that the responses are independent, and that the number of successes and failures in the sample are both at least 5. In addition, it assumes that the null hypothesis proportion is known and fixed.

Result from R

1-sample proportions test with continuity correction

data: 7 out of 30, null probability 0.5 X-squared = 7.5, df = 1, p-value = 0.00617 alternative hypothesis: true p is not equal to 0.5 95 percent confidence interval: 0.1063502 0.4270023 sample estimates: p 0.2333333

Note. Table C2 provides R and Python code for stats.

Python code from Bard is not working out of box.

Appendix D Appendix D provides Python code for document similarity plus ChatGPT and Bard generated code.

Table D1 Table D1 provides code for document similarity in Python

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Python Code generated by ChatGPT

The question for both was: Python code for document similarity. # -*- coding: utf-8 -*# !/usr/bin/python

import string from sklearn.feature_extraction.text import CountVectorizer from sklearn.metrics.pairwise import cosine_similarity

doc1 = """ (Verse 1) I'm walking by the river, The sun is setting low.

The wind is playing with my hair, And I'm feeling so at peace.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Verse 2) I'm walking in the stream, The water is cool and clear.

I feel so alive, And I know that I'm free.

51

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Bridge) I'm going to take a deep breath, And let go of all my worries.

I'm going to enjoy this moment, And savor every second.

(Chorus) I love the sound of the river, The smell of the fresh air.

I love the feeling of the sun on my skin, And the wind in my hair.

(Outro) I'm going to keep walking, And keep enjoying this beautiful day.

I'm going to live in the moment, And be grateful for all that I have. """ doc2 = """ Verse 1: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow

52

Playing with your hair, like a melody I can't help but feel alive, when you're here with me

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Verse 2: The water's so cold, but we don't mind We'll keep on walking, until we find A place to rest, and watch the sky turn pink With your hand in mine, I don't need to think Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget The wind in our hair, as we run so free We'll find our way, like a river to the sea

Bridge: The world's a mystery, we'll unravel it together With every step we take, we're getting closer to forever We'll hold on tight, never letting go Watching the river flow

Chorus: You and I, we'll chase the sunset Dancing in the light, we'll never forget

53

The wind in our hair, as we run so free We'll find our way, like a river to the sea

Outro: Walking in the stream, with the sun setting low The river rushes by, and the wind starts to blow Playing with your hair, like a melody I can't help but feel alive, when you're here with me. """

# Remove punctuation and convert to lowercase translator = str.maketrans('', '', string.punctuation) doc1_clean = doc1.translate(translator).lower() doc2_clean = doc2.translate(translator).lower()

# Tokenize the documents vectorizer = CountVectorizer().fit_transform([doc1_clean, doc2_clean]) doc1_tokens, doc2_tokens = vectorizer.toarray()

# Compute the cosine similarity between the tokenized documents similarity = cosine_similarity([doc1_tokens], [doc2_tokens])[0][0]

print("The similarity between the two documents is:", similarity)

exit(2)

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Pyhon Code generated by ChatGPT

# Sure, here is a Python code for document similarity: import nltk from nltk.tokenize import word_tokenize from nltk.corpus import stopwords

def get_document_vector(document): """Gets the vector representation of a document.""" # Tokenize the document into words. tokens = word_tokenize(document)

# Remove stopwords from the tokens. stop_words = set(stopwords.words('english')) tokens = [token for token in tokens if token not in stop_words]

# Create a bag of words representation of the document. bag_of_words = {} for token in tokens: if token in bag_of_words: bag_of_words[token] += 1 else: bag_of_words[token] = 1

# Return the bag of words representation of the document. return bag_of_words

def get_document_similarity(document1, document2): """Gets the similarity between two documents.""" # Get the vector representations of the documents.

55

vector1 = get_document_vector(document1) vector2 = get_document_vector(document2)

# Calculate the cosine similarity between the vectors. similarity = cosine_similarity(vector1, vector2)[0, 1]

# Return the similarity. return similarity

Note. Table D1 Python code.

The similarity between the two documents is: 0.6553365119417301.

The Python code from Bard is not working out of the box.

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Protocol of Publication LIGS University Filled in by the evaluating lecturer: Approved by (lecturer’s name)

PhDr. Peter Jan Kosmály, PhD.

Turnitin check (Lecturer will add this information)

0% (original published content)

Evaluation of article on scale from 1-10 (10 is the best): Content

10

Formal criteria, language, grammar

10

Overall evaluation

10

Overall feedback (approximately 100 words):

The paper examines the areas of content writing within women´s businesses and the impact of AI chatbots on producing marketing communication. The paper uses a mix of quantitative methods (content analysis of chatbot´s production) and qualitative methods (user´s evaluation of the AI-produced content). The research problem and related terms are very well described, the methodology used is explained and the results were formulated into recommendations. The paper is a part of the author´s other papers on related problems within the same topic - how can new marketing methods, such as artificial tools for producing content, change or influence local enterprises or whole specific types of businesses (women's business). The benefits of the paper include both theoretical (research problem, scientific methods, conclusions, discussion) and practical (clear explanation, advice, conclusions).

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About the Authors

Carolina M. Billings, Ph.D. (C) Carolina M. Billings, Ph.D. (C), is completing her Marketing Doctorate (at Dissertation) from LIGS University, Hawaii. Her Research and Dissertation focus on Leveraging Technology and Aggregates for Women’s Entrepreneurship’s Success. She earned her MA-IS with a focus on Leadership, Communications, Strategic Change and Conflict Resolutions from Royal Roads University in Canada. Ms. Billings is an accredited Certified Human Resources Leader CHRL with the Human Resources Professional Association of Canada and a Senior Human Resources Professional SHRP-SCP with the Society of Human Resources Professionals in the United Estates. As a lifelong learner, Ms. Billings holds Postgraduate Diplomas from Ivey Business School at Western University, Queens University, and the University of Toronto.

A former CFO/CHRO, Ms. Billings is the Founder and CEO of The Hive Consulting Group Inc. dba Powerful Women Today ™. Powerful Women Today is a boutique accelerator and global community of highly influential women entrepreneurs and professional women who want to make a difference in the world by showcasing their voice, expertise, talents, experience and passion through publishing, coaching, speaking, social justice and social impact. PWT’s mission and vision are to champion and empower women’s emotional and financial independence.

Jiri Medlen, Ph.D. Jiri Medlen, Ph.D. is an accomplished researcher with a diverse academic background. Born in former Czechoslovakia, he holds a Ph.D. in Management from LIGS University, Hawaii. Before that, he earned an MS in Electrical Engineering and Computer Science and a Postgraduate Diploma in Data Science from Columbia Engineering.

Jiri has contributed to his field as a research scientist, with several of his articles published in journals. His research interests include organizational behaviour, strategic management, and entrepreneurship. He is particularly interested in exploring how organizations can effectively leverage technology and data to improve their performance.

When he's not busy conducting research, Jiri enjoys spending time in the great outdoors. He is an avid hiker and finds solace in the natural world. Additionally, Jiri is a passionate soccer fan and enjoys playing the sport in his free time.