I am taking a Course at https://education.gale.com/l-tplmain/. My course in called Introduction to Artificial Intelligence. GALE has many College level course on many subjects which are free with your Library card.

There are various forms of artificial intelligence (AI). Business, the Arts and Industry are being transformed or disrupted by AI implementations such as natural language processing, forecasting, and robotics. Especially in the Arts, there are ethical factors in AI deployment.

The course Instructor, David Iseminger, is an author and technology veteran with expertise in computing, networking, wireless and cloud technologies, data and analytics, artificial intelligence, and blockchain. While with Microsoft, David worked on early versions of Windows and its core networking infrastructure, transmission protocols, security, data visualizations, and multiple emerging cloud technologies.

I was so far over my head here that I was treading water and near drowning. Aside and apart from that, I have some personal experience with AI both as an amateur writer and in the use of AI to create illustrations for short stories I have written. P.S. I passed the Course

Graphic Arts

One story I wrote was about a Housebot, a robot for cleaning house which was also a mechanism for spying. It’s not a great story but why I mentioning it is to illustrate the use of AI as a co-creator.    https://soniabrock.com/HB-21.html

First of all I made the illustration using Illustration by Image Creator from Microsoft Bing

I told Bing I wanted a small image of a Robot shaped like a garbage can with arms and fingers and a small red knob on top. Bing gave my several examples and gradually we, together narrowed down the appearance until we got to one I could use. It’s not hard to do. You just have to be very specific telling the AI image creator exactly what you want. Seems fairly harmless, doesn’t it. Hold that thought. Let’s look at some ramifications for the Arts.

• Any number of graphics programs will let you manipulate images.
  
  
• Amateur ‘artists’ are using AI image manipulation to put the faces of celebrities and persons known to them on bodies stolen from pornography. That’s the lower side of this new technology. When you combine bad humans with AI you add a while new dimension to alternate reality. The 'artists' in this case are bad guys but they are still being creative. Mikhail Bakunnin, an old time Russian revolutionary anarchist and philosopher, said "Destruction is a creative urge!"
  
  
• Faces you see online are beautified. The real owner is made artificially glamorous. That’s fairly harmless but you might get a shock if someone you connect with on an online dating service is much less attractive in person.
  
  
• Fake news videos and images show us things that never really happened, That’s a more serious use of the graphical side of artificial intelligence.
  
  
• Hollywood loves CGI (Computer-generated imagery) Saves the a lot of money and distorts reality. It’s a lot easier to send a computer generated car over a cliff and you save a fortune in props and stuntmen.
  
  
• Dead actors can be brought back to screen life with a suitable fee paid to the descendents, and so it goes.
  
  
• According to WIRED magazine YouTube is launching features that allow creators to use AI to generate visuals (e.g. putting people / scenes into fantasy settings) turning audio/podcast content into richer video-style content using AI.

  If broadly adopted, these tools could enable many more people to produce content, or produce content faster, bypassing traditional production costs.
  Current human?filmed/videoed content could thus shift to AI?assisted or AI-created video.

Acting:

Let’s go on to voice acting. I used to do some Podcasting and it was a lot of work writing scripts and getting the vocals just right. Nowadays I can write a script and get an AI program to read it for me. Here’s the link to a free online voice generator. <https://voicegenerator.io/>

That’s kind of fun. Not so much fun if you’re a voice actor and https://www.audible.ca/ is using AI to read a book to add to their list of literary items instead of paying a real live actor.

AI can replicate the human voice and make a politician or a doctor or anybody say whatever they want.

Writing:

Let’s start small and talk about auto-correct. Microsoft Word and other writing programs now come with auto-correct installed.
It can correct your spelling and suggest words, sometimes with humorous results. Punctuation is added or corrected.
That’s very handy but you need to keep a critical eye on it.

I am an amateur writer. Sometimes I can’t untangle a sentence to make it clearer. The temptation is great to pop it into ChatGPT and ask the AI to rewrite it, which it does a nice job of in a bland sort of way, or not, as in the following example where I used ChatGPT; telling it to rewrite a paragraph in the style of Edgar Rice Burroughs

"I got a granny phone call from someone who purported to be my daughter. AI had duplicated her voice and she needed money right away due to an arrest from a vehicle accident involving alcohol. My daughter doesn’t drive or drink. She’s a Buddhist nun."

The Artificial Intelligence wrote:
"More gravely still, there came to me a voice borne across the mysterious ether—a voice I knew as my daughter’s own. Yet it was but a cunning phantom, wrought by some strange artifice of this new age of sorcery we call artificial intelligence. With pleading urgency it declared that she lay in peril, ensnared by the law after a drunken calamity upon the highway. But I, who know her heart, knew it could not be. She touches neither wine nor wheel, and walks the world as a sworn disciple of the Buddha. Thus I discerned the trickery, though the echo of her voice chilled me to the marrow."

Thus, you see, AI can write some really purple prose!

That’s amusing but it’s not so amusing when a real magazine received hundreds and hundreds of AI written Science Fiction stories which swamped their editorial staff. None were publishable. The magazine had to stop receiving submissions for a time and legitimate writers were thus shut out along with the AI fakes.

Newspapers have published articles written by Artificial Intelligence under the direction of a lazy reporter and these articles were, in part, fantasy - not based in real time events and with false quotes and references. AI doesn’t know the truth from false information. It just scrapes available references from the Internet and some of these references come from crackpot conspiracy theorists. For instance, Elon Musk has been modifying his GROK AI tool to be more conservative in it’s replies.

There has been court action in this regard, OpenAI, a 63.92 Billion dollar AI model developer, and others devour copyrighted fiction and non fiction books and newspapers, such as the NY Times, to base their Large Language Models on.

“Large language models (LLMs) are advanced AI systems designed to understand and generate human language by analyzing vast amounts of text data. They use deep learning techniques to predict and create coherent text based on the context provided.”

That’s how the former rewrite example was developed. It ‘read’ all of the Tarzan, etc. books by Edgar Rice Burroughs and copied his style based on his common use or words and phrases to produce the fake version of the quote I requested.

Ai isn’t just taking from literature. It also takes from you the audience.

If you have a smart TV, remember it is observing you and your likes and dislikes. Every online store is recording what you buy and from where. Every social media platform whether it be Facebook, Instagram, Whatsapp or YouTube is doing the same. Sure, it’s to find out what you like and sell you more but, more than that, you have been quantified for the purposes of control.

Dystopia or Utopia? We are about to find out. We are living in a controlled environment.

Footnote from my online Artificial Intelligence course:

#The principal constraint in robotic implementations is the need for a controlled environment. Robots use a set of rules, both to carry out their programmed tasks and to interact with their surroundings. Since these rules are rather limited (historically by restrictions such as memory capacity and today by the sheer scope of programming them), a robot needs to perform in a controlled environment.#

I asked AI for it's take on AI & the Arts

In bullet point form how is AI affecting the Arts?

Here's a clear breakdown of how AI is affecting the Arts, in bullet point form:

" Creative Collaboration: Artists use AI tools to generate ideas, images, music, or text, often as a springboard for human refinement.

" New Art Forms: AI enables generative art, algorithmic music, and interactive installations that weren't possible before.

" Accessibility: AI tools help people with limited technical skills (or disabilities) create visual art, music, or literature more easily.

" Speed & Efficiency: Automates repetitive tasks
(e.g., background generation, video editing, color correction) so artists can focus on core creativity.

" Personalization: Allows tailored experiences (e.g., AI-generated music that adapts to a listener's mood or visuals customized to an individual).

" Restoration & Preservation: Used to restore old films, artworks, and recordings, filling gaps with AI-based reconstructions.

" Cultural Democratization: Lowers barriers for entry into the arts, letting more people produce and share creative works.

" Ethical & Legal Challenges: Raises questions about copyright, authorship, and the ownership of AI-generated works.

" Economic Disruption: Impacts creative industries by replacing or undercutting traditional roles (illustrators, voice actors, etc.).

" Blurring Human vs. Machine Creativity: Challenges definitions of originality, authenticity, and what it means to be an "artist."


AI asked: Would you like me to expand this into short real-world examples (e.g., visual art, literature, music, film) so it's more concrete?

Here's a bullet point list of how AI is affecting the Arts, with real-world examples:

" Visual Arts & Design
o AI tools like DALL·E, MidJourney, and Stable Diffusion generate original images, paintings, and concept art from text prompts.
o Fashion brands (e.g., Tommy Hilfiger) use AI to design collections and predict trends.
o Obvious Collective's AI portrait "Edmond de Belamy" sold at Christie's for $432,500 in 2018.

" Music
o AIVA and Amper Music create film scores and background tracks with minimal human input.
o Pop artist Grimes released an AI-voice platform ("Elf.Tech") allowing fans to generate songs in her voice with her approval.
o AI models recreate voices of deceased artists (e.g., The Beatles' "final" song in 2023 using AI to isolate Lennon's vocals).

" Literature & Writing
o Writers use AI (e.g., ChatGPT, Sudowrite) for brainstorming plots, editing, or generating poetry.
o AI has co-written short stories and screenplays-"Sunspring" (2016) was the first AI-written short film script.
o Publishers face controversy over AI-generated books flooding platforms like Amazon Kindle.

" Film & Animation
o AI tools such as Runway Gen-2 generate video clips from text prompts, used by indie filmmakers for experimental projects.
o Major studios use AI for de-aging actors (e.g., Harrison Ford in Indiana Jones and the Dial of Destiny).
o AI dubbing tools (like Papercup) automatically translate and lip-sync films for global release.

" Theatre & Performance
o AI-generated scripts have been staged in experimental theatre, exploring machine creativity.
o Dance choreographers use motion-capture AI to generate new movement patterns (e.g., projects at MIT's Media Lab).
" Cultural Preservation
o AI restored Beethoven's unfinished 10th Symphony in 2021, allowing it to be performed.
o Museums like the Mauritshuis used AI to recreate missing parts of Vermeer's "Girl with a Pearl Earring."

" Photography & Journalism
o AI image generators have won awards (e.g., Boris Eldagsen's AI photo at Sony World Photography Awards, which he declined).
o Newsrooms experiment with AI-written articles, raising questions about authenticity and creative labor.

Here’s a clear glossary of AI terminology—concise but detailed enough to serve as a reference.

Core Concepts
Artificial Intelligence (AI): The field of creating machines that can perform tasks requiring human-like intelligence, such as reasoning, learning, and problem-solving.
Machine Learning (ML): A subset of AI where systems learn patterns from data instead of being explicitly programmed.
Deep Learning (DL): A branch of ML that uses multi-layered neural networks to process complex data like images, audio, and natural language.
Neural Network: A computational model inspired by the brain, made of layers of “neurons” that process and transform data.
Natural Language Processing (NLP): AI techniques for understanding, interpreting, and generating human language.
Computer Vision: The ability of AI systems to interpret and understand visual input (images, video).

Data & Training
Dataset: A structured collection of data used to train or test AI systems.
Training: The process of teaching a model by adjusting its parameters based on data.
Validation / Test Set: Data reserved to check how well a trained model generalizes to unseen inputs.
Overfitting: When a model learns training data too well, including noise, and performs poorly on new data.
Underfitting: When a model is too simple to capture patterns in data.
Feature: An individual measurable property or characteristic used in training a model.
Label: The correct answer or outcome used to supervise learning (e.g., "cat" in a cat/dog classifier).

Types of Learning
Supervised Learning: Training a model with labeled data (input + correct output).
Unsupervised Learning: Training without labels, focusing on finding patterns or clusters.
Reinforcement Learning (RL): Learning through trial and error, using rewards and penalties to guide behavior.
Self-Supervised Learning: A method where the system generates its own training labels from raw data (common in large language models).

Models & Techniques
Transformer: A deep learning architecture central to modern NLP (e.g., GPT, BERT).
Large Language Model (LLM): AI trained on vast text data to predict and generate human-like language.
Generative AI: AI systems that create new content (text, images, audio, video).
Embedding: A numerical representation of data (words, images, etc.) in a dense vector space.
Attention Mechanism: A method that helps models focus on relevant parts of the input data.
Fine-Tuning: Adjusting a pre-trained model for a specific task with additional training.

Performance & Evaluation
Accuracy: Percentage of correct predictions out of total predictions.
Precision: How many of the predicted positives are actually positive.
Recall: How many actual positives were correctly identified.
F1 Score: A balance between precision and recall.
Bias: Systematic errors in AI predictions, often due to skewed training data.
Fairness: Efforts to ensure AI treats groups equitably and avoids harmful discrimination.
Infrastructure
GPU (Graphics Processing Unit): Hardware commonly used to accelerate AI model training.
API (Application Programming Interface): A way for developers to connect software to AI models.
Cloud AI: AI services provided over the internet (e.g., AWS, Google Cloud, Azure).

Ethics & Safety
Alignment: Ensuring AI systems act according to human goals and values.
Explainability (XAI): Making AI decision-making processes transparent and understandable.
Hallucination (in LLMs): When a model generates false or fabricated information.
Autonomy: The extent to which AI can operate independently without human oversight.
Singularity: A hypothetical future point where AI surpasses human intelligence.