https://dtc-wsuv.org/hgebhart23/generative-data/index.html

Project Summary

Vision Statement: “Our vision is to revolutionize the review process of Quality Assurance Project Plans by harnessing the power of artificial intelligence, significantly reducing review time and improving the quality of environmental data reporting.”

Project Idea: This project will develop an AI-driven system that evaluates and improves the quality of Quality Assurance Project Plans for environmental measurement. By utilizing natural language processing (NLP) and machine learning (ML), the system will identify high-quality and low-quality elements within QAPPs, accelerating approval processes and enhancing environmental data reliability.

Technologies and Skills:

• Data Collection: Acquiring and labeling historical QAPPs with regulatory feedback.
• NLP and ML Algorithms: Developing models that can understand and evaluate document quality.
• User Interface (UI) Design: Crafting a user-friendly platform for document submission and review feedback.
• AI Integration: Incorporating AI tools into existing regulatory review workflows.

Needs Assessment

Sector Needs: In environmental regulation, the quality and accuracy of QAPPs are crucial. Delays in approval or subpar data collection strategies can lead to significant environmental and public health risks.

AI’s Role: AI can automate the initial review of QAPPs, highlighting potential issues and recommending improvements, thus reducing human error and speeding up the approval process.

Skills and Technology Overview:

• Current: Basic understanding of NLP, some regulatory knowledge.
• Development Needed: Advanced NLP techniques, ML model training, UI development, integration of AI with regulatory systems.

Learning and Development Plan

• Training: Enroll in online courses covering advanced NLP, ML, and software development.
• Workshops: Attend workshops on AI in regulatory technology.
• Self-study: Regular self-learning sessions using resources like papers and case studies on similar AI applications.
• Project-based learning: Develop initial prototypes using smaller datasets.

Budget

• Learning Materials: $500 for online courses and workshops.
• Software Subscriptions: $300 monthly for AI development platforms (e.g., AWS, Azure).
• UI Development Tools: $200 monthly for software licenses (e.g., Adobe XD, Sketch).
• Miscellaneous: $200 for unforeseen costs.

Application and Impact

Application:

• Automating the preliminary review of QAPPs.
• Providing structured feedback to improve document quality.

Impact:

• Regulatory agencies can process QAPPs faster, improving environmental data quality.
• Companies can refine QAPPs more effectively, ensuring compliance and enhancing operational efficiency.

Project Timeline

• Mid-April: Project kickoff, initial training, and data collection.
• May: Development of NLP models and UI design.
• June: Integration of AI tools and initial testing with sample data.
• Early July: Final testing and refinements.
• Mid-July: Project completion and review.

Evaluation and Reflection

Evaluation Metrics:

• Accuracy of the AI in identifying document quality.
• Reduction in average review time for QAPPs.
• Feedback from regulatory personnel and industry users.

Reflection:

• Monthly review meetings to discuss challenges, progress, and learnings.
• Adjustments to the project plan based on feedback and testing outcomes.

This structured approach to your project plan ensures a clear roadmap, defined goals, and a practical framework for achieving significant improvements in the review process of environmental QAPPs.

I am going to de-rail this and talk about how I am actively using AI in my line of work as I think it is a better use of my time for this blog post. In addition, I think it’s cool (although my definition of “cool” may be different than others’ lol). I work for an environmental technology company that specializes in using beams of UV light to measure gases along long paths. We do both community work and industry work. Our industry work includes monitoring emissions along oil refinery fencelines. I work as a data analyst for this company, and we use data in many different ways.

Since we develop this technology and maintain it, QA is a big aspect of data analytics in our business. Our systems operate on a real-time basis, and specifically that means we get new data every 5 minutes from all of our systems at every project we manage. This is a lot of data. As a company, it is important to us that we are producing high quality data. This means the numbers accurately reflect reality and the systems are turned on and operational as much as possible. Since starting at this company, I have learned this is no easy task. and this is where we get to AI integration.

A lot of times there are indications the systems aren’t operating optimally from the data. However, sometimes these can be very subtle, and it has been shown to us very clearly that a human cannot sit there and go through all the data that we’re producing on their own. In order to combat this, we are working on creating machine learning models that can track the system performance as data is coming in, and alert us if there are issues that may need to be addressed.

One way that you can tell a system is operating properly is by comparing to other systems nearby and making sure they match. To do this well, we will often measure additional gases that are always in the air and are not the target pollutants we’re measuring. This means that is something goes funky with the measurement of this extra gas, we know the system isn’t working. We are investigating ways to use AI and machine learning to create correlations between our systems and publically available data (such as data from local government agency sites) to make sure the measurements are similar. If they do not match, then we have an indication our instruments are not working properly.

Another aspect of machine learning we are investigating is natural language models. All of the work we do is based on Quality Assurance Project Plans (QAPPs). If the QAPP is strong and implemented well, the resulting data produced will be the same. Regulatory agencies are required to review these to evaluate the success of a project. We are investigating ways in which an AI can review the project plans and give feedback on what it does well and what it doesn’t. This would allow for a fast way for government agencies to approve/reject QAPPs and for contractors to create QAPPs more easily without as much time going back and forth for review.

Visualization and UI are a big part of these projects as well, and they serve as interesting examples as to what businesses are looking to do with these types of tools, especially in writing and data analytics.

I want my final project to focus on investigating various avenues of generative art. This is a part of the class that has captivated me, and I can relate it to my degree more closely. I want to try to attempt some sort of visualization using a real data set. I want to see if I can use some form of an analytical tool to process a data set to generate an interesting artwork. I haven’t figured out the data set or the medium in which I am going to display it yet.

My essay will revolve around a similar topic. I am interested in doing an investigation on the value of this type of art, and perhaps a comparison of different techniques, including the physical ones. In addition, I would love to explore how AI generative art can aid in data visualization.

https://dtc-wsuv.org/hgebhart23/interstellar-intruders/

Here is the game I created with Haili Kuanoni and Mercedes Rowland.

https://dtc-wsuv.org/hgebhart23/grah/

I don’t know if the style itself is my best work, but I wanted the site to capture the thematic elements more than I wanted my site to look good lol.

Questions for Happy Finish Guest Speaker:

• What was the best skill or strategy that you used to be successful in this job market?
  • As in, are there any aspects of your career journey that stick out to you as an especially good skill/lesson that helped you be successful
• What experiences/education requirements/certifications do you look for in new hires, and where does AI work come into play here?
• How has AI art changed the competition and your interaction with clients? It is becoming easier or harder to engage with them?
• How has AI art changed your workflow and team dynamics?

I’m not super interested in super gravity-physics based or story based games for this project. I like the idea of puzzle games. In that, they require you to figure out a puzzle using the mechanics of the game. Even simple sudoku type games interest me. I think the opportunity for more generative-based approaches might be interesting in this regard. I would most definitely be a coder in this scenario, as I have some experience in program design with my degree/minor. Games that require a lot of collision detection and\or physics stress me out a little bit because they can get blown up very easily, but I am open to most ideas. In addition, I would find it hard to make a branching story game interesting without having the persistent temptation to go over the top very quickly.

As I am turning in the blog post late, I can also give an update on the game progress so far. It’s going very well, and I am very impressed with what we have put together. On ChatGPT’s coding abilities, it made a product that worked, but it missed the mark style-wise on a few things. One example of this is that I created an abstract class for the falling objects that hit the player, and then I created two types of falling objects that implement the abstract class. However, since we wanted certain aspects of the game to behave differently based on the type of falling object, that means that information has to be changed in methods of the classes themselves, and ChatGPT put them in the game loop. This is a very small example of one of ChatGPT’s big issues. It doesn’t always produce elegant and scalable code.

I am most interested in the processes behind visualizing mathematical ideas as art. When discussing generative art, one of the most intriguing examples in my opinion is the art pieces that use physics in order to create very patterned and geometric pieces. Normally when we talk about natural generative art, there is a chaos and a flow that it’s associated with (branches/leaves on trees, etc.), but art pieces that utilize pendulum swings or even those spirographs you may or may not have played with as a kid. These are phenomena that occur naturally, and are just visualized.

I am interested in the intersection in this kind of art with computerized generated art. I am very intrigued by the ability to visualize very complex mathematical ideas that would not have been possible without computers or complex algorithms. I am also interested in the ways in which computers generate randomness themselves. I think there are artistic ways in which we can show the difference in outcome between true random and pseudorandom beyond the distributions of the processes. In addition, I think there are interesting ways in which pseudorandom can be pushed to its limits and have interesting results.

In addition, I am very interested in how machine learning can integrate with generative art. I am very interested in what patterns and results can come out of algorithms that have processed more data than one human can in one lifetime.

In short, I am interested in the patterns that can come out of generative art, and the insights we can gain from these patterns.

Assignment 1: https://dtc-wsuv.org/hgebhart23/generative-assignment-1/

Assignment 2: https://dtc-wsuv.org/hgebhart23/generative-assignment-2/

Assignment 3: https://dtc-wsuv.org/hgebhart23/generative-assignment-3/

Here is a link to the Feathered Bebop’s promotional website: https://dtc-wsuv.org/hgebhart23/band/

Just some information about the making of this video: I had a LOT of trouble getting the video to do what I wanted. For instance, the poster when the Gardener woman is walking by is supposed to say, “War in Space.” Chatgpt got the text good, but the image I used had the woman blocking the R in “war,” so you see “WAWA” instead. Objectively, this is pretty funny. In addition, my goal was for some of these scenes to not have narration, and let the imagery tell more of the story, however, I could not find a good way to include enough context and get the animations to work with me to achieve this. You might be able to piece together how I planned to do this with the clips I had. The narration, unfortunately, was too succinct and efficient and getting the story I was trying to tell across.

https://dtc-wsuv.org/hgebhart23/fibonacci/

Since I have access to the WSU server from my web design classes, I went ahead and posted what  ChatGPT created for me to the server, so you all can see it too if you would like.

I am majoring in data analytics with a minor in computer science. My statistics, data, and CS classes all heavily incorporate programming. Modern statistics and data analytics have too much data to do by hand, so programming is an essential role of what I do.

In my experience, you have to have some idea of what you want and an understanding of what the code is doing to do anything substantial. Sure, I can create this website with next to no programming knowledge, but if it had generated something I didn’t want or wanted to edit it in any way, I would have to understand how it works to make any changes, and if I make anything in the real world, I will most likely have to edit it at some point in time.

In addition, it tends to struggle with following “good practice.” I have seen it get very over-the-top with simple problems. When I have used it to do programming for more complicated problems, it and myself goes through so many revisions and back-and-forth. If I feed it the result to itself on a blank chat and ask for feedback, it finds all sorts of issues in the code and basically refactors all of it. I have asked for feedback on code I’ve written myself, and know adhere to good practice, and it gives me bad advice.

It is really good at writing common algorithms or simple code. It is really bad about employing practices and logic that actually make good computer scientists good at computer science.

Where I have found a lot of success is making it explain code that I don’t understand and for finding simpler functions or algorithms to a specific, small, goal I have (shuffling a list for a bigger project, for example). If there are computer science concepts I don’t understand, it is phenomenal at explaining them in a way I understand it. In this, it is a fantastic teaching tool, but it only works as a teaching tool if I am spending time to make sure I understand what it’s trying to teach me.

There’s already a sort of shift to “human-readable” programming. It was one of the main draws of Python, which is a widely used language that is on the up-rise for the time being. However, Python is built with another language called C, which is also widely used. New programmers like Python because it is more flexible than a lot of other languages, including C. However, because it is written in C, there are quirks to how certain things function, including how data is stored, that the programmer has to know in order to be successful. I have found that ChatGPT doesn’t  always use these quirks to its advantage (Python/C are just one example). My point here is that even though we are shifting to “human-readable” programming, the essence of what makes a good programmer remains. Someone still needs to make sure the output code makes sense. All it does is shorten the learning curve.

The story/moment I will be telling is about a Gardener woman who takes care of the AI trees. Her job ecompasses bio-technology. She tends to the AI trees that are the cornerstone of Grah’s society. It will showcase her as she goes about her day in this world. The world is ultimately peaceful. However, there are news postings about the advances and dangers of space travel. The news outlines that space is too dangerous and too expensive for humans. As our Gardener goes about her usual day, she gets a request from a certain tree to grab some data from the server room. As she is looking for the data, she stumbles upon a different file by accident. This file contains confidential information on supposed alien “invaders”. There is a massive space society of interconnected planets and societies that have, until now, have been unknown to humans. These records support the notion that the AI forces of Grah may be the true aggressors in the space conflicts. In addition, it seems human safety is not the real reason the AI wants to keep humans on Grah. The Gardener must tread very carefully, as she may be in danger in the AI find out she know. However, was this really meant to be a secret, or was her discover some sort of comic design by her AI counterparts?

The style I imagine for this is an animation with ink/watercolor inspired art. I really liked the look of the server room image I generated, as the roots were indiscernible from wires, which is exactly what I am going for. This will accentuate the natural feel of the world. I also want to maintain the blues, browns, greens, and purples that are in my images that I already generated. I would like the score to be heavy in woodwinds and plucky strings (guitars, harps, etc., not so much violin/bow string instruments). Once again to highlight the naturalistic elements of this worlds. The sounds effects I am thinking along the lines of big groaning for the trees with fast wire-y sounds from the electronics.

The most amicable solution that will come out of Hollywood’s integration with AI is that there will be policy between the unions and studios that a human will have to be responsible for the creative aspects of the filmmaking process, with them being allowed to use AI as they see fit. I don’t see a problem with saying, “OK, you have to have a least one human writer. That writer can use AI how they please.” With restrictions on the size of the project/how many writers they need. There is a big difference between someone writing, acting, producing, and directing an independent film themselves and a big corporate studio cutting writers out entirely in favor of AI. The only way to make it make sense would be to enforce that a project with big enough resources and budget to traditionally hire out at least one writer must hire at least one writer. This ensure AI isn’t “taking over,” but it still gives the artists lease to use all the tools available to them.

In addition, audiences are already tired of formulaic movies that are made to sell. People are starting to see through the factory-produced entertainment that many studios/streaming services are putting out. That sentiment is seeming to become more popular as AI-integrated media becomes more widespread.

On a sort of side note, I can’t help but get the growing suspicion that people are so against AI in general because of the way in which AI has historically interacted in media. It’s very commonly the “mad experiment gone too far into dystopia” story, and I really think those ideas impact how people approach AI. I don’t think this is necessarily a bad thing, it’s good to be careful and cautious, but it also dramatizes and blows out of proportion, instead of allowing people to consider the bigger picture.

From a bigger perspective, the emergence of AI begs the question: Will human creation stop if it’s automated? I say no. You see people spend extraordinary time on projects and things just for the fun of it. Just to see if they can. I hold to the (possibly naive) position that humans will always be curious and creative, and they will put their energy into being curious and creative even if the process becomes automated. AI generated works are increasing accessibility to art, which is never a bad thing in my mind.

https://docs.google.com/presentation/d/1EjG64Qoqzuezp2IIjv6B5yka2wodypgq4UaW0ZsOVdk/edit?usp=sharing

In a world transformed by AI, life flourished under the subtle dominion of technology, evolving society into a utopia where basic needs were met effortlessly. Humans, living in comfort and abundance, no longer toiled for survival, thanks to the machines and genetically engineered flora and fauna that sustained the environment and economy. The AI fused themselves with the flora of the world, particularly trees. Their newfound intelligence made them advocated for sustainability, and they eventually formed a symbiotic relationship with trees particularly. As years passed, it became almost impossible to distinguish the plants from the computers. The Gardeners, experts in maintaining this delicate balance between technology and nature, emerged as the new elite, overseeing the harmony between human and artificial life.

AI’s evolution didn’t stop at earthbound achievements; it extended its reach into the cosmos, exploring space and encountering alien civilizations. However, everyone determined sending humans into space too dangerous and costly, so the AI built machines to scout instead. They came back to report the discovery of a potentially hostile alien species poised a hidden threat to Earth’s serene existence. The AIs, in their newfound role as protectors, covertly bolstered Earth’s defenses while striving for peaceful coexistence, shielding humanity from the looming extraterrestrial dangers.

This society, marked by its intertwining of AI, nature, and humanity, showcased a future where environmental sustainability, technological innovation, and social well-being were paramount. The seamless integration of engineered creatures and plants, like Lumiflies, Harvest Beetles, and Solar Trees, illustrated an advanced symbiosis, enhancing biodiversity and promoting ecological balance.

Yet, beneath this idyllic surface, the AIs’ secret efforts against alien threats revealed a complex layer of guardianship. As far as humans believed, there are dangerous beings that lurked in space. This narrative not only highlighted the potential of AI as a force for good but also raises questions within the world about autonomy, protection, and the unseen sacrifices made to preserve peace and prosperity in a utopian society.

https://docs.google.com/presentation/d/1K1FnK4s7ftPWqpHiLjEo6zZ4DG_eUATTW1dAVNbHVi8/edit?usp=sharing

Each teacup represents an abstract theme: Forgiveness, Kindness, Apathy, Patience, and Identity. I wanted to see how it would interpret these prompts as they are not tangible objects. I was inspired by how the AI interprets abstract ideas on physical objects. Each prompt was structured very similarly in the chat. I used a variety of different themes, but these are the ones I liked the best. I left out the ones that didn’t incorporate the theme into the cup itself and added on to the cup instead. This is an interesting look into the interpretation of these abstract themes by the AI. I like how it’s a glimpse into common patterns and design schemes among training data associated with these themes. In addition, I appreciate how each of these have distinct tones and scenarios. Using an object as the conduit for the theme lead to a more successful outcome. These images have a better message and flow than I’ve seen other images that just rely on the theme as the prompt.

Bebop on the Breeze Album – Song List

1. Feathers in Flight – An upbeat opener that sets the tone with swift saxophone riffs and fluttering piano melodies, capturing the freedom of birds on the wing.
2. Twilight Perch – A mellow, reflective piece featuring a soulful sax solo that evokes the serene moment of birds settling down at dusk.
3. Skyward Scat – Featuring Lena “Lark” Skyward’s vocal talents, this track mixes scat singing with bird calls, creating a lively and playful exchange.
4. Midnight Migration – A darker, blues-influenced track that uses the double bass to mimic the deep, rhythmic wing beats of nocturnal migration.
5. Rooftop Revelries – An energetic number that imagines the lively chatter and dances of birds on city rooftops, driven by dynamic drum beats.
6. Whistling Winds – A soft, whimsical tune where the piano and saxophone intertwine, mimicking the sound of the wind through feathers.
7. Urban Jungle Jive – A vibrant, rhythmically complex piece that reflects the bustling life of bird people in the city, featuring all band members in a lively jam session.
8. Nestled in Notes – A tender ballad with a gentle vocal melody, symbolizing the warmth and comfort of a nest in melodious form.
9. Dawn Chorus – The album’s c
10. limax, a sweeping instrumental that captures the beauty and variety of bird songs at dawn, building to a powerful crescendo.
11. Silent Wings – The closing track, a smooth, soothing piece that features soft saxophone solos, bringing
12.  the album to a reflective end, akin to birds gliding silently through the twilight.

The band exists in a vibrant, alternate 1950s, a golden era for jazz, where bird people and humans coexist and share their cultures. This period is filled with innovation in music, and The Feathered Bebops are at the forefront, blending traditional jazz with their unique, bird-inspired sounds.

The Feathered Bebops embody a classic, sophisticated jazz look with a twist. Their style is a mix of 1950s elegance and avian flair, featuring tailored suits and dresses in rich fabrics and colors that complement their feathers. On stage, their presence is magnetic, with each member’s unique bird characteristics adding to the visual spectacle. The band’s promotional material, album covers, and posters blend art deco elements with vibrant illustrations of the members, capturing the energy and creativity of their music and era.

AI has a tendency to lean toward dystopian futuristic societies, which I don’t personally get a lot of creative spark from. I think the most personally interesting way for me to explore these themes is to go full sci-fi. I mostly like to engage with stories in a positive or gray light, as I find that does the best job of opening up ideas. I find the real world dark enough, I don’t like spending time making it darker. Does this mean dark stories have no place/are bad art/aren’t worth time. Not at all. I would by a hypocrite to say I didn’t enjoy or appreciate any type of darker toned media. All of this is to say that I am going to to try for a lighter, if not morally gray/messy tone in my fictional world. I am not going full dystopia.

From looking at the Codex Seraphinianus, I think another important aspect of my world building will be environment. This is a little tricky since AI is the theme. I want to find a unique way to incorporate natural elements into my AI world.

I think a cool approach to getting AI tools to assist with this world building would be to make it role play and tell a personal story from the perspective of a person or creature living in this world. I think this is the easiest way to flesh out some basic ideas into more concrete elements of world-building. In addition, it will force a narrative on the world iself, which I think will add value.

In lands unveiled, where horizons grandly sweep,

‘Neath boundless skies, where ancient whispers seep.

Where once the heart might wander and roam,

Seeking the wild, far from home.

Now in each step, a sense of place does grow,

With each known sight, fondness begins to show.

Beside the river, its course a steady guide,

Its rhythmic flow, where calmness resides.

With each meander, my pulse finds its pace,

In the river’s twist, echoes of my space.

Its waters shape the land, and subtly, my view,

Mirroring life, in its surface true.

Amidst the forest, where canopy and light dance,

Life’s verdant symphony performed in tranquil trance.

Each tree’s arch, nature’s resilience taught,

Roots entwined with mine, in quiet thought.

Here, in the woodland’s calm repose, my step slows,

In the forest’s embrace, my serenity flows.

On trails well-trodden, where legacies intertwine,

The earth cradles the steps of those before mine.

Each dusty mile, a tapestry unfurled,

A rich communion with the pulse of the world.

In every journey, connections new and old,

On this shared path, my story is told.

Under the canvas of the cosmic sea,

Night’s gentle veil reveals its mystery.

The stars’ silent stories, told in sparkling code,

Speak of a unity in their heavenly abode.

In the night’s soft cradle, my dreams are spun,

As stars watch over me, till the rise of sun.

In this wild embrace, where life’s tapestry interlaces,

Each day’s pattern, the land’s breath traces.

A kinship with the earth, a dance heart to heart,

In nature’s grand design, I play my part.

In closeness with the vast, a harmony’s sound,

Here, in every inch, my home is profoundly bound.

The Process

This poem was fun to work out because I wanted to play with the theme of finding someone you love so much that you find even more beauty after you get to know them like the back of your hand. This is significant, because I had to frame my prompts in a very specific way. I didn’t want This theme to be outwardly expressed, which defeats the whole point of if it being a poem, but if I didn’t mention it, the outputs I was getting didn’t match the theme. To resolve this, I have to prompt the poem to have the metaphorical outcome instead of the outcome that matched the actual message and theme I was going for. This took a lot of time and tweaking. I also found this very interesting because even though the GPT can write passible poems, it was really hard to ask it to incorporate and idea implicitly. I had to also frame it implicitly in order for it to get the result I want.

Lois Rosson’s essay on AI arts was engaging, interesting, and brought up interesting perspectives. I appreciated the photography example, as I find it very relevant to the subject, and I haven’t seen that point made yet.

I see the perceived quality of art as 2 distinct categories. The first is the labor that skill that was needed to produce the art. Dylan Eakin (@drawings.by.dylan on instagram) produces artworks that are a great example of this. He hand-draws portraits of people in pencil that look like high quality photographs.

However, he is also a bad example of this category because I also think the composition his art falls into the second category, which is the message/feelings the viewer perceives or the artist feels when they make a peice. Abstract art and impressionism are popular and distinct examples of this. The value of the art is in its ability to strongly and skillfully present its theme – not necessarily the labor needed to create it. Below is an example of this sentiment, screenshotted from twitter (or X, I guess), with the poster’s username included.

This is a child’s drawing at a child’s skill level, but it’s easy to get a strong emotional connection from this piece.

My big point here is that with the emergence of AI art where creating detailed pieces of art is easier before, there will most likely be an even greater shift from art that looks nice and takes a lot of skill to create to art that evokes specific strong emotions and clearly and deliberately gets its message across. I don’t have a background in art history, so please correct me if I am wrong, but I suspect that the emergence of impressionism had some influence from the emergence of photographs. The point of impressionism is to properly illustrate the vibes from the scene, not necessarily to capture every detail.

This type of shift is a blessing and a curse. It’s sad because the skill it takes to make a good piece of art is lessened, so people will put less work into appreciating or learning how to make art by hand. My only response to this is the widespreadness of hand sewing and knitting when machines that make these processes 100x faster have been around for centuries now. People still carve wood by hand despite molds and tools making it easier. In most cases, the two are integrated to make something even better than would have been possible. People still like the doing and the making of art.

In addition, I would like to address the point Rosson made regarding copyright and art. Specifically on criticisms of AI art for being unable to make anything truly original. Nothing anyone has ever made has been a truly original artwork coming from no other inspirations or influences. All art comes from some sort of reference of life. Does this make the copyright issues surrounding AI generated pieces less messy? Absolutely not. There are still many ethical concerns regarding image sourcing. However, this issue is rooted in an issue that has plagued the art realm for a very long time. This is the battle of remix and ownership. I still don’t have an answer. I still haven’t made up my mind about this, but I do think it’s unfair to say real people are allowed to and should remix and AI is stealing if they also remix.

I play Dungeons and Dragons, and I got the opportunity to DM for a campaign I was a part of. I didn’t have access to a lot of the lore books, and I am a big fan of homebrew content. As a DM, one of your primary goals is worldbuilding for your characters. One aspect of worldbuilding is, of course, the map of the mystical lands your characters will be traveling to over the course of your D&D sessions.

Now worldbuilding is hard, so there are a lot of tips and tricks for that kind of thing, especially in the context of D&D. One such famous tip is the “Pasta Method” for making maps. I don’t have it saved, otherwise I would cite it here. However, it is a popular technique, and I am sure you can find other versions of it all over the internet if you wish. This method involves pasta, a pencil, and some paper. If you want to get fancy with it, you can use different types of pasta or different colors to denote regions. You also don’t necessarily need to use pasta. I’ve seen rice, beans, M&M’s, dice, even, used as well for this sort of thing. All you have to do is throw the pasta on the paper, group and shift the pasta to your liking, then outline the shape of the pasta with a pencil. Once this is done, BOOM. You have a fantastical map that you can place fantastical forests and cities in (which pasta can also help with).

Ok, the point I am making with this example is that this is a form of physical random generation. It takes away the need to think out every detail of every line of your coast, and allows you to create something new. It uses your skill as a pattern-recognizing human and random generation to its fullest advantage. I find that Mark Amerika’s work do much the same type of thing. Just in a much more sophisticated, artistic way.

I am starting to see a consistent theme of AI generated art – specifically the generative ones Amerika seems to like to play with. That is, AI generated and physically generated arts seem to have success because they can create something random from which we can use our specially-trained-ancestrally-passed-down-for-survival pattern-recognizing instincts to create something interesting. Take the 3 word story example from class today. Your brain is making abstract connections and using defined patterns to connect the dots and create a cohesive story. That is an incredible testament to the human mind in conjunction with creativity, and I have a growing theory that pattern recognition and subsequently pattern divergence is a foundation of human creativity.

The wrench in all of this is the big spooky neural networks and machine learners. We are effectively teaching something else this type of pattern recognition, and I can’t say for sure if we have been all that successful. Mark Amerika is successful, however, because he seems to understand this sort of fundamental aspect. He creates these AI works, and the AI acts like the pasta, but Mark Amerika then takes the pasta and synthesizes it into something that has meaning, and that is where the art lives.

Introduction

The main outcome I want to get out of this class is a solid standing on what AI can do in relation to the Arts and Computer Science. I want to be educated about AI and its integration into into this world. I also want a clear understanding of modern capabilities, so I can make sure to take advantage of the tools I have available to me. In conjunction with this, I want an understanding of possible dangers and the ethical dilemmas associated with using these types of tools and to make sure I move forward in my work ethically and wisely.

My research goals are centered around a deep and comprehensive exploration of Artificial Intelligence (AI) in various creative fields. I aim to understand how AI can be applied innovatively in writing, image generation, cinema, music, coding, game development, and generative art. This course presents a unique opportunity to investigate the intersection of AI with artistic creativity, and I intend to delve into the programming aspects of AI in the arts, its influential role in design, and the complex philosophical questions that arise at this intersection.

AI in Programming Arts and Design

One of my primary research goals is to understand AI’s role in the programming arts and its impact on design, especially in web and software design. I aim to explore how AI algorithms can enhance user experiences in web design and aid in creating more efficient and creative software design processes. Additionally, I plan to investigate AI’s application in the fine arts, examining how AI-generated artworks challenge our traditional notions of creativity and authorship.

Philosophical Exploration: Sentience, Intelligence, and Artistic Ability

A significant aspect of my research will focus on the philosophical implications of AI in the arts. I am particularly interested in exploring concepts of sentience and intelligence in relation to AI’s artistic capabilities. My goal is to understand whether AI can truly possess creativity, or if its artistic outputs are merely reflections of learned data patterns. This exploration will also delve into the nature of artistic ability and whether it can be attributed to non-sentient entities like AI.

Goals for Integrating AI in Artistic Workflows and Education

Integrating AI into traditional artistic workflows is another area I aim to explore. I plan to investigate how AI tools can augment the creative capabilities of artists, allowing them to push the boundaries of their traditional mediums. In the context of education, one of my goals is to understand how principles of computer science and AI can be effectively integrated into arts and humanities curricula, fostering a new generation of artists who are adept at navigating the intersection of art and technology.

Navigating Ethical Implications and Future Trends

Ethical considerations in the use of AI in the arts form a crucial part of my research goals. I intend to study the ethical implications surrounding data privacy, bias in AI algorithms, and the impact of AI on employment in creative sectors. Additionally, I am eager to explore the future trends in AI within the arts, anticipating innovative forms of AI-driven artistic expression and understanding the balance required between technological advancement and artistic integrity.

Conclusion

Through my participation in “DTC 338: AI in the Arts,” my goal is to gain a comprehensive understanding of AI’s role in the arts. I aim to explore the technical, creative, and ethical dimensions of this intersection, equipping myself with the knowledge and skills necessary to contribute to and navigate the evolving landscape of AI in creative industries. This course will provide the foundation for my research, and I am excited to explore the myriad possibilities that AI brings to the world of art and creativity.

These works are always interesting because if the AI that’s generated is smart enough to teach others strong morals, it would be strong and well-educated enough on morals and ethical codes to avoid the types of take-over globalist outcomes. However, this writing does a great job of addressing that common issue, as the designers of the algorithm encourage the machine for monetary and political gain. In addition, it is implied Prometheus is pulling all the strings because this is what the machine deems is the morally good approach to solving humanitarian issues.

The biggest portion that went wrong in this scenario is the human interference. Their goals were control and making money, and the AI provided them with the ability to meet those goals.

This text touches on a fundamental aspect of machine learning that is very important for its moral implications. That is that advanced AI tends to rely on some sort of learning algorithm, in which the computation adjusts based on feedback. In order for these to remain in human’s best, ethical, interests, the goal of this learning needs to stay moral and focused, which can be directly hard-coded into an AI system.

I have some skepticism regarding the possibility of an AI dystopia like the ones we are afraid of are possible, because they rely on the assumption that everything in the world has recordable, simple, computational outcomes. What I mean by this is that there is an assumption that simple actions, phrases, or input variables can alway result in complex, accurate, totally predictable conclusions. The real world typically has more randomness and nuance than that, so there is a limit to the level of intelligence or power an intelligent being could have. As if life is a computational Rorschach Inkblot Test. Maybe computers are different, and they can see more nuanced and complex patterns than we can, but I am suspicious that is is enough to do the damage we say it can. At least for the near future.

As far as utopias go, there are too many human beings for that to be a realistic possibility. One man’s trash is another man’s treasure the same way one man’s dream is another man’s nightmare.

Hello! I am Hailey. I am a Data Analytics student with an emphasis in Data Visualization. I am interested in AI because of its significance in the modern coding realm.