While generative AI is seen as controversial, it has undeniably impacted artists and the art world. Some claim it can’t create “real art,” while others think the future may prove them wrong.
In 2022, a man named Jason Allen stirred up tremendous controversy with his AI-generated art. He had entered Midjourney-created digital art in a competition at the Colorado State Fair and won. He defeated the other division contestants, claiming the blue ribbon and a few hundred dollars in prize money. Although he claims to have done nothing wrong since he didn’t technically break the rules, there was immediate backlash from others in the competition. The incident soon went viral and thousands on the Internet expressed their opinions.
The situation was among the first of its kind and has become a landmark in the generative AI model debate. Those against the use of the technology claim that the resulting works produced by it are ingenuine and amount to intellectual theft and that generative AI is nothing more than an aggregator of Internet content displayed as art. Those for the use of generative AI believe otherwise, stating that its arrival pushes the boundaries making art more accessible.
Using reinforcement learning with generative AI could help to calm the waters. Instead of relying on static data sets, using reinforcement learning, a form of machine learning would lead to evolved new experiences. This would result in generative AI that uses ethical principles and would make it easier to reward art produced this way without concerns over copyright infringement.
Instead of seeing algorithms as competition for human artists, people would grow to appreciate the democratization of art making the creation of artistic works more accessible for more people. If the algorithms respected moral and legal boundaries, then acceptance and use would be more likely.
In the end, it is humans who will have to create the rules that govern ethical Generative AI. After all, an algorithm is only as good as its training data and feedback.
While many people think generative AI has no place in the artistic community, its presence is undeniable. After all, what does “real art” even mean? Most lasting changes in creative spaces come from controversial styles and methods. A good example of resistance to change is that there are still people who don’t believe digital art has validity.
That’s why a growing number of people see generative AI creations as legitimate forms of art. There’s something to be said about its creative capabilities. And even though generative models are aggregators and rely on human creations as models, they still create something unique. Is it different from tracings or mirroring? Even the Mona Lisa has been copied by a student of Leonardo da Vinci. Does that make the copy illegitimate art?
The world of art and graphics design and job opportunities are shrinking as traditional media sees declining numbers and revenue. These are jobs that are at the highest risk for future AI takeovers. The algorithms are winning because they produce end products much faster and cheaper than any human can.
That’s why traditional and digital artists feel threatened. To them, it signals the downfall of artistry and creativity. Although 43% of American adults believe in the revolutionary aspects of AI technology, not as many are convinced that art generated this way is legitimate. And considering the Colorado State Fair competition results, the fear of lost jobs from the use of generative Art isn’t unfounded. While some artists who entered the competition poured dozens of hours and hundreds of dollars into their creations, the winner only had to type one sentence. And since it’s technically possible to copyright the art generated by AI for commercial use, it is understandable that many artists feel their livelihoods are at stake.
It already is with the recent arrival of ChatGPT and Dall-E 3. The controversy will remain but likely generative AI will become accepted as an extension of digital graphic design. And ultimately, art may become a synthesis of human and AI expression. Arguably, it will become hyper-human since people will create the training data for the algorithms. Already, in a recent study, humans could only tell the difference between generative AI-produced art and that created by humans about half of the time.
Can you tell if the image below was human or AI-created?
Although artists aren’t may not be fond of this new medium for creating art, it is making an immediate impression on those who see the results. And it is allowing people to create fantastic images when they never thought of themselves as being artistic. With proper guidance and ethical guardrails in place, Generative AI should grow to become one of the most impactful technologies that the art world and artists have ever seen.
Editor’s Note: In the last week OpenAI, the creator of ChatGPT and Dall-E 3 announced that Midjourney and LeonardoAI, two application programming interfaces (APIs) that charge for their use will no longer be needed because ChatGPT Plus will render AI art without them. Describe the image and Dall-E 3 will create it. But you will need a subscription to ChatGPT Plus.
]]>By definition, sentience is about feelings and sensations and not thinking. Consciousness, on the other hand, is about our awareness of self and our place in the world around us. And thinking is about the ability to reason, consider a problem, come up with an idea or solution, or have an opinion.
So from what we know about ChatGPT in its various iterations, does it meet the definition of any of these terms? Is it sentient? Is it conscious? Is it thinking?
Here are Katie’s conscious thoughts on the subject.
Unless you’ve been living under a rock for the past few months, chances are you’ve heard of the new AI software, ChatGPT. This technology is making waves in the tech industry and is enthralling millions with its ability to take simple, natural language questions and answer them in incredible detail.
ChatGPT is a generative AI which means it can produce text, images, and other types of responses to prompts. Generative AI learns from inputs of data to generate its output. LLM is a subset of generative AI.
The advent of the technology has the potential of upending entire industries. If an AI can produce works of art, transcribe information, write essays, take the bar exam and pass, and generate software code, what does it mean for humans in these careers or doing these jobs?
For most of us without a degree in computer software engineering, the inner workings of AI and LLM systems are a mystery. Maybe this explanation can help.
An LLM uses a deep learning model built using a neural network. A neural network is a computer-based technology that mimics biological circuitry in living brains. LLMs are trained on massive quantities of unlabeled text using self-supervised learning strategies, which are a type of machine learning that doesn’t necessarily need to involve heavy human categorization of inputs. Ultimately, this allows the AI to perform well at a variety of different tasks and “memorize” a great deal of knowledge including patterns within natural language.
An LLM’s ability to understand natural language patterns opens many doors for the software to become a valuable tool with many companies interested in how the technology can be adapted for internet search impacting ranking factors and the calculation of search results.
The titans referred to here are the technological giants of the industry and include Amazon, Google, Microsoft, Apple, and Meta. All are working with generative AI systems in the face of OpenAI’s recent release of ChatGPT. Many industry analysts and investors are speculating on which of these companies and their generativeAIs will come out on top.
The power and use of the technology are currently not constrained, but given the early results from ChatGPT, many working with AI are worried about where future advancements will take us. An open letter signed by more than 1,100 technology industry leaders has called for a temporary halt to development until safety guardrails and protocols are
put in place. After all, human-competitive AI software can have many serious and unexpected consequences, according to them.
But many industry leaders are encouraging the industry to continue to push the boundaries of what can be achieved with this technology. They see real potential benefits, the easing of workloads, and producing real positives for the human condition. For example, some believe a generative AI could be used to transcribe doctors’ patient charts or help with baseline diagnoses for some conditions. They argue that this could free up doctors to spend more time communicating face-to-face with patients.
One of the questions associated with advanced generative AIs is when these systems become too life-like. Is there a point when they could become conscious, sentient or thinking? Have generative AIs creators considered the implications for humanity? Some in the industry already believe generative AI has crossed the bridge of consciousness or at least the appearance of it. Former Google engineer, Blake Lemoine, is one of these. After working with and conversing with Google’s generative AI LaMDA (Language Model for Dialogue Applications), he was utterly convinced the software was sentient and helped to connect it to a lawyer.
From a neurological perspective, there is an ongoing debate about what comprises sentience, consciousness and thinking. Determining these characteristics is at times hard even in humans. For example, if a person suffers from severe dementia do they qualify in these three categories? But as generative AI continues to undergo its evolution, at some point, we will need to determine if this technological creation of our species will fulfil all three states of mind that we currently claim as our own.
]]>