What Are the Ethical Implications of Using AI in Creative Work?
AI has been a hot topic for over a year – its catapulting entry into daily discourse is undeniable, and its ever-growing effects in workplaces, information distribution, and creativity, among so many other areas of life, is indisputable to say the very least. It makes sense that, like with every other technological advancement, people have recognized its benefits and named the issues that come with it.
Reactions to AI have varied. From companies like Google, Amazon, and Microsoft embracing it with open arms as heralding a new age for humanity to downright fear of its potential for harm and condemnation of any further development of it, we can say with certainty that AI is here to stay. Who doesn’t want autonomous cars after all?
Join us for this week’s article in which we summarize the main points of debate below:
Which Ethical Dilemmas Does the Use of AI Raise?
1. Ownership, Authorship, and Copyright Infringement
Our use of Creative AI tools in generating music, art, and literature has raised significant challenges related to ownership and authorship for copyright law. Traditionally, copyright was associated with human authorship, and machines were considered tools in the creative process. If you created something, it was yours and you owned the rights to it, unless otherwise stated.
However, with machine learning algorithms and AI, computers now play a more active and complicated role in generating creative works. This shift raises questions about who owns the copyright to AI-generated content. Some legal systems, including those in the United States, have expressed that only works created by a human can be protected by copyright, as they must reflect the “author’s own intellectual creation.”
Copyright infringement is also of significant concern, as creative AI tools use existing material to generate content. This has inevitably led to disputes over who bears responsibility for copyright violations, the user supplying stimuli or the tool’s creator. Legislation might need to be adapted to address these new challenges. If we allow AI to assert ownership, this could lead to discussions about AI being classified as a “legal person.”
2. Lacking Human Intention, Meaning, and Perfect Imperfection
Have you ever looked at an AI-generated art piece and could tell it was not created by a human? You’re not the only one. With human creation come inherent little variations, deviations, personal touches, flaws, asymmetries, and patchwork. The mix creates a result that’s unique to the specific artist and the specific artwork they’ve produced. You can argue that it’s all these imperfections that make human creations so perfect and unique in their own way.
The artist’s intention is also imbued into their work, adding meaning and intentionality. These take form and can be observed in a painter’s strength and speed in their brush strokes, their choice of colors, and the order in which they add every layer. You can feel a director’s intention through their filming style, storytelling abilities, and choice of certain angles, sets, and guidance of delivery to the actors. A writer chooses to use certain words over others, narrates a story in their own style, and develops each character in as much depth or lack thereof as they wish.
AI’s lack of human intention and absence of meaning in the assets it produces lead to content that is often devoid of character, appears too perfect and cold, and is classified by humans per the true nature of the output – reductive.
3. Duplicating a Creator’s Signature Style (aka ‘Artistic Identity’)
There’s a concern about Creative AI replacing artists and authors in certain fields, such as music and writing, with AI-generated content that emulates the style of human creators, potentially leading to ethical and creative implications. The incorporation of Creative AI into the creative workflow and the ethical considerations surrounding ownership and authorship are multifaceted issues that extend beyond simple content generation.
4. Perpetuating Discrimination Through Biased Data
These tools analyze information to make predictions or draw conclusions, but if the data they learn from is biased, their results will also be skewed. For instance, if an AI system is taught with data that heavily favors male voices, it might struggle to accurately recognize and transcribe female voices, leading to unfair treatment of women. Bias can also creep into natural language processing, where certain words linked to specific groups can affect how the AI system interprets text.
Additionally, AI systems can pick up and reinforce human biases present in their training data, resulting in content that’s discriminatory and offensive. This could harm the reputation of organizations using such tools. To prevent these issues, it’s essential to ensure that the data used to train AI content tools is diverse and representative, and to consistently monitor and assess the tools for bias and discrimination. This way, we can reduce potential harm and ensure the ethical and responsible use of these tools.
5. Reductive Nature of AI-Generated Output
It is no secret that Creative AI tools generate assets based on the input they have been fed. An argument could be made that humans are no different, since we too base our inspiration on experiences, memories, and interests. Still, there is an important distinction to be made here – humans possess critical thinking abilities that allow us to slice and dice and combine input in novel ways. Since, at the time of writing, AI has yet to achieve a point of singularity, its discretionary abilities to produce something new are non-existent.
Using AI Responsibly in the Future – Is It Possible?
While AI raises complex ethical dilemmas, it also offers tremendous potential for positive impact. To ensure virtuous AI use in the future, it is crucial to continue exploring these dilemmas, developing solutions, and promoting responsible AI development and deployment. This way, we can harness the benefits of AI while mitigating its ethical challenges.
Learn More on the Ethics of AI Bias (MIT)
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