Introduction
As the world progressed in the field of technology, it saw the rise of artificial intelligence that transformed the entire digital landscape.
From manufacturing to healthcare, finance, and content creation, artificial intelligence paved its way into all the industries and sectors of the digital world.
The most popular sector that saw a wave of revolution with artificial intelligence is AI-generated content in the field of content creation.
AI-generated content includes various types of content, such as text, images, audio, and videos that are generated while using AI algorithms.
As a result, AI-driven systems and platforms have the ability to generate human-like text, create realistic images, compose music using various genres and the voices of existing artists, and produce artistically advanced videos.
Though AI-generated content has made the lives of creative content creators extremely easy, it comes with its specific set of challenges.
In this blog, we will understand some of the issues in AI-generated content specifically related to quality, authenticity, and copyright issues.
Quality Issues In AI-Generated Content
Quality issues in AI-generated content refer to the several limitations and shortcomings that are faced by the content produced by AI systems.
Quality issues are harmful to content generation as they impacts the usability, reliability and overall effectiveness of the generated content. As a result of quality issues, the outcome of the AI-generated content fails to meet the standards that are expected from the consumers and human creators.
Let us now have a look at the various quality issues in AI-generated content:
Coherence and Relevance
One of the most significant quality issues faced by AI-generated content is its coherence and relevance. It is often seen that AI models, inspite of their power, generate content that lacks a logical flow.
For example, when an AI platform generates an essay, there is a possibility that the paragraphs don’t seamlessly integrate with each other, leading to a disconnect in the entire essay.
The challenge of coherence and relevance is majorly seen in longer formats of texts where it becomes difficult for the AI system to maintain a relevant and comprehensive theme.
Factual Accuracy
AI-generated content may be filled with factual inaccuracies as it may generate content that has incorrect or misleading information.
As various AI models like ChatGPT are trained on the data present on the internet, they may incorporate some false data present on the internet.
This becomes extremely problematic for situations where factual accuracy is highly important, such as the healthcare industry, news articles or academic papers.
Creative Limitations
AI-generated content often lacks the depth of creativity and innovation that a human mind has the capability to generate.
While AI systems have the ability to imitate the styles of human beings to generate new ideas, it lacks the ability to create genuinely new innovative ideas.
For instance, the AI system may generate a story with new plot twists and narratives, but it will lack the depth of emotions required to hook the users.
Redundancy and Repetition
AI-generated content is often found to be redundant. This implies that the AI-system repeats the same ideas or phrases in the entire text by paraphrasing it.
The issue of redundancy and repetition arises because the AI system may not fully understand the concept of information hierarchy, leading to the generation of content that is less engaging and monotonous.
Over-Optimisation for Keywords
In a world where SEO (Search Engine Optimisation) has become essential for every online business, the content generated by AI systems might be overly optimised for keywords. As a result, it hampers the readability and natural flow of the content for the user.
Although such content may be technically sound for search engines, it often provides a very poor user experience that affects the user’s engagement.
Authenticity Issues In AI-Generated Content
Authenticity issues in AI-generated content relate to the challenges with respect to the trustworthiness and genuineness of the generated content.
The issue of authenticity arises when the content generated by AI systems is indistinguishable from human-generated content, which often leads to potential deception and loss of trust in the system.
Further, authenticity issues also include various ethical considerations that relate to representation, consent, and manipulation.
Given below are some of the authenticity issues seen in AI-generated content:
Identifying AI-Generated Content
One of the most significant authenticity challenges faced by AI-generated content is the difficulty in differentiating between AI-generated content from human-generated content.
This can lead to serious issues when users consume AI content, which changes their perception regarding various scenarios, such as authenticity and trustworthiness.
Deepfakes and Misinformation
AI technology has the ability to generate realistic deepfakes (manipulated videos or images) that have the power to deceive users and viewers.
Such deepfakes are often used for malicious and harmful purposes, such as spreading misinformation amongst audience or tarnishing the reputation of an individual.
With the rise of deepfakes and misinformation in the digital landscape, the authenticity of audio and visual content has become extremely questionable.
Attribution and Authorship
It is extremely difficult to determine the authorship of AI-generated content. Further, if a text or image generated by an AI system is attributed to a human author, it can be significantly misleading and can lead to many serious consequences.
On the other hand, when authorship is attributed to the AI system, it raises many questions about the true source of originality, innovation, and creativity.
Manipulation and Propaganda
AI-generated content has the potential to be used to manipulate the overall public opinion in a society.
For example, AI can be used to generate realistic and convincing social media posts that spread disinformation or propaganda.
As a result, the authenticity of online posts and information is questioned, and it can also have serious societal implications.
Verification Challenges
Verifying the content generated through AI systems is extremely challenging. Traditional verification methods such as fact-checking and source validation are not considered to be effective methods for AI-generated content.
Therefore, it is necessary that organisations use new tools and techniques to verify the authenticity of the AI content.
Copyright Issues In AI-Generated Content
Copyright issues in AI-generated content refer to the legal challenges with respect to the ownership, use, and protection of AI-produced works and content.
These issues arise because of the uncertainty that exists in the current copyright laws when applied to AI-generated content.
As a result, many disputes can be seen with respect to the ownership, liability and use of copyrighted material when training an AI system.
Now that we have understood what copyright issues are with respect to AI content let us look at some of the most common copyright issues faced by AI-generated content:
Ownership of AI-Generated Works
A significant and fundamental copyright issue faced by AI-generated content is determining the ownership of the AI-generated works.
The traditional copyright law attributes the ownership to human creators, but when it comes to AI content, the copyright law is unclear about who will hold the rights of the content – the developer, the user, or the AI system itself.
Use of Training Data
Majority of the AI models are trained on huge volumes of datasets, which often includes copyrighted material. As a result, it raises many questions about the legality of using such copyrighted material for the training purpose of the AI model.
Further, if an AI-generated work even closely resembles a copyrighted work, it can lead to infringement claims by the owner of the copyrighted work.
Originality and Creativity
Copyright law has been enforced to protect the original and creative works of individuals and organisations. The content generated by AI systems challenges this notion as the content is generated by an AI model that lacks consciousness and creative intent.
Therefore, today, the question of whether AI-generated content meets the criteria for copyright protection has become a complex one for the legal department.
Infringement and Liability
Suppose the content generated by AI systems does infringe on a copyright material, then, determining the liability or legal accountability becomes a problem for the legal world.Â
This is because it is unclear that in such a scenario whether the liability should be laid upon the developer of the AI system, the user who gave the command, the AI system itself or any other party.
Due to this uncertainty in the copyright law, enforcement and legal accountability becomes extremely complicated.
International Jurisdiction
Copyright laws may vary significantly across many countries, which complicates the legal landscape for AI-generated content.
It is possible that AI-produced content may be infringing copyright laws in one jurisdiction but not in another jurisdiction. This often leads to international copyright disputes.
Conclusion
With the rise of AI technology, the challenges of quality, authenticity, and copyright issues in AI-generated content are also on the rise.
While every industry has seen significant transformation due to artificial intelligence, content creation with AI faces many significant challenges that need to be addressed for better usage of the AI system.
Continuous collaboration between technologists, legal experts, and policymakers is important to ensure that the content generated by AI systems is high-quality, authentic, and legally compliant.
If we are able to address the issues mentioned in this blog, we can use the power of AI to generate revolutionary content while mitigating the risks associated with AI content generation.
FAQs
AI can be utilised for generating various types of content, such as articles, social media posts, reports, images, music, and videos. Further, by using natural language processing (NLP) and machine learning algorithms, AI systems can analyse large volumes of datasets to create comprehensive and relevant content that imitates human creativity, and writing.
The various advantages of AI-generated content include increased efficiency and scalability, cost reduction and the ability to create large volumes of content in a quick and accurate manner. It can also improve personalisation by providing customised content to targeted and specific audiences that are based on data analysis and user behaviour patterns, leading to better organisational revenues and success.
Yes, various ethical concerns are present in AI-generated content, such as potential biases, authenticity and trust issues, misuse of content, privacy concerns, and the challenge of ensuring proper attribution and copyright management.
The skills that are needed to create AI-generated content include skills in data science, machine learning, and natural language processing. Additionally, it is important to have proficiency in programming languages like Python, familiarity with AI frameworks, and an understanding of various content creation tools. Further, to ensure the responsible use of AI, it is extremely important to have knowledge of ethical considerations and copyright laws.
