AI’s Impact on Content Creation, Marketing, Authenticity and Ethics

Dive into audience questions below as we unravel the possibilities AI brings to the table

Artificial Intelligence (AI) is no longer a futuristic concept; it's here, making waves across various sectors, including content marketing and content creation. As AI progresses, it's prompting a series of questions about its influence on content creation, authenticity, ethical considerations, and copyright issues. Our webinar was designed to ignite discussions around these topics. Based on the inquiries we received, we're eager to share our opinions, insights, and thoughts on how we can potentially navigate the AI landscape, harnessing its power to drive evolution and growth in our industry.

Below are questions from the live audience that explore how AI might change content creation, marketing strategies, and potentially new opportunities.

Impact on Content Creation and Marketing

As AI continues to evolve and advance, do you see any potential for brand-new types of marketing campaigns and ways to reach and engage the audience that has not been executed before?

As AI continues to evolve and advance, it's set to augment and amplify existing marketing capabilities rather than completely reinventing the wheel, at least in the short term.

  • Amplified Brand Storytelling: AI can help brands tell their stories more effectively and authentically. By analyzing engagement data, AI can help identify what aspects of a brand's story resonate most with audiences, enabling more impactful storytelling. To do this at scale is another challenge that requires a partner that cannot only distribute content at scale but also measure the engagement beyond page views and time spent. 
  • Predictive Marketing: AI's predictive capabilities can enhance existing marketing strategies and targeting by anticipating consumer needs and trends based on engagement with content. This will allow brands to be more proactive, addressing these needs based on the type of content consumers engage with and what that engagement translates to for marketers.
  • Quality over Quantity: With AI enabling more content to be created more quickly, there's an inevitable risk of an increase in low-quality content. This makes it even more crucial for brands to focus on creating high-quality, value-driven content that truly resonates with their audience while being able to validate the value through the aforementioned engagement measurement. 

Do you feel using AI in creative content could backfire when targeting the Gen-X or older generations who might be more hesitant about the progression of AI?

While it's true that some members of Gen X or older generations may initially be hesitant about AI-generated content, there are also compelling reasons to believe that they could be receptive to it, such as:

  • Quality of AI Content: If the AI-generated content is of high quality, relevant, and engaging, there is a high chance for a positive reception regardless of the audience's age. The key is in the value and relevance of the content, not necessarily in who or what created it.
  • Personalization: AI can streamline and personalize the content experience, which can be appreciated by any demographic, including Gen X and older generations. The more a content topic resonates with a demographic, the higher the likelihood of engagement and captured attention. AI will certainly increase the potential for more personalized storytelling regardless of the demographic age of an audience.

 

Authenticity and Bias

These questions delve into the authenticity of AI-generated content, potential bias in AI, and the impact on diverse representation.

How might the industry head off a backlash against AI-generated content while promoting and protecting authenticity?

Emphasizing authenticity and quality content is exactly how our industry can mitigate potential backlash against AI-generated content. Here are some examples:

  • Human Oversight: Maintain human oversight in the AI content creation process. This can help ensure the content aligns with brand values and meets audience expectations.
  • Quality Assurance: Ensure that AI-generated content meets high-quality standards via Human Oversight. This includes accuracy, relevance, and value to the audience. High-quality content, regardless of how it's produced, is more likely to be accepted.
  • Ethical Guidelines: Establish and adhere to ethical guidelines/regulations for AI use. This includes respecting user privacy, avoiding bias, and ensuring fairness in AI algorithms.
  • Transparency: Be open about the use of AI in content creation. Audiences appreciate honesty and are more likely to accept AI-generated content if they know its use.
  • Education: Educate content producers about AI and its role in content creation. This can help dispel misconceptions and foster acceptance of using AI-generated content responsibly. 

Remember, authenticity isn't just about who or what creates the content but also about the value and relevance it provides to the audience.

How do we prevent these tools from creating content that is too close to the plagiarism of other creators' work?

In theory, the larger and more diverse the dataset, the lower the chance for plagiarism.

With that said, plagiarism is a complex issue. For example, if an AI unintentionally generates content that closely resembles existing work, it could potentially be seen as plagiaristic. In another scenario, if an AI generates similar output for many individuals, the first to publish the output could be seen as the original “owner/creator,” and anyone that publishes the output afterward as a plagiarist.

One of the ways to mitigate these scenarios from occurring is to become well-versed in what’s called “prompting.” The more detailed and specific the prompt, the lower the chance the output will resemble existing works or similar AI outputs.

How do we navigate the innate bias that AI machines have, especially when creating images that represent true diversity?

As mentioned in the webinar, this is a very challenging topic to navigate. The question of whether we can use AI to generate diverse and inclusive imagery is rather a simple answer. Yes, we can, but it relies on the dataset used to train AI models. AI models learn from the data they are trained on. If the training data lacks diversity, the AI will too. Ensuring the training data includes a wide range of diverse examples can help produce more inclusive results.

AI, however, should not operate in a vacuum, even with the right dataset. Human oversight is crucial to checking for bias and making necessary adjustments, especially concerning the datasets used to train AI models.

  • Bias Detection: Implementing bias detection measures can help identify and correct bias in AI outputs. This could involve regular audits of the AI's performance and outputs.
  • Ethical Guidelines: Establishing ethical guidelines for AI use can provide a framework for addressing bias. This could include principles like fairness, inclusivity, and transparency.

More importantly, the question of whether we should use AI image generation to represent true diversity is an entirely different debate. This is likely to become one of the most hotly contested areas of AI application, and rightfully so (Levi Strauss example).

As emphasized during the webinar, it's inevitable that we, as an industry, will encounter missteps along the way. However, the speed and efficiency with which we learn and recover from these errors will ultimately shape our future trajectory. 

Do you think we’ll lose the value of authenticity in photography as there becomes a shift from assuming images are “real” to an assumption that an image is “fake” made by AI?

The introduction of DSLR cameras and post-production software like Photoshop has already sparked debates about authenticity in photography in the past.  For example:

  • Does the ability to take hundreds of shots and choose the 'best' one in real-time lessen the skills traditionally required to capture the perfect shot in a single click of the shutter?
  • Does the capacity to heavily edit images with software like Photoshop diminish the artistry and craftsmanship traditionally associated with manual photo development and manipulation?

Just as with AI, these technological advancements have changed the tools and techniques used in photography, but they haven't eliminated the value of authenticity. Instead, they've expanded how photographers can express their creativity and convey their unique perspective, which are key aspects of authenticity in photography.

AI will likely lead to a reimagining of what we perceive as authentic.  It's crucial to remember that while AI can produce remarkable images, the human element in photography remains irreplaceable. The unique context, emotional depth, and personal perspective that a human photographer brings to their work is something AI cannot replicate. Therefore, even as the tools for image creation evolve, the importance of human creativity and genuine expression in photography will persist.

 

Ethical Considerations and Regulations

These questions focus on the ethical implications of using AI, potential regulations, and the need for internal oversight.

What ethical considerations should be incorporated when using AI and generative AI? Are there any industry or company efforts toward adopting regulations and standards?

Ethical AI use involves respecting data privacy, transparency, and fairness. AI systems must avoid biases and would benefit from clear disclosure when used. Many companies are setting internal AI guidelines, and industry-wide standards are being developed. Regulatory bodies are also stepping in. Companies like OpenAI, Microsoft, Google, and IBM are advocating for AI regulations around key principles like fairness, reliability, and privacy.

How do you foresee federal oversight of AI in the short-term and longer term?

On May 16th, 2023, OpenAI CEO Sam Altman supported and recommended federal oversight and regulation regarding AI during his appearance at the Senate Hearing.

In the short term, we can expect federal oversight of AI to focus on establishing basic guidelines and regulations. This could involve setting standards for how AI systems should be developed and used and how data should be handled. There may also be efforts to prevent and penalize misuses of AI, such as in cases of fraud or discrimination.

In the longer term, as AI technology continues to evolve and become more integrated into our daily lives, federal oversight will likely become more comprehensive and nuanced. This could involve more specific regulations for different sectors (like healthcare, finance, or autonomous vehicles).

Do we need AI ethics officers in our companies?

For companies with less extensive AI use, it may be sufficient to have existing team members trained in AI ethics or to consult with external AI ethics experts as needed.

For larger organizations with heavy use of AI and higher potential to significantly affect people's lives, privacy, or rights, having an AI ethics officer can be crucial, especially as federal oversight becomes more prevalent.

This role can help ensure the company's AI practices align with ethical guidelines, legal regulations, and societal expectations. They can also help navigate complex ethical dilemmas that may arise in the development and deployment of AI systems.

Ownership and Copyright Issues

These questions address the potential legal issues surrounding AI-generated content, including copyright infringement and licensing.

How do creative ownership and licensing work with AI-generated content?

The issue of creative ownership and licensing with AI-generated content is a complex and evolving area of law with many perspectives that have yet to be finalized. Here are a few key points to consider:

  • AI as a Tool: In many cases, AI is viewed as a tool used by a human creator, and the human user who utilized the AI to generate the content retains the copyright. This is similar to using a paintbrush to create a painting.
  • AI as the Creator: If the AI is considered to have created the work, it gets more complicated. In many jurisdictions, including the U.S. and EU, AI cannot hold copyright, and a work created solely by AI may fall into the public domain.
  • Licensing of Training Data: If an AI was trained on copyrighted works, there could potentially be licensing issues, even if the output is considered new and original.

Given the complexity and evolving nature of this issue, it's always recommended to consult with a legal expert when dealing with AI-generated content and copyright.

Do we think that FTC/FCC regulation will get involved?

Regulatory bodies such as the Federal Trade Commission (FTC) and the Federal Communications Commission (FCC) in the United States will likely become more involved in AI regulation as the technology continues to evolve.

The FTC has already shown interest in AI and has issued guidance on how existing laws related to truth in advertising, fair credit practices, and data privacy apply to AI. Similarly, the FCC, which regulates interstate and international communications, may also have a role to play, especially as AI becomes more integrated into communication networks and services.

New legislation may be introduced that specifically addresses AI, and new regulatory bodies may even be created.

Since the US Copyright Office does not recognize AI images as copyrightable at this point, can clients use AI-created images and not have a competitor or other client use the same AI-generated images?

There is, unfortunately, no simple answer to this question. The Copyright Office has clarified that only works created by a human author, with at least a “minimal” degree of creativity, are protectable by copyright. This was emphasized in a case involving a graphic novel that used images generated by an AI platform, where the Copyright Office concluded that the images created solely by the AI were not protected by copyright.

However, in a policy statement, the Copyright Office stated that AI-generated work may be protected by copyright if a human is sufficiently involved in the creative process. This could include selecting or arranging AI-generated material creatively or modifying material after it is created by AI. The Copyright Office has left open the possibility of revising its guidance as AI technology develops further.

This stance could lead to potential legal ambiguities. For instance, it might be challenging to determine the extent of human involvement necessary for a work to be considered copyrightable.

  • Definition of Human Involvement: What constitutes sufficient human involvement in the creative process for a work to be copyrightable? If it is not enough for a human to initiate the AI program, what constitutes a more substantial role to qualify as demonstrating a “minimal degree of creativity”? How do you measure this? Does prompting the AI to use specific colors, shot angles, and/or styles qualify? There are no clear answers currently. 
  • International Implications: How will this stance align with international copyright laws and norms? Different countries may have different views on the copyrightability of AI-generated works, leading to potential legal complexities.

In wrapping up, it's clear that AI is not just transforming the marketing and content creation landscape, but it's also challenging us to rethink our approaches to authenticity, ethics, and copyright. As we continue to explore the potential of AI, it's crucial to strike a balance between leveraging its capabilities and upholding ethical and authenticity standards.

Moreover, understanding and addressing the copyright implications of AI-generated content is essential to ensure fair and responsible practices. As we move forward, fostering open dialogue, embracing regulation, and prioritizing transparency will be key to responsibly harnessing the power of AI.

To learn more, check out the full conversation about AI and content and marketing.

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Disclosure: The responses provided were developed with the assistance of ChatGPT 4, which contributed to idea generation, editing, and clarification. Human oversight was maintained throughout to ensure narrative coherence, accuracy, and appropriate tone.

The perspectives and opinions expressed in this document are intended for general guidance and do not constitute legal or professional advice. It is recommended that organizations consult with their legal team or appropriate stakeholders to understand the specific implications for their operations. These views are based on our current understanding and interpretation of the evolving AI landscape.

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