Artificial intelligence (AI) is poised to become a vital tool for brands seeking to enhance their online presence.
However, integrating AI into marketing strategies inevitably creates legal considerations and new regulations that agencies must carefully navigate.
In this article, you’ll discover:
- How businesses and SEO and media agencies can minimize legal risks of implementing AI-enhanced strategies.
- Useful tools to reduce AI bias and a handy process to review AI-generated content quality.
- How agencies can navigate main AI implementation challenges to ensure efficiency and compliance for their clients.
Legal compliance considerations
Intellectual property and copyright
A crucial legal concern when using AI in SEO and media is following intellectual property and copyright laws.
AI systems often scrape and analyze vast amounts of data, including copyrighted material.
There are already multiple lawsuits against OpenAI over copyright and privacy violations.
The company faces lawsuits alleging unauthorized use of copyrighted books for training ChatGPT and illegally collecting personal information from internet users using their machine learning models.
Privacy concerns on OpenAI’s processing and saving of user data also caused Italy to entirely block the use of ChatGPT at the end of March.
The ban has now been lifted after the company made changes to increase transparency on the chatbot’s user data processing and add an option to opt out of ChatGPT’s conversations used for training algorithms.
However, with the launch of GPTBot, OpenAI’s crawler, further legal considerations are likely to arise.
To avoid potential legal issues and infringement claims, agencies must ensure any AI models are trained on authorized data sources and respect copyright restrictions:
- Ensure data has been obtained legally and the agency has the appropriate rights to use it.
- Filter out data that doesn’t have the required legal permissions or is of poor quality.
- Conduct regular audits of data and AI models to ensure they comply with data usage rights and laws.
- Hold a legal consultation of data rights and privacy to ensure nothing conflicts with legal policies.
Both agency and client legal teams will likely need to be involved in the above discussions before AI models can be integrated into workstreams and projects.
Data privacy and protection
AI technologies rely heavily on data, which may include sensitive personal information.
Collecting, storing, and processing user data must align with relevant privacy laws, such as the General Data Protection Regulation (GDPR) in the European Union.
Moreover, the recently introduced EU AI Act also emphasizes addressing data privacy concerns associated with AI systems.
This is not without merit. Large corporations, such as Samsung, have banned AI completely due to the exposure of confidential data uploaded to ChatGPT.
Therefore, if agencies use customer data in conjunction with AI technology, they should:
- Prioritize transparency in data collection.
- Obtain user consent.
- Implement robust security measures to safeguard sensitive information.
In these cases, agencies can prioritize transparency in data collection by clearly communicating to users which data will be collected, how it will be used, and who will have access to it.
To obtain user consent, ensure that consent is informed and freely given through clear and easy-to-understand consent forms that explain the purpose and benefits of data collection.
In addition, robust security measures include:
- Data encryption.
- Access control.
- Data anonymization (where possible).
- Regular audits and updates.
For example, OpenAI’s policies align with the need for data privacy and protection and focus on promoting transparency, user consent and data security in AI applications.
Fairness and bias
Agencies must be proactive in identifying and mitigating algorithmic bias. This is especially important under the new EU AI Act, which prohibits AI systems from unfairly affecting human behavior or displaying discriminatory behavior.
To mitigate this risk, agencies should ensure that diverse data and perspectives are included in the design of AI models and continuously monitor results for potential bias and discrimination.
False or misleading content
AI tools, including ChatGPT, can generate synthetic content that may be inaccurate, misleading or fake.
For example, artificial intelligence often creates fake online reviews to promote certain places or products. This can lead to negative consequences for businesses that rely on AI-generated content.
Implementing clear policies and procedures for reviewing AI-generated content before publication is crucial to prevent this risk.
Another practice to consider is labeling AI-generated content. Although Google seems not to enforce it, many policymakers support AI labeling.
Liability and accountability
As AI systems become more complex, questions of liability arise.
Agencies utilizing AI must be prepared to take responsibility for any unintended consequences resulting from its use, including:
- Bias and discrimination when using AI to sort candidates for hiring.
- The potential to abuse the power of AI for malicious purposes such as cyberattacks.
- The loss of privacy if information is collected without consent.
The EU AI Act introduces new provisions on high-risk AI systems that can significantly affect users’ rights, highlighting why agencies and clients must comply with the relevant terms and policies when using AI technologies.
Some of OpenAI’s most important terms and policies relate to the content provided by the user, the accuracy of responses and the processing of personal data.
The content policy states that OpenAI assigns the rights of the generated content to the user. It also specifies that generated content can be used for any purpose, including commercial, providing it complies with legal restrictions.
However, it also states that output may be neither completely unique nor accurate, meaning that AI-generated content should always be thoroughly reviewed before use.
On a personal data note, OpenAI collects all information users input, including file uploads.
When using the service to process personal data, users must provide legally adequate privacy notices and fill out a form to request data processing.
Agencies must proactively address accountability issues, monitor AI outputs, and implement robust quality control measures to mitigate potential legal liabilities.
Get the daily newsletter search marketers rely on.
AI implementation challenges for agencies
Since OpenAI released ChatGPT last year, there have been many talks on how generative AI will change SEO as a profession and its overall impact on the media industry.
Although changes come with a mix of enhancements to the daily workload, there are some challenges agencies should consider when implementing AI into client’s strategies.
Education and awareness
Many clients may lack a comprehensive understanding of AI and its implications.
Agencies, therefore, face the challenge of educating clients about the potential benefits and risks associated with AI implementation.
The evolving regulatory landscape necessitates clear communication with clients regarding the measures taken to ensure legal compliance.
In order to achieve this, agencies must:
- Have a clear understanding of their client’s goals.
- Be able to explain the benefits.
- Show expertise in implementing AI.
- Address the challenges and risks.
A way to do that is by having a fact sheet to share with clients containing all the necessary information and, if possible, provide case studies or other examples of how they can benefit from using artificial intelligence.
Integrating AI into SEO and media strategies requires significant resources, including financial investments, skilled personnel and infrastructure upgrades.
Agencies must carefully assess their clients’ needs and capabilities to determine the feasibility of implementing AI solutions within their budgetary constraints, as they may require AI specialists, data analysts, SEO and content specialists that can effectively collaborate together.
Infrastructure needs may include AI tools, data processing and analytics platforms to extract insights. Whether to provide services or facilitate external resources depends on each agency’s existing capabilities and budget.
Outsourcing other agencies might lead to quicker implementation while investing in in-house AI capabilities might be better for long-term control and customization of the offered services.
AI implementation demands specialized technical knowledge and expertise.
Agencies may need to recruit or upskill their teams to effectively develop, deploy, and manage AI systems in line with the new regulatory requirements.
To make the most of AI, team members should have:
- Good programming knowledge.
- Data processing and analytical skills for managing large amounts of data.
- Practical knowledge of machine learning.
- Excellent problem-solving skills.
Agencies must consider the ethical implications of AI use for their clients.
Ethical frameworks and guidelines should be established to ensure responsible AI practices throughout the process, addressing the concerns raised in the updated regulations.
- Transparency, disclosure, and accountability when AI is utilized.
- Respecting user privacy and intellectual property.
- Obtaining client consent to use artificial intelligence.
- Human control over AI with ongoing commitment to improve and adapt to emerging AI technologies.
Accountability matters: Meeting the legal challenges of AI implementation
While AI presents exciting opportunities for improving SEO and media practices, agencies must navigate legal challenges and adhere to the updated regulations associated with its implementation.
Businesses and agencies can minimize legal risks by:
- Ensuring data has been obtained legally and the agency has the appropriate rights to use it.
- Filtering out data that doesn’t have the required legal permissions or is of poor quality.
- Conducting audits of data and AI models to ensure they comply with data usage rights and laws.
- Holding a legal consultation of data rights and privacy to ensure nothing conflicts with legal policies.
- Prioritizing transparency in data collection and obtaining user consent by clear and easy-to-understand consent forms.
- Using tools that help reduce bias, like AI Fairness 360, IBM Watson Studio, and Google’s What-If Tool.
- Implementing clear policies and procedures for reviewing the quality of AI-generated content before publication.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.