Navigating Ethical and Legal Challenges of AI in Marketing: A Comprehensive Guide

The ethical or legal questions raised by AI make it difficult for marketers to adapt.

One of our most successful marketing campaigns started long before AI was in all our computers. If we repeated this initiative today, with the help of artificial intelligence, ethical or legal questions would make our lives much more complicated. So, will it allow AI to mess things up?

A little context

Ethical questions related to the use of AI

It raises various legal and ethical questions related to the use of artificial intelligence (AI) and personal data.

Data protection and privacy: The campaign uses personal data, including names, birthdays and email addresses. As a data controller, the company must ensure compliance with the General Data Protection Regulation (GDPR), the French Data Protection Act 2018 and the ePrivacy Directive (2002/58/EC) which applies to to process personal data. Ensure that you provide clear information about data processing activities, obtain valid consent where necessary, and respect the rights of data subjects. It also makes sense to anonymize or anonymize data used in AI algorithms to better protect privacy.

Fairness and bias: The AI ​​system must not discriminate or exclude a customer based on their first name or any other personal characteristic. If a name day is not recognized for a particular customer, another method must be put in place to ensure that they are not unfairly excluded from the benefits of the campaign.
Intellectual Property: The AI ​​model used for personalized recommendations may infringe on patents related to recommendation systems. Due diligence on intellectual property is essential to identify risks of infringement.
Transparency and accountability: The use of AI must be transparent to customers. Let them know that AI algorithms are used to personalize product recommendations. The company should also have mechanisms in place to investigate and deal with any issues arising from the AI ​​system.
Legal liability: The company is legally responsible for the results of the campaign, even those created by the AI ​​system. Any harm or damage resulting from the use of AI may lead to legal liabilities.

Worse, AI could discriminate against or block certain customers

AI-based systems learn patterns from data and use these patterns to make predictions or decisions. If the input data is biased, the AI ​​system reproduces and may amplify that bias. In the context of the marketing campaign you described, the AI ​​system should not discriminate or exclude a customer based on their first name or any other personal characteristic.
Here are some examples of what could happen:

Name recognition bias: Suppose your customer base has more customers with unique names (eg, “Jean”) than less common names (eg, “Evariste”). If the AI ​​system is trained on this data, it may be more effective in identifying and sending offers to “Jean” on St. John’s Day, but it may look at ” Evariste” on Saint Evariste’s Day because there is less data for this name in the training set. This could lead to unintended discrimination, with customers with less common names receiving the same offers.

Discriminate based on other personal attributes: In trying to personalize the customer experience, AI may inadvertently discriminate based on other attributes. For example, if the AI ​​system also considers gender, age or geographic location to generate personalized recommendations, this could lead to discriminatory results. For example, if the system learns that young people prefer a certain style of clothing and older people others, it risks perpetuating these stereotypes and not recommending a wider variety of products to each group. .

How can such prejudice and discrimination be avoided?

• Make sure the AI ​​system is trained on balanced data representing each name equally. To do this, you can preempt unrepresented names or include methods in your model to handle class mismatches.
• Consider implementing measures of fairness in the evaluation of your AI model to ensure that it does not favor one group over another.
• Use interpretive AI techniques to understand why your AI system makes certain recommendations and monitor it to make sure it’s not unfairly favoring certain groups.
• Ensure that you obtain and record clear consent from your customers for the use of their personal data, and inform them of how their data is used, including the use of AI.

What is the action plan for the CEO and his teams

And the CEO:

• Make sure all departments are aware of the importance of data ethics and privacy laws in AI-powered enterprises.
• Provide the necessary resources to ensure compliance with data ethics and privacy laws.
• Actively participate in training sessions to understand the legal and ethical implications of AI.
• Regularly review reports from other managers regarding data compliance and AI ethics.
• Create a company culture that respects customer privacy and promotes the ethical use of AI.

Chief Marketing Officer (CMO):

• Work with the IT/AI development team to ensure that the design of the marketing campaign takes into account ethical implications and complies with data protection laws.
• Coordinate with the Legal Manager and Data Protection Officer to understand and meet data privacy regulations.
• Implement strategies to ensure that user consent for data use is obtained appropriately.
• Regularly review and evaluate the marketing campaign to identify and correct any ethical or legal issues.
• Review and approve all campaign-related customer communications to ensure transparency and fairness.

Legally responsible:

• Conduct regular audits to monitor compliance with data protection laws.
• Conduct intellectual property due diligence to identify risks of infringement.
• Provide legal advice to the CMO and CEO regarding any changes to data privacy laws that may affect the enterprise.
• Work with the DPO to train staff on data protection and the legal implications of the AI-driven initiative.
• Prepare regular reports to the CEO detailing legal compliance and any risks or issues identified.

Data Protection Officer (DPD):

• Collaborate with the AI ​​development team to ensure data privacy is preserved during data processing.
• Conduct data protection impact assessments to identify and mitigate any risks.
• Provide guidance to the CMO and Legal Manager on compliance with data privacy regulations in the enterprise.
• Regularly inform the CEO and other responsible parties about data protection procedures.
• Train staff on data protection and the importance of compliance.

AI Ethics Advisory Committee (if any):

• Regularly review the ethical implications of the AI ​​system, including potential bias and discrimination.
• Make sure the AI ​​system is transparent and make sure it adheres to ethical guidelines.
• Make recommendations to the CMO and AI development team on how to improve the ethical use of AI in the enterprise.
• Conduct regular reviews to assess the impact of the AI ​​system on fairness and discrimination.
• Report to the CEO on ethical issues and recommendations related to the use of AI.

IT/AI development team:

• Work with the CMO to understand the campaign’s goals and ensure the AI ​​system aligns with those goals.
• Implement changes to the AI ​​system to resolve ethical issues and ensure compliance with data protection laws.
• Regularly monitor the AI ​​system to detect and correct any bias or discrimination.
• Ensure that data is anonymized or anonymized before it is used in the AI ​​system.
• Provide regular updates to the CEO and other managers regarding AI system performance and issues encountered.

So much extra work for a simple campaign! If we assume that these little people are normally established and not chasing after extra work, adding to their already full schedules, it’s a safe bet that our enterprise project will never be verified. If the campaign is not limited to sending only on February 30 of leap years.