AI and Advertising the Rise of a New Era

Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans based on the data that they process. AI has been transforming various industries and sectors, including advertising, where it has been playing a role in many processes, such as programmatic media buying, content creation, and audience analysis. AI has the potential to enhance the effectiveness and efficiency of advertising by creating more personalized, relevant, and engaging experiences for consumers, as well as providing more insights and analytics for advertisers and marketers.

However, AI also poses some challenges and risks for advertising, such as ethical, legal, social, and technical issues, that need to be addressed and mitigated. Therefore, the main argument of this essay is how to harness the power of AI while avoiding its pitfalls in advertising. This essay will discuss the benefits and challenges of AI in advertising, and propose some solutions and recommendations for using AI responsibly and effectively in advertising.

Three Benefits of Advertising with AI

One of the benefits of AI in advertising is that it can create more personalized, relevant, and engaging experiences for consumers. AI can analyze large amounts of data from various sources, such as online behavior, preferences, demographics, and location, to deliver tailored ads that match the needs and interests of each individual. For example, Netflix uses AI to recommend movies and shows based on the viewing history and ratings of each user.

Another benefit of AI in advertising is that it can improve the targeting and optimization of ads, by finding the best channels, platforms, formats, and times to reach the most potential customers. For example, Google Ads uses AI to optimize the bidding and placement of ads based on the performance and goals of each campaign.

A third benefit of AI in advertising is that it can enhance the measurement and evaluation of ads, by providing more accurate and comprehensive metrics and insights on the effectiveness and impact of each ad. For example, IBM Watson uses AI to measure the emotional response and sentiment of consumers to different ads.

Smart Advertising Practices With and Without Artificial Intelligence (AI)

Smart advertising practices are those that aim to reach the right audience, deliver the right message, and achieve the right results. Depending on the goals, budget, and resources of the advertisers, they may choose to use AI or not in their campaigns. Here are some examples of smart advertising practices with and without AI:

With AI: AI can help advertisers create more personalized, relevant, and efficient ads by using data, algorithms, and automation. The key is starting with the right advertising objectives and then using AI to help craft the campaign. For example, AI can generate creative assets based on the advertiser’s website and marketing materials1, optimize bids and targeting based on real-time data, and manage campaigns via chat1. AI can also provide insights and analytics to measure and improve the performance and impact of the ads.

Without AI: Advertisers can still use traditional methods and tools to create and run effective ads without AI. For example, advertisers can conduct market research, segment their audience, and craft their message based on their objectives and value proposition. Advertisers can also use various channels and formats to reach their audience, such as TV, radio, print, online, or outdoor. Advertisers can also track and evaluate their ads using metrics such as reach, impressions, clicks, conversions, or ROI.

Issues with AI and Advertising

AI in advertising has the potential to offer many benefits, such as personalization, efficiency, and creativity. However, it also poses some challenges or risks that need to be addressed.

Ethical issues: AI in advertising may raise ethical concerns about privacy, consent, transparency, and accountability. For example, some AI-powered advertising practices may collect and use personal data without the user's knowledge or permission, or may manipulate the user's emotions or preferences to influence their behavior.

Legal issues: AI in advertising may encounter legal issues related to data protection, consumer protection, intellectual property, and competition. For example, some AI-powered advertising practices may violate the user's rights to data privacy and security, or may infringe on the intellectual property rights of the content creators or owners.

Social issues: AI in advertising may have social impacts on the user's well-being, identity, and diversity. For example, some AI-powered advertising practices may create or reinforce stereotypes, biases, or discrimination, or may affect the user's self-esteem, body image, or social relationships.

Technical issues: AI in advertising may face technical challenges such as reliability, accuracy, and scalability. For example, some AI-powered advertising practices may produce inaccurate, misleading, or harmful results, or may fail to perform as expected or intended.

Problematic AI Advertising Practices

Some examples of problematic AI-powered advertising practices or outcomes are deepfakes, microtargeting, and algorithmic bias.

Deepfakes: Deepfakes are synthetic media that use AI to manipulate or generate realistic images, videos, or audio of people or events. Deepfakes can be used for malicious purposes, such as spreading misinformation, defaming reputations, or impersonating identities. For instance, deepfakes can be used to create fake endorsements, testimonials, or reviews of products or services, or to deceive or influence the user's opinions or decisions .

Microtargeting: Microtargeting is a technique that uses AI to segment and target the user based on their personal data, such as demographics, behaviors, interests, or preferences. Microtargeting can be used for beneficial purposes, such as delivering relevant and customized ads to the user. However, microtargeting can also be used for harmful purposes, such as exploiting the user's vulnerabilities, biases, or emotions, or influencing the user's political or social views. For example, microtargeting can be used to expose the user to extremist, hateful, or divisive content, or to sway the user's vote or participation in elections .

Algorithmic bias: Algorithmic bias is a phenomenon that occurs when AI systems produce unfair, discriminatory, or inaccurate outcomes due to the limitations or flaws of the data, algorithms, or design. Algorithmic bias can affect various aspects of advertising, such as content creation, selection, delivery, or evaluation. For instance, algorithmic bias can result in excluding, misrepresenting, or stereotyping certain groups of users, or in favoring or disadvantaging certain products, services, or brands.

Sources

The Ethics of AI in Advertising - https://www.forbes.com/sites/forbesagencycouncil/2020/07/28/the-ethics-of-ai-in-advertising/

The Dark Side of AI in Advertising - https://www.adweek.com/brand-marketing/the-dark-side-of-ai-in-advertising

The Legal Challenges of AI in Advertising - https://www.lexology.com/library/detail.aspx