The Ethics of Using AI in Advertising
For example, most would agree its acceptable to leverage AI to target a consumer who shows interest in sports cars. But what if you also knew that consumer was deep in debt and lacked impulse control, had multiple moving violations, and had a history of drug and alcohol abuse? Is it still okay to market a fast car to this person, in a way that would make it nearly irresistible?
ByAdrianne PasquarelliandMegan Graham- 3 days ago
As anindustry, advertising has long been obsessed with understanding human behavior. The ability of artificial intelligence (AI) systems to transform vast amounts of complex, ambiguous information into insight is driving personal analysis into market behavior. There are nearly 2 billion Facebook users globally. About 200 billion tweets are shared on Twitter every year. Google processes 40,000+ searches every second. We can now assess the entirety of an individuals social activity: every word, every picture, every emoji.
Some call this algorithmic transparency. Transparency, however, is not realistic in this context, because the most valuable intellectual property of an AI lives in the algorithm, and agencies arent eager to share that code openly. In addition, sophisticated machine-learning systems can be a black box, unable to adequately explain their rationale for any particular choice. When you dont know the internal functions and benefits — the recipe for authentic trust isnt there. Explainability means ensuring the ability to clearly explain the decisions an AI makes and why.
Aside from these fears, there are more practical considerations around the use of AI in advertising: inherently biased data, algorithms that make flawed decisions and violations of personal privacy.
Algorithms– AI engines contain codes that refine raw data into insight. They dictate how the AI system operates, but are designed and developed by humans. Which means that their instructions should be explainable.
For these reasons, we need a code of ethics that will govern our use of AI in marketing applications, and ensure transparency and trust in our profession.
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Rather than judging each case on its moral merits, its more effective to establish guidelines that remove the guesswork. A system of transparency — in which the consumer is more of a partner in his or her marketing, rather than an unwitting target of it — is the ethical way forward.
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The more complete our understanding of an individual, the more persuasive our marketing can be. But each new insight into a consumer raises new questions about our moral obligations to that individual — and to society at large.
Add to that location-based data from mobile phones, transactional data from credit cards and adjacent data sets like news and weather. When machine learning and advanced algorithms are applied to these oceans of digital information, we can intimately understand the motivations of almost every consumer.
But AI also introduces troubling ethical considerations. Advertisers may soon know us better than we know ourselves. Theyll understand more than just our demographics. Theyll understand our most personal motivations and vulnerabilities. Worrisomely, they may elevate the art of persuasion to the science of behavior control.
Often, these data sets reflect preexisting human biases. Microsofts unfortunate experience with Tay, the conversation bot that reproduced the hateful speech of those that engaged it, is probably the most infamous case study.
Such a system would include three primary aspects: data, algorithms and consumer choice.
Consumer choice– Simply put, consumers should be aware of the techniques being used to market to them, and have the option of participating in those campaigns. In order to make an informed choice, consumers need a clear explanation of the value exchange in any given campaign. What are they giving up? What are they getting in return? And they should be allowed to opt out if they are uncomfortable with the transaction.
Data– AI is fueled by data, which is used to train algorithms and sustain the system. If data is inaccurate or biased in any way, those weaknesses will be reflected in decisions made by the AI system.
Jason Jercinovic is global head of marketing innovation and global brand director at Havas.
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ByJason Jercinovic.Published onJune 26, 2017.
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We are advertisers, not ethicists. However, that doesnt excuse us from considering the social impact of the work we do. We know theres a line that can — and probably will — be crossed with AI. Therefore, we must establish best practices for the use of AI in advertising, and understand the differences between what we can know, should know, and shouldnt know.
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These are undeniably powerful tools, and no one can blame the advertising industry for rapidly adopting them.
