AI could mitigate bias in advertising tech

Significant changes are afoot in the advertising industry. In the last month alone, Netflix announced it may enter the ad business, lawmakers introduced bipartisan bills to throttle Google’s digital ad dominance and Facebook rolled out changes to help advertisers achieve more precision in their targeting. As major players prepare, advertisers have an opportunity to manage these changes in a way that optimizes ad spending and addresses the problem of bias in ad technology.

Bias is a well-known issue for the ad industry, and the programmatic technologies the companies have adopted to supercharge marketing campaigns may not be improving matters. Nearly $1 trillion of digital media flows through programmatic engines that segment and target specific audiences, sometimes missing large consumer groups in the process. Not only can that contribute to improper bias, but it’s also an inefficient way to spend your ad dollars.

The industry needs to do better, and we need to start now.

Why now? Marketers are rebuilding their technology infrastructures to benefit from artificial intelligence (AI). Netflix already relies heavily on AI to personalize content, and Nike uses it to sell to consumers directly. These developments require that marketers create a foundation of trust with consumers, and to keep pace with the industry, it must be done in a way that scales.

It’s why, as an industry, we must tap into AI and leverage the powerful tools at our disposal to help mitigate the bias problem.

As AI algorithms come to dominate in the industry’s efforts to find audiences and serve ads, we must integrate mitigation tools to avoid reinforcing biased thinking. That is, rather than letting AI exacerbate the problem, we must make the technology part of the solution. Doing this can help bring fairness by adapting ad buying behavior to reach more diverse audiences. By embedding fairness metrics and AI algorithms into the core of marketing processes, we can deliver a more effective value exchange between consumers and brands and potentially generate improved ROI on media dollars spent.

Scaling fairness

The technology needed to mitigate bias in ads already exists, and companies in finance, human capital management, healthcare, education and many other industries are testing open-source toolkits that build bias mitigation into their marketing processes. It’s time for the advertising industry to make a concerted effort to build fairness into our marketing technology as well.

AI bias occurs when the machine learning process used to create AI models places certain privileged groups at a systematic advantage and certain unprivileged groups at a systematic disadvantage. Such bias could impact a financial institution’s ability to fairly assign credit scores or issue mortgages, or it could affect an insurance company’s ability to accurately predict medical expenditures for different clients.

In advertising, bias can prevent consumers from being exposed to certain brands and information based on flawed algorithmic analysis. Often, this does harm to both the consumers and the brands. Embedding fairness metrics and AI algorithms into the marketing processes could enable the technology to, for example, automatically — and at scale — generate anomaly reports when something doesn’t look right with the data indexing as media plans are executing.

If such a fairness solution can be applied to the core of how we do marketing today, we could not only help reduce bias, but also potentially help brands get a better return on their media spending.

Open for businesses

Addressing this problem is bigger than just one company. We need the best minds and resources in the marketing industry working together to address systematic bias in advertising. If our industry refuses to acknowledge the problem and fails to try to embed fairness into our core marketing processes and tools, then we could be facing a future dominated by ad platform consolidation, opaque metrics and automation-enhanced bias. An open, transparent approach to governance, AI and data sharing can help brands take back control of how they communicate with their audiences.

Frankly, I don’t see how anyone in our industry can be aware of the potential bias problem and not be passionate about addressing it. It’s the right thing to do for society, in that you’re making information about products and services available to people who, because of bias, might not be exposed to those things. And it’s the right thing to do for brands, helping them better connect with a larger set of consumers that can help drive more business.

I’m calling for an industry-wide effort encompassing every team, function, brand, agency and ad-tech provider. Leaders across the industry must commit to tackling bias together, if we are to make our industry better, more equitable, and more fit for the future.

Bob Lord is the IBM senior vice president for The Weather Company and Alliances.