Marketers must ensure that AI and ML is not coded with unconscious bias
Marketers are embracing diversity, but are they overlooking a critical opportunity? Merkle’s Tracie Kambies discusses why many may be missing the mark when it comes to AI and ML, and what they must do about it.
Diversity, equity and inclusion are more important than ever in our dynamic world. Marketers and their digital agencies have embraced diversity, equity and inclusion (DEI) with enthusiasm and care. They are building their teams to be diverse, changing their brands to be inclusive, and shaping their messages to be just and ethical. DEI rightly must inform every part of the business. This is especially true as more people and organizations realize the importance of DEI in our current moment in history. Rethinking our ethics when it comes to data privacy, personal information and fluid identities is in motion now. Marketers are on it.But are they missing the mark when it comes to artificial intelligence (AI) and machine learning (ML) AI and ML are exciting tools for the modern marketer riding the bleeding edge of technology. AI and ML can be used to hyper-target customer segments, learn from ridiculously deep data sets, improve content, react to the behaviors of millions of consumers and predict how we learn, shop and buy. They are game changers. The best AI/ML experts have their hands full learning how to leverage the technology, keeping up with new developments and changing their business models to adapt to new applications. What hasn’t always happened or been done well is considering the ethics of what they are building.
Considering ethics while buildingAI and ML have their own special challenges in encoding ethics into their artificial brains. The point of AI/ML in marketing is to create bias toward inciting consumer action, such as transacting. The models are built to learn on their own. The incentives are aligned toward marketing KPIs such as increasing sales or building loyalty and engagement. They are fed data sets filled with dimensions of past action, demographics, financials, channels and more.
What they don’t usually get is ethical instructions to guide their outputs. AI and ML, in their current forms, are ethically blind. The ethically-blind AI presents openings for dangerous outcomes. It may produce segments or targets that have undesirable biases against race, gender, sexual preference, identity, age and a host of other discriminations we wouldn’t tolerate in other aspects of life. The ethically-blind AI could reverse much of the positive impact we are achieving through our human-curated activities in our branding or our team-building practices. A modern, ethical organization simply can’t afford to have a non-ethical actor so prominently directing the organization’s marketing behavior. Rethinking our approach while we don’t know exactly what ethical AI/ML looks like, we can begin to rethink how we approach the discipline with an ethics-based mind-set.
Firstly, we need to inject ethical thinking into our design of AI and ML. We need to be conscious of how ethics plays into our algorithms and examine the outputs for moral content. We need to bring a diverse and inclusive mind-set to our AI teams, and the best way to ensure this is to build AI teams that are diverse and inclusive themselves.
We also need to change our incentives so that ethical behavior in AI/ML is encouraged, and that competing incentives don’t impede our ability to act ethically. Marketers and their agencies need to start asking themselves some exploratory questions: Are our DEI objectives clearly accounted for in our AI and ML programs? Are our ethics part of our design process and governance? Do we have a way to measure the ethical impact of our AI and ML outputs? Can we track them before they go to market? Do marketers incentives and KPIs need to be adjusted to accommodate ethical approaches to employing AI/ML
Are we bringing a diverse and inclusive perspective to our AI and ML programs? More precisely, are our teams themselves diverse and inclusive in their composition. So much of AI/ML is designed and performed by agencies and their holding companies, so it is essential for marketers and agencies to be leaders in bringing ethics to these disciplines. We in the industry take great pride in being innovators in this bright and brilliant field. We know it’s not only the future but the now. We must embed our ethics and our deeply-held desires for justice within it now. It’s our duty.