AI is already helping companies understand their customers better. And many theorize that AI will soon know us better than we know ourselves. In an age where data has become commoditized, but the insights and profits from data are the rather exclusive belonging of a few enormous tech players, what better way to harness consumer trust and loyalty than by giving people back valuable insights that can turn them not just into smarter and better customers, but also more self-aware humans? After all, if our choices as consumers are becoming more and more data-driven, but that data does not actually increase consumer sophistication or rationality, that’s a huge missed opportunity. We must democratize the knowledge that algorithms have on us, at least by making sure that companies have to share the personal insights they’ve gathered with us. Importantly, brands will enhance their ethical reputation and trustworthiness if they share their insights with consumers; persuading them that there is no conflict between knowing them well, and helping them know themselves well, when done in an ethical and transparent way.
Self-knowledge is the cornerstone of human identity. Without it, we wouldn’t be able to construct a logical story of who we are, which would make our experience of life, and interactions with others, chaotic, irrational, and unbearable. And yet, self-knowledge is a hard skill to master, with research suggesting that only 10-15% of people are self-aware. In fact, if there is one consistent finding in the history of psychology, it is that self-deception is far more common than self-knowledge.
Enter AI (artificial intelligence). Though in essence still a prediction machine, as it basically consists of algorithms capable of (a) finding patterns in large datasets, and (b) training themselves to get “smarter” (increase their predictive accuracy), there are clear reasons to expect AI to also improve our ability to understand things, including ourselves.
This assumption is particularly relevant in consumer marketing, a field in which AI has pioneered algorithmic personalization, including targeted nudges to not just predict, but also influence human behavior. If this sounds too technical or abstract, here are some simple everyday examples you are surely familiar with:
- Netflix recommending movies on the basis of what you (and others like you) have watched before
- Amazon recommending products (e.g., cosmetics, sneakers, books, etc.) on the basis of what you (and others like you) have bought before
- Spotify recommending songs on the basis of what you (and others like you) have listened to before
- Perhaps most famously, Google’s search engine guessing what we are probably searching for (based on what other people have searched, especially when they share certain features with us)
- The most widely discussed (and impressive) example today: ChatGPT’s ability to compare our questions to large language databases to interpret and produce the information we need
Although the widespread adoption of these platforms provides compelling evidence for the value of AI to consumers, their AI engines do little to improve our self-knowledge. This creates two problems. First, while our choices may become more data-driven, they do not increase consumer sophistication or rationality — a missed opportunity, especially in the face of growing product supply and sophistication. Second, when the algorithms do work, they may come across as “creepy”: how did they know what I want even when I didn’t know, and what other stuff do they know about me?
Perhaps more importantly, to avoid the dystopian scenario predicted by Yuval Harari and others that AI will soon know us better than we know ourselves, we must democratize the knowledge that algorithms have on us, at least by making sure that companies have to share the personal insights they’ve gathered with us. Consider how ChatGPT will have advanced its knowledge of humanity after its recent interactions with millions of consumers (gaining users at a faster rate than TikTok and Instagram did), without really boosting our self-knowledge.
So, here’s an idea for how consumer AI and algorithmic personalization based on machine-learning and digital marketing might evolve in the near future: by helping us understand who we are, and what our choices actually say about us. Note that the scientific basis for this is well-established, and predates the recent AI age (which I highlight in my latest book, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique). Here are a few findings worthy of consideration:
Even our most trivial choices, including our clothing, email signatures, and food preferences, reveal central aspects of our identity.
Marketers have known this for years, which is why the real choice between Pepsi and Coke, Nike and Adidas, Mac and PC, is not based on functional or rational reasons, but rather on identification with the brand, which itself rests on our interpretation of that brand’s personality. The more similar you think a brand is to your personality, the more you will “fit” with it, and gravitate towards it. Importantly, your perceived similarity with a brand may be entirely subjective or aspirational (e.g., people like Macs not because they are cool and creative, but because they would love to be seen as such, and people like Pepsi more than Coke, not because they are contrarian and rebellious, but because they would love to be… and so on). In these ways, brands and products help us attain our “ideal self”, boosting our image of ourselves.
The opportunity for AI, then, would be to make us aware of the alignment (and gaps) between how we want to be seen, and what are brand and product choices convey about us: For example, “consumers who buy X or watch Y tend to have X values or Y personality.” In fact, as Nathalie Nahai argues in her latest book, Business Unusual, consumers are extremely committed to adjusting their choices based on the reputation of brands, including their moral and political orientation.
There are reliable and systematic links between our preferences and our personality traits.
There are few exceptions to this rule, and the list of correlations between human personality traits and product preferences is too extensive to even summarize. But consider a few examples: your choice of music reveals the degree to which you are extraverted, curious, and neurotic; your choice of movies reveals the degree to which you are intelligent, conscientious, and agreeable; your Facebook data reveals whether you are conservative or liberal, sociable or introverted, optimistic or pessimistic; your tweets reveal whether you are narcissistic or not, and so on. Importantly, AI could be used as a real-time coach, giving us regular feedback on how our daily patterns of behaviors express underlying needs, moods, and motivations. Just as wearables can translate physiological signals into actionable feedback on our fitness, energy, sleepiness, or stress levels, AI could detect changing patterns to our habits to alert us about increases in negative or positive affect, curiosity, or aggression.
Brands and consumers have a mutual interest in understanding consumers’ personalities.
This accelerated in the 1950s, when marketing campaigns were grounded in focus groups and telephone surveys to segment customers “psychographically” with the purpose of improving their offers, products, and services. With AI, we can get a much more granular and personalized version of this, updated in real-time, which should enhance the connection between brands and consumers.
A brand is a promise to deliver. Deliver what? What people want or need. This requires brands to understand who people are. The process for doing that requires nothing more than what is in place already: extensive data on consumers’ behaviors, and AI capabilities to translate that data into insights. Importantly, brands will enhance their ethical reputation and trustworthiness if they share this understanding with consumers; persuading them that there is no conflict between knowing them well, and helping them know themselves well, when done in an ethical and transparent way.
In an age where data has become commoditized, but the insights and profits from data are the rather exclusive belonging of a few ginormous tech players, what better way to harness consumer trust and loyalty than by giving them back valuable insights that can turn them not just into smarter and better customers, but also more self-aware humans?
