That sudden good movie recommendation of our favorite genre or actor on Netflix. Instagram Ads featuring shoes on sale that we’ve been planning to purchase. It is hyper-personalization, made possible with artificial intelligence (AI). And consumers today have grown to appreciate this. According to McKinsey’s latest data, 71% of people demand personalized interactions.
Yet, beneath the surface of these convenient experiences lies a pressing question. Are our smart devices listening to us and recording our search history? Is this just personalization or surveillance? The line is increasingly blurred. As AI evolves and the majority of businesses integrate technology to scale faster, it also creates ethical dilemmas. How does this impact our privacy and security?
This article examines the advantages and disadvantages of hyper-personalization. And how can businesses transition to privacy-first personalization.
The Benefits of Hyper-Personalization
We’re spoilt for choice. If not this, then that. Whether it’s shopping for shoes online, booking a cab, or ordering food from our favorite restaurant, consumers today are overwhelmed with options for the same offering. At the same time, attention is becoming increasingly scarce. A lot of credit goes to social media. Just one poor experience is enough for people to turn away from business. Perhaps that’s why brands have accelerated the use of hyper-personalization. Unlike standard automation, it works by learning from individual user behaviors. It allows businesses to tailor interactions on a much more human level.
Imagine opening a food delivery app where your favorite food is available at a discounted price or scrolling through a feed that shows only stories that interest you. This can result in impromptu purchases.
For businesses, the benefits are undeniable:
- Higher engagement: Personalized recommendations trigger human emotions. It makes customers feel seen and heard and can double click-through rates (CTR), in comparison with generic messaging.
- Customer loyalty: Sometimes, the cost of retaining a customer can be higher than acquiring a new one because regular marketing and sales strategies may not be effective for specific business types. That said, with personalized AI recommendations, brands can better engage with their customers. And when users feel understood, they tend to return.
- Efficiency: AI cuts through the endless options to serve what matters most. For instance, in an online food delivery app, AI accomplishes this by analyzing vast amounts of data, including past order history, browsing patterns, and reviews.
The Hidden Costs of This Convenience
But the question looms: Is this hyper-personalization or hyper-surveillance? Behind the closed doors of the internet world lies a massive collection of personal data. Our browsing history. Purchasing patterns. Location data. This ocean of information seems to power the algorithms that seem to “know” us all too well.
However, this has also led to some people raising concerns over genuine issues, such as surveillance, consent, and potential data misuse. As in, how safe are our financial transactions? Are our private chats really encrypted? Recent investigations reveal that Meta AI’s app marks private chats as public, raising privacy concerns.
Without proper governance, AI may retain sensitive information, and it poses privacy concerns. Here is how:
- Data overreach: Companies often gather more information than necessary. But is it aligned with our fundamental rights? Right to privacy. And does anyone have the time or patience to read through those privacy policies or terms and conditions? Documents by brands that we’re forced to agree to during sign-ups?
- Opaque systems: There’s no transparency. Most users are unaware of what data is being collected and how it is stored. Or, most importantly, who has access?
- Manipulation risk: Nudging users toward choices that they may not have made freely. Let’s say, a certain political content that an individual may have engaged with in the past. Based on algorithms, the user can be shown content that, at a surface level, may appear to be personalized, but can quickly cross into influencing their beliefs and behaviors. And the user wouldn’t even be aware of this paradigm. It has the most significant impact on developing minds, especially those of teenagers and young adults. Behavioral scientists refer to this communication tactic as “personalized persuasion.”
Thankfully, regulations such as the GDPR and the California Consumer Privacy Act (CCPA) frameworks impose rules on data handling. And for businesses, the good news is that they don’t have to choose between AI-driven efficiency and data privacy. They can have both.
Toward Privacy-First Personalization
Some strategies include:
- Build ethical, trustworthy AI systems: Prioritize transparency. Minimize legal risks. Promote inclusivity. For example, users don’t need to read the 30-page technical and legal terms and conditions (T&Cs) to understand their choices.
- Give user more control: Give people genuine options to opt out. Like on Apple devices, users have the option to deny location sharing.
- Ensure data integrity: Use accurate, up-to-date, and unbiased data to deliver fair and precise results. Also, integrate explainability into AI models. So, users can clearly understand why a decision was made, especially if something doesn’t go as expected.
- Adhere to compliance requirements and monitor consistently: Ensure fair and transparent usage in accordance with local laws. Also, continuously monitor the frameworks and business strategies to ensure AI aligns with ethical standards.
These practices not only mitigate privacy risks but also build long-term trust. At the outset, human oversight and participation remain key. Because AI learns from historical data, and good, ethical human insights can trigger a business that offers personalized services without compromising an individual’s privacy.
Conclusion
Hyper-personalization is empowering because it enables brands to make a meaningful impact on their customers. However, the same tool that’s proving to be advantageous for businesses may also be a form of hyper-surveillance for customers. Sure, people are getting nurtured this way as they’re getting to consume the products (service and content) to their liking. But at what cost?
People should have clear visibility into how AI makes decisions. They should have the right not to share information with which they’re not comfortable, while continuing to have the opportunity to transact with the business. Users should be able to challenge or verify AI-generated outputs. Sensitive details such as one’s identity, medical history, and financial records must be handled with strict safeguards. Such information shouldn’t be stored for later use or exploited, such as selling data to other businesses, and must be used only for intended purposes.
Nevertheless, businesses need not abandon the very thing that’s getting them customers today, AI-driven personalization. Integrating responsible, secure, transparent AI systems that also respect individuals’ privacy should be the way forward. Because only then can businesses succeed in earning people’s trust in the long run. That will also be an accurate measure of AI’s progress.
