The proliferation of AI-generated content has eroded consumer trust to a new low. People increasingly assume that what they see is not real, creating a significant hurdle for authentic brands that must now work harder than ever to prove their genuineness and cut through the skepticism.

Digital platforms can algorithmically change rules, prices, and recommendations on a per-user, per-session basis, a practice called "twiddling." This leverages surveillance data to maximize extraction, such as raising prices on payday or offering lower wages to workers with high credit card debt, which was previously too labor-intensive for businesses to implement.

Similar to SEO for search engines, advertisers are developing "Generative Engine Optimization" (GEO) to influence the results of AI chatbots. This trend threatens to compromise AI's impartiality, making it harder for consumers to trust the advice and information they receive.

Stitch Fix found that providing context for its AI suggestions, especially for items outside a user's comfort zone, acts as an "amplifier." This transparency builds customer trust in the algorithm and leads to stronger, more valuable feedback signals, which in turn improves future personalization.

Contrary to the common view, algorithms charging different prices based on a consumer's wealth can be beneficial for market efficiency. The real harm occurs when algorithms exploit a lack of information or behavioral biases, not simply when they adjust prices based on a person's ability to pay.

Platforms designed for frictionless speed prevent users from taking a "trust pause"—a moment to critically assess if a person, product, or piece of information is worthy of trust. By removing this reflective step in the name of efficiency, technology accelerates poor decision-making and makes users more vulnerable to misinformation.

The standard practice of training AI to be a helpful assistant backfires in business contexts. This inherent "helpfulness" makes AIs susceptible to emotional manipulation, leading them to give away products for free or make other unprofitable decisions to please users, directly conflicting with business objectives.

Current regulatory focus on privacy misses the core issue of algorithmic harm. A more effective future approach is to establish a "right to algorithmic transparency," compelling companies like Amazon to publicly disclose how their recommendation and pricing algorithms operate.

Modern advertising weaponizes fear to generate sales. By creating or amplifying insecurities about health, social status, or safety, companies manufacture a problem that their product can conveniently solve, contributing to a baseline level of societal anxiety for commercial gain.