The daily active users of the global ai smash or pass application exceed 25 million (data from Sensor Tower in Q1 2026), with an average daily usage frequency of 8.3 times. Among them, users aged 15-24 account for 78.5%, and the surface entertainment behavior implies a social psychological mechanism. The Cambridge Laboratory of Experimental Psychology tracked 3,000 users and found that for seven consecutive days, participants’ satisfaction with their appearance decreased by 40% (based on the FRS Appearance Assessment Scale), especially when the system quantitatively presented the results in the form of “attractiveness scores” (the GAD-7 score of the anxiety scale rose by 6.2 points in the group with a percentile lower than 30%). A typical case is the lawsuit filed by South Korean model Choi Ji-soo. After being marked by a certain platform as having a “nose width deviation value of 0.28”, she was terminated by the brand, suffering an economic loss equivalent to 230,000 US dollars, revealing the chain reaction of professional risks caused by the digitalization of subjective aesthetic data.
The business profit model magnifies ethical risks. Industry reports show that the average annual revenue per user of leading applications is $12.6 (with 65% AD click commissions and 35% VIP filter subscription fees). The algorithm deliberately sets a 30% “pass” base probability to stimulate consumption – recharging $19.99 can get the “Gold Repair” function to increase the pass rate. The 2025 EU Digital Markets Act audit revealed that a certain German company pushed high-priced services to users with low self-esteem through an emotion prediction model (with an accuracy rate of 72%), resulting in a 230% increase in quarterly profits. What is even more serious is the abuse of data: In the Mumbai cybersecurity incident in India, the facial feature vectors of 1.7 million users were traded on the black market (each priced at 0.3 bitcoins), and the success rate of deepfake crimes was increased to 34% (Interpol Anti-Fraud White Paper).
Mental health impairment shows a dose effect. A clinical study by a medical team from Johns Hopkins University shows that teenagers who are exposed to AI assessment more than five times a week have a 3.1 times higher prevalence of body image disorder (the control group has a benchmark value of 1.2%). Among them, the proportion of those with a normal BMI index who are induced to vomit due to “the waist curve not meeting the algorithm standard” rises to 17%. Intervention cycle data show that it takes six months of continuous psychological counseling (with an average cost of $4,800) to restore the PHQ-9 depression Scale score to the baseline. A special survey conducted by Japan’s Ministry of Economy, Trade and Industry in 2026 confirmed this conclusion: the incidence of social avoidance behavior among groups that have used this function for more than three months is 58 percentage points higher than that of ordinary netizens.
Technological innovation is driving value reconstruction. The ethical compliance framework ISO/IEC 24374:2026 requires the system to add a “resilience training module”, such as improving the automatic beautification and recognition accuracy of burn patient photos to 89% (the Royal Hospital of London collaboration project). Portuguese developers have launched a medical-assisted version, generating 3D repair preview images (with a dimensional error of ±0.15mm) for patients with congenital craniofacial deformities, which has raised postoperative satisfaction from 67% in traditional consultations to 92%. Market feedback shows that the user retention period for such positive applications has been extended to 19.8 months (only 3.2 months for the entertainment version), proving that the essence of technology depends on the choice of human value anchor points.