Sources: 
Proof-of-work (PoW) methods are increasingly used to slow down bots by requiring them to perform costly computations, but scalpers with sufficient resources continue to bypass these defenses.
Modern AI technologies have made traditional CAPTCHAs, such as image-based and audio-based tests, ineffective as bots can now solve them easily. To counter this, systems like Google's reCAPTCHA v3 analyze user behavior — including mouse movements, click patterns, and browsing history — to detect automated activity.
However, Raphael Michel, creator of the ticketing platform Pretix, highlights the inherent challenge in bot mitigation, known as the
“BAP theorem”: no current solution simultaneously achieves
bot resistance, accessibility, and privacy. This means that while some methods may block bots effectively, they often compromise user accessibility or privacy.
Moreover, PoW methods raise significant ethical concerns due to their energy consumption. These computations, while slowing bots, consume power unnecessarily, contributing to environmental impact. Scalpers, who can afford the computational cost, continue to exploit these systems, undermining their effectiveness.
"Proof-of-work methods slow bots by demanding costly computations, but scalpers can still afford the resources. Worse, these methods consume energy unnecessarily, raising ethical concerns about environmental impact," the report notes.
As bot mitigation evolves, balancing security, user experience, and environmental responsibility remains a complex challenge for developers and platforms worldwide.
Sources: Proof-of-work techniques slow bots by requiring costly computations, but scalpers still bypass CAPTCHAs, raising concerns about energy consumption and environmental impact. Modern AI easily defeats image and audio CAPTCHAs, while systems like reCAPTCHA v3 track user behavior to detect bots, yet no solution balances bot resistance, accessibility, and privacy.
