In this week’s issue of the Kernel, we’re looking at risk. How do people weigh risk, say, when it comes to losing their livelihoods or even facing jail time for exposing cybersecurity holes? Or, relatedly, when playing Capture the Flag, the hacker game that often comes with a big payoff for the winner? And what’s risk without chance, that risk of the unforeseen, when math, big data, and poker-playing robots are showing us that more things than we realize may be completely predictable?
First, Yael Grauer profiles Carnegie Mellon University’s Plaid Parliament of Pwning, a loose group of hackers who compete worldwide in Capture the Flag tournaments. CTF is a place for budding cybersecurity specialists to show off their skills; prizes can run to the tens of thousands of dollars. The PPP is consistently among the best teams, with its members entertaining job offers from Silicon Valley powerhouses before they’ve even graduated. It’s an unorthodox hobby, and one that players argue hones their abilities and broadens their experience.
CTF provides researchers with a safe zone for trying new techniques and exploits. In the real world, unfortunately, probing for security holes can have negative consequences. As David Silverberg details, a growing number of cybersecurity experts have found themselves on the wrong side of the law simply for publicizing flaws. That can mean an early-morning visit from FBI agents, guns drawn and pounding on your door. Critics argue that companies are using law enforcement to intimidate researchers who’ve embarrassed them; while the law remains murky, some experts have vowed not to share their findings. That means, of course, fewer companies learning about vulnerabilities from people with good intentions. It’s likely to make everyone less safe online.
Finally, I interview Adam Kucharski about the interplay of math, science, and gambling. As he notes, the three have long affected one another, from the development of probability theory to the advances in today’s poker-playing bots. Unsurprisingly, those techniques borrow from cutting-edge science, and their advances then feed back into our broader knowledge. As Kucharski points out, there’s a familiar resemblance between the algorithms that make stock market decisions faster than humans can comprehend and the lines of code that define poker-playing bots capable of defeating their creators. As our machines continue to outpace their makers, questions inevitably arise about what’s chance, what’s predictable, and, ultimately, what is human.
Enjoy the issue.
Photo via sputnik/Flickr