Two Technology Stories Reshaping Security and Health
The latest edition of MIT Technology Review's The Download newsletter brings together two seemingly unrelated but equally compelling stories about how technology is reshaping our world. On one hand, criminal networks are wielding sophisticated electronic tools to steal luxury vehicles at unprecedented rates. On the other, a visionary researcher is harnessing artificial intelligence to address one of humanity's most urgent health crises: the growing threat of antimicrobial resistance.
These parallel narratives illustrate a fundamental tension in the technology landscape. The same tools and techniques that enable criminal innovation also hold the potential to solve existential challenges. Understanding both sides of this equation is essential for navigating the complex technological environment that defines modern life.
When Technology Enables Crime
The epidemic of luxury car theft represents a striking case study in how connected technology creates new vulnerabilities. Modern vehicles, packed with electronic systems designed for convenience, have inadvertently become easier targets for thieves equipped with the right tools. Relay devices that amplify key fob signals, CAN bus injection tools that hijack a vehicle's internal network, and GPS jammers that blind tracking systems have all become widely available on underground markets.
The targets are specific and lucrative. Lamborghinis, Rolls-Royces, Bentleys, and other exotics worth hundreds of thousands of dollars are being systematically identified, stolen, and exported by organized criminal enterprises that operate with disturbing professionalism. The losses are staggering, and the recovery rates are low, particularly once a vehicle crosses international borders.
What makes this story particularly relevant to the broader technology community is the speed of the arms race. Automakers introduce new security measures, and criminal groups adapt their tools in response, often within weeks. It is a microcosm of the cybersecurity challenge that affects every connected device, from smartphones to industrial control systems. The luxury car theft epidemic is not just a crime story; it is a technology story with implications that extend far beyond the automotive industry.
Turning AI Loose on Antimicrobial Resistance
On the other side of the technology spectrum, César de la Fuente, a researcher at the University of Pennsylvania, is demonstrating the extraordinary potential of artificial intelligence to solve problems that have stymied conventional approaches. His target is antimicrobial resistance, a crisis that the World Health Organization has identified as one of the top ten global public health threats.
Antimicrobial resistance occurs when bacteria, viruses, fungi, and parasites evolve to resist the drugs designed to kill them. The result is infections that become increasingly difficult or impossible to treat, turning routine medical procedures into life-threatening events. The pipeline of new antibiotics has slowed to a trickle in recent decades, as pharmaceutical companies have shifted investment toward more profitable drug categories.
De la Fuente's approach is radically different from traditional antibiotic discovery, which typically involves screening soil samples and microbial cultures for compounds with antimicrobial properties. Instead, his team uses machine learning algorithms to analyze vast databases of biological sequences, searching for peptides with potential antibiotic activity in places no one has thought to look before.
The AI systems can evaluate millions of candidate molecules in a fraction of the time it would take human researchers to screen even a small subset. More importantly, the algorithms can identify patterns and structural features associated with antimicrobial activity that might not be apparent to human analysts, opening up entirely new chemical spaces for drug discovery.
Unexpected Sources of New Antibiotics
One of the most remarkable aspects of de la Fuente's work is the range of sources he has explored. His team has identified potential antibiotic compounds in the genomes of extinct organisms, in the proteins of the human body itself, and in the vast troves of metagenomic data collected from environments around the world. The idea that the next breakthrough antibiotic might be hiding in the genetic code of a Neanderthal or in the chemistry of our own immune system challenges conventional assumptions about where new drugs come from.
The computational approach also accelerates the process of moving from discovery to development. Once a promising peptide is identified, the AI can help predict its behavior in biological systems, estimate its toxicity, and suggest modifications that might improve its effectiveness. This kind of in-silico optimization can shave years off the traditional drug development timeline, a critical advantage when resistant infections are killing an estimated 1.27 million people annually.
The Broader Lesson
Together, these two stories from The Download newsletter underscore a central theme of our technological moment: the tools we create are morally neutral, and their impact depends entirely on how they are deployed. Electronic devices that exploit vehicle security systems and AI algorithms that discover life-saving drugs are both products of the same culture of innovation. The challenge for society is to create incentives and guardrails that maximize the beneficial applications while minimizing the harmful ones.
The luxury car theft epidemic demands better security engineering, international law enforcement cooperation, and regulatory frameworks that hold technology sellers accountable. The antimicrobial resistance crisis demands sustained investment in AI-driven drug discovery, reformed incentive structures for pharmaceutical development, and global coordination to ensure new antibiotics reach the patients who need them most. In both cases, technology alone is not enough. It must be paired with the institutional capacity to direct it toward constructive ends.
This article is based on reporting by MIT Technology Review. Read the original article.
