Jesse Dunietz

I took a AAAS Science & Technology Policy Fellowship to get a taste of science policy. But "science policy" turned out to mean something very different from what I expected.

Researchers are too focused on whether AI systems can ace tests of dubious value. They should be testing whether systems grasp how the world works.

Have a problem with many competing variables? Why not solve it with a computer algorithm based on cooling metal?

Money. We all use it. But is it real? I mean, you can touch a coin or bill, but who decided that’s worth anything? And what about all those 1’s and 0’s getting swapped and traded by computers thousands of times per second? How are those worth anything?

Good weather forecasts save lives, but scientists are worried that 5G transmissions could drown out frequencies measured by weather satellites, setting weather forecasts back decades.

Silicon transistors allowed computers to shrink from the size of houses to watches in a short time, but engineers are facing a problem: we've almost hit the limit on how small silicon transistors can get.

We use algorithms every day for things like image searches, predictive text, and securing sensitive data. But algorithms show up all over nature, too, in places like your immune system and schools of fish—and computer scientists have learned a lot from studying them.

Every wire, memory chip, and radio link is constantly fending off data corruption with error detecting and correcting codes.

If our efforts to automate trains are any indication, the cars and trucks of the future may be more dependent on human help than we imagine.

You might think that quantum physics was discovered because of some super complicated electron behavior or something, but it was actually invented to explain ovens.

Keeping our data safe and secure is necessary in today's world, but a lot of the encryption we depend on has been in development for thousands of years!

There are labs so silent that many people can't stand being inside them, but that stillness lets us run some of our most sensitive experiments.

Movies like Predator reveal how useful thermal imaging goggles can be, but why do hot objects give off infrared radiation to begin with?

Randomness is important for all kinds of things, from science to security, but to generate true randomness, engineers have turned to some pretty odd tricks.

What are the methods twitter bots use to fool us, and what are some of the challenges in doing so?