6 ms·

Seems reminiscent of the tales of early 2000s Google interviews, of the "estimate how many golf balls fit in an airplane" variety. I'm not convinced this offer

Seems reminiscent of the tales of early 2000s Google interviews, of the "estimate how many golf balls fit in an airplane" variety. I'm not convinced this offers a useful selection criteria other than boosting your unconscious bias on who "seems smart", but on the other hand I'm also not convinced it's any worse than the standard modern Leetcode interview.

Swizec 6y ago
Funnily that old style of question is far closer to my day-to-day as an engineer than a leetcode algorithms question. Most of my job involves figuring out solutions to fuzzy problems based on unknown constraints, undiscovered requirements, and often unclear end-goals. "How would you fill this airplane with golf balls?" is a fantastic question. If the candidate doesn't reply with "Why? What are you really trying to achieve?", they're gonna do poorly in modern software development. Caveat: This does not apply to junior positions where you are expected to bang out code based on super fleshed out requirements and constraints.
- dragonsngoblins 6y ago
  I suppose it depends on how you grade the answers. Like I have bad spatial awareness in terms of how big things like planes are. I genuinely don't really have an idea how long a commercial airliner is, or how big a ping pong ball is. I feel like I'd do ok if I could get reasonable approximate values for things like the size of the plane, the balls, the seats, etc. if I also have to supply those values myself the end result is likely to be off The end result being off is fine if I am being graded based on my thought process, but a disaster if I am being graded at having an idea of the size of airplanes before walking into the interview.
  - Swizec 6y ago
    Like I said, the point of this question isn’t to seek your domain expertise, the point is to see how you use other people’s domain expertise to create a [software] system.
    - dragonsngoblins 6y ago
      The way you ask it sure. I'm just not sure that is how everyone asks it, though maybe it is. I've never been asked something quite like that before but some comments I've seen around seem to imply some people want a close to accurate answer.
  - dogfoods 6y ago
    Commercial airliners vary in size more than an order of magnitude anyway. There are commercial aircraft that are shorter than an A380 is tall.
    - kortilla 6y ago
      The fuselage of a 737 is the same diameter as the engine of a 777.
- RogerL 6y ago
  Why? Isn't the better question "how would you solve <the actual thing they are being hired to solve>"? I hire people to track objects via computer vision. I ask them "hey, here's a system I want, what approaches would you take", and explain that this is a 3 year research project, of course they will be giving simplistic and wrong answers and there is knowledge asymmetry here, but I'll inform you as you go as to what works and not. "Optical flow". Okay, why? What's the general algorithm? Okay, so it turns out it doesn't work in our situation because X,Y,Z. Any ideas on what you'd look at next. And so on. Because that is exactly how my day-to-day conversations and work goes. Bounce ideas off of co-workers, latch onto something that seems promising, explore, maybe it works, maybe it fails. If it fails, what does that tell you about what to try next. Along the way you can have them code a tiny piece of something they mentioned if you want to see some code. But basically you are seeing if they understand the domain you are working in (which is not golf balls on airplanes), if they have some (not comprehensive) knowledge of the domain, and if they understand book solutions don't necessarily deal with the messiness of the real world and can adapt approaches to appropriately (i.e. a 20sec/frame algorithm is not going to cut it when I need 180fps). It bothers me that this is still somewhat unfair due to the vast information asymmetry, but I try to deal with that. And my own biases can creep in. Are they mostly using 1980s style image processing techniques? Do they understand Bayes? Do they throw ML at problems that aren't tractable that way? It's unlikely that their past experience & preferences reflect exactly what we need. What is important - can they adapt, or even better, communicate why my choices are wrong and theirs are right (I don't need a robot to grind out code reflecting my ideas, I need them to figure things out and solve things in a fairly scientific manner). So those are the questions I try to ask. I have no evidence that I get it right, but I haven't been disappointed with the hires.
  - 908B64B197 6y ago
    I think your approach is pretty optimal, but at larger companies the candidates might be interviewing for the company as a whole and not for a specific team.
  - milesvp 6y ago
    Interesting you mention 80’s style image processing techniques. Please take care with these kinds of biases. Often older techniques are superior than ones that are merely fashionable today. I’ve also been around long enough to see pendulums go back and forth at least once in the AI realm, never mind tech in general. Mind you, I’m not saying you’re wrong to discount people who fail to stay abreast in their field, just know that sometimes there is wisdom in ignoring popular trends, or revisiting old techniques that might benefit from a different landscape.
908B64B197 6y ago
I don't think they were looking for the right answer; I think the goal of that type of questions is to see how does the candidate approaches it. It's especially valuable with college hires. Some candidates will simply freeze if they don't know the answer. Some will try to estimate the dimensions and come up with an estimate. I think Google wanted to try to anticipate what a person would do when stuck by asking these types of questions.

Swizec 6y ago

Funnily that old style of question is far closer to my day-to-day as an engineer than a leetcode algorithms question. Most of my job involves figuring out solutions to fuzzy problems based on unknown constraints, undiscovered requirements, and often unclear end-goals. "How would you fill this airplane with golf balls?" is a fantastic question. If the candidate doesn't reply with "Why? What are you really trying to achieve?", they're gonna do poorly in modern software development. Caveat: This does not apply to junior positions where you are expected to bang out code based on super fleshed out requirements and constraints.

dragonsngoblins 6y ago
I suppose it depends on how you grade the answers. Like I have bad spatial awareness in terms of how big things like planes are. I genuinely don't really have an idea how long a commercial airliner is, or how big a ping pong ball is. I feel like I'd do ok if I could get reasonable approximate values for things like the size of the plane, the balls, the seats, etc. if I also have to supply those values myself the end result is likely to be off The end result being off is fine if I am being graded based on my thought process, but a disaster if I am being graded at having an idea of the size of airplanes before walking into the interview.
- Swizec 6y ago
  Like I said, the point of this question isn’t to seek your domain expertise, the point is to see how you use other people’s domain expertise to create a [software] system.
  - dragonsngoblins 6y ago
    The way you ask it sure. I'm just not sure that is how everyone asks it, though maybe it is. I've never been asked something quite like that before but some comments I've seen around seem to imply some people want a close to accurate answer.
- dogfoods 6y ago
  Commercial airliners vary in size more than an order of magnitude anyway. There are commercial aircraft that are shorter than an A380 is tall.
  - kortilla 6y ago
    The fuselage of a 737 is the same diameter as the engine of a 777.
RogerL 6y ago
Why? Isn't the better question "how would you solve <the actual thing they are being hired to solve>"? I hire people to track objects via computer vision. I ask them "hey, here's a system I want, what approaches would you take", and explain that this is a 3 year research project, of course they will be giving simplistic and wrong answers and there is knowledge asymmetry here, but I'll inform you as you go as to what works and not. "Optical flow". Okay, why? What's the general algorithm? Okay, so it turns out it doesn't work in our situation because X,Y,Z. Any ideas on what you'd look at next. And so on. Because that is exactly how my day-to-day conversations and work goes. Bounce ideas off of co-workers, latch onto something that seems promising, explore, maybe it works, maybe it fails. If it fails, what does that tell you about what to try next. Along the way you can have them code a tiny piece of something they mentioned if you want to see some code. But basically you are seeing if they understand the domain you are working in (which is not golf balls on airplanes), if they have some (not comprehensive) knowledge of the domain, and if they understand book solutions don't necessarily deal with the messiness of the real world and can adapt approaches to appropriately (i.e. a 20sec/frame algorithm is not going to cut it when I need 180fps). It bothers me that this is still somewhat unfair due to the vast information asymmetry, but I try to deal with that. And my own biases can creep in. Are they mostly using 1980s style image processing techniques? Do they understand Bayes? Do they throw ML at problems that aren't tractable that way? It's unlikely that their past experience & preferences reflect exactly what we need. What is important - can they adapt, or even better, communicate why my choices are wrong and theirs are right (I don't need a robot to grind out code reflecting my ideas, I need them to figure things out and solve things in a fairly scientific manner). So those are the questions I try to ask. I have no evidence that I get it right, but I haven't been disappointed with the hires.
- 908B64B197 6y ago
  I think your approach is pretty optimal, but at larger companies the candidates might be interviewing for the company as a whole and not for a specific team.
- milesvp 6y ago
  Interesting you mention 80’s style image processing techniques. Please take care with these kinds of biases. Often older techniques are superior than ones that are merely fashionable today. I’ve also been around long enough to see pendulums go back and forth at least once in the AI realm, never mind tech in general. Mind you, I’m not saying you’re wrong to discount people who fail to stay abreast in their field, just know that sometimes there is wisdom in ignoring popular trends, or revisiting old techniques that might benefit from a different landscape.

908B64B197 6y ago

I don't think they were looking for the right answer; I think the goal of that type of questions is to see how does the candidate approaches it. It's especially valuable with college hires. Some candidates will simply freeze if they don't know the answer. Some will try to estimate the dimensions and come up with an estimate. I think Google wanted to try to anticipate what a person would do when stuck by asking these types of questions.