4 ms·

> "The more data we have on what happens over the next few days is going to really accelerate our ability to retrain our AI systems and then help all of you acc

by mabbo 7y ago

> "The more data we have on what happens over the next few days is going to really accelerate our ability to retrain our AI systems and then help all of you accurately understand tenant risk moving forward into this new world," This is actually dumb in terms of ML, and really dumb in terms of discrimination. Given someone missed rent April 1st 2020, what does that tell you going forward about their future? Does it imply they're likely to miss rent again someday? Far less than the same data point any other time before. So it's not useful that way. So why get these data points about people? Perhaps what it does imply is that they may have poor health? Or a disability? Or that they don't have a university degree? Or (data still coming as to this relationship) that they are more likely to be a specific race? I feel that what these folks are really doing is trying to have their model learn to predict "won't pay rent" based on a data point that implies all the things they're not allowed to train their model to predict with due to obvious discrimination laws. Edit 5 minutes later: It could be innocent stupidity too. Hanlon's razor is important.

T-hawk 7y ago
There's value in the converse of that data point, though, right? If someone made rent on April 1st (and maybe even more importantly May 1st), that might be an even stronger signal that they'll continue to do so without interruption.
- thaumasiotes 7y ago
  Depends on how common each is. It's a signal that puts people in the top or bottom X% of renters. If knowing someone is in the bottom 90% of renters isn't that useful, then knowing someone else is in the top 10% is, yes. If the threshold is closer to the median, then both sides are closer in usefulness to each other. I'd be pretty surprised if making rent in April was really at the 90th percentile, though.
- phkahler 7y ago
  The big differentiator is going to white collar jobs. There will be others, but it doesnt take an AI to figure out who is at risk.
  - tobylane 7y ago
    The UK government announced and started support for pay (income tax) as you earn employees a while before support for the self employed/contractors, so maybe the AI prefers standard salaried employment above all else.
    - NullPrefix 7y ago
      > maybe the AI prefers standard salaried employment above all else. Is it wrong for AI to have the same biases as the general population?
chickenpotpie 7y ago
> Landlord service Naborly creates 'blacklist' of tenants who are nonessential and can't work from home I agree this seems like bad ML. Why assign so much weight to a once a century event?
- beckingz 7y ago
  Check back in next month?
clairity 7y ago
the whole concept of predicting human behavior on very sparse and backward-looking data is problematic, not just in this one instance. even in cases where we have a ginormous amount of data (equity markets, self-driving cars) and a recognizable set of rules/heuristics does it fail to predict human behavior well enough to depend on predictive models. we're infinitely complex relative to these models. they just don't seem to have enough degrees of freedom to pin us down (yet; who knows in a thousand years). in the case of landlords, it's tantalizing to pay a few bucks and get some comfort that you've done your due diligence, rather than facing the uncomfortable reality and esteem hit that there is no certainty predicting future behavior. and renters pay for that ignorance and moral hazard.
- ballenf 7y ago
  Landlords don't need to "predict human behavior" they only need to reduce their risk a little more than their competitors to have a slight edge in the market.
nomel 7y ago
Assuming the blacklist is changed into a new variable in the risk assessment equation, a missed payment for April 1st could probably answer the question "did this person have enough saved to cover one rent check?". This assumes they didn't intentional skip rent with forgiveness in mind, to save for upcoming months without work. I can't imagine missed payments after April will be useful.
- chickenpotpie 7y ago
  The lowest estimate I can find for percentage of Americans that live paycheck to paycheck is 49% and the highest is 80%. This just feels like a list of people who didn't get paid in March.
onetimemanytime 7y ago
Ummm...you will get a "don't rent to John" report based on Covid non-payment, not a detailed thing
deleted 7y ago
[deleted]
TrackerFF 7y ago
Yes, it's bad data. They're going to use black-swan events for their training data - which is complete nonsense. Their training sets will be full of false-negatives (good renters that can't make rent. I.e, people with long history of being able to pay rent, but suddenly can't make rent b/c extraordinary events)
davvolun 7y ago
"We've noticed that Joe Everybody didn't make any rent payments prior to their birth or after their death. [HIGH RISK]"

by mabbo 7y ago

T-hawk 7y ago

There's value in the converse of that data point, though, right? If someone made rent on April 1st (and maybe even more importantly May 1st), that might be an even stronger signal that they'll continue to do so without interruption.

thaumasiotes 7y ago
Depends on how common each is. It's a signal that puts people in the top or bottom X% of renters. If knowing someone is in the bottom 90% of renters isn't that useful, then knowing someone else is in the top 10% is, yes. If the threshold is closer to the median, then both sides are closer in usefulness to each other. I'd be pretty surprised if making rent in April was really at the 90th percentile, though.
phkahler 7y ago
The big differentiator is going to white collar jobs. There will be others, but it doesnt take an AI to figure out who is at risk.
- tobylane 7y ago
  The UK government announced and started support for pay (income tax) as you earn employees a while before support for the self employed/contractors, so maybe the AI prefers standard salaried employment above all else.
  - NullPrefix 7y ago
    > maybe the AI prefers standard salaried employment above all else. Is it wrong for AI to have the same biases as the general population?

chickenpotpie 7y ago

> Landlord service Naborly creates 'blacklist' of tenants who are nonessential and can't work from home I agree this seems like bad ML. Why assign so much weight to a once a century event?

beckingz 7y ago
Check back in next month?

clairity 7y ago

the whole concept of predicting human behavior on very sparse and backward-looking data is problematic, not just in this one instance. even in cases where we have a ginormous amount of data (equity markets, self-driving cars) and a recognizable set of rules/heuristics does it fail to predict human behavior well enough to depend on predictive models. we're infinitely complex relative to these models. they just don't seem to have enough degrees of freedom to pin us down (yet; who knows in a thousand years). in the case of landlords, it's tantalizing to pay a few bucks and get some comfort that you've done your due diligence, rather than facing the uncomfortable reality and esteem hit that there is no certainty predicting future behavior. and renters pay for that ignorance and moral hazard.

ballenf 7y ago
Landlords don't need to "predict human behavior" they only need to reduce their risk a little more than their competitors to have a slight edge in the market.

nomel 7y ago

Assuming the blacklist is changed into a new variable in the risk assessment equation, a missed payment for April 1st could probably answer the question "did this person have enough saved to cover one rent check?". This assumes they didn't intentional skip rent with forgiveness in mind, to save for upcoming months without work. I can't imagine missed payments after April will be useful.

chickenpotpie 7y ago
The lowest estimate I can find for percentage of Americans that live paycheck to paycheck is 49% and the highest is 80%. This just feels like a list of people who didn't get paid in March.

onetimemanytime 7y ago

Ummm...you will get a "don't rent to John" report based on Covid non-payment, not a detailed thing

deleted 7y ago

[deleted]

TrackerFF 7y ago

Yes, it's bad data. They're going to use black-swan events for their training data - which is complete nonsense. Their training sets will be full of false-negatives (good renters that can't make rent. I.e, people with long history of being able to pay rent, but suddenly can't make rent b/c extraordinary events)

davvolun 7y ago

"We've noticed that Joe Everybody didn't make any rent payments prior to their birth or after their death. [HIGH RISK]"