
A.I. Is Learning from Many Humans - jonbaer
https://www.nytimes.com/2019/08/16/technology/ai-humans.html
======
_fullpint
Not exactly on topic but after skimming the article and then the comments,
there seems to be — albeit a very understandable — misunderstanding of what is
being done in the field and how the public views and uses terminology.

People hear or read the words Machine Learning and assign a HAL like
technology to it.

It’s definitely hard to explain an idea like SVM, it’s applications, and how
it works/what it does without a background in some linear algebra.

And then to broach more complicated topics like temporal real time neural
networks in computer vision for something like anomaly detection.

From my conversations with people because it’s something that isn’t understood
there is almost a cognitive dissonance. One of which expects so much now, but
at the same time denies the future application space when the conversation
becomes more personal. “Why aren’t self driving cars a thing yet...” and then
“A machine couldn’t do what I do.”

It’s worrying that there will definitely be regulation coming to the field,
where the people writing the laws and the people the writers represent have a
hard time understanding what they are trying to regulate. Add in the fact that
the tech itself is somewhat cheap and will only get less expensive. You only
have to look as far as the Deep Fakes fiasco on Reddit. The guy creating fakes
of celebrities being superimposed on porn is a self proclaimed amateur and was
able to accomplish a quite a bit at home with Keras.

Edit:

I do want to mention that a lot of the papers I’ve read recently on real time
anomaly detection rely on automated labeling and not having human labelers.

It’s only important to have human readable labels if a human has to interpret
directly.

~~~
jinfiesto
> It’s definitely hard to explain an idea like SVM, it’s applications, and how
> it works/what it does without a background in some linear algebra.

I don't actually think this is the case. The basic idea is that you can
represent data as points in n-dimensional space and draw decision boundaries
in that space. I think most people should at least be able to understand this
geometrically for n=2/3 and then accept that it possibly extrapolates to n >
3.

~~~
bashinator
What is a "decision boundary?" What does it mean to represent data as a point
in space? Why would the number of dimensions of space matter? How does any of
that relate to AI or machine learning?

~~~
jammygit
Those details matter a lot, you're right. However, pictures help a lot imho,
and I bet my parents could get the jist of this:

[https://qph.fs.quoracdn.net/main-
qimg-968b9df8608f76d41586a0...](https://qph.fs.quoracdn.net/main-
qimg-968b9df8608f76d41586a0c257381821)

~~~
bashinator
Is that teaching a computer to distinguish between males and females based on
height and weight?

~~~
jinfiesto
More or less, yes.

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sailfast
Each time I read an article about this I am convinced that any person
contributing to this kind of learning algorithm should have the opportunity
for equity in the outcome. (perhaps in addition to the wage for doing the
task)

If I'm a delivery driver roaming all about town with my camera on my dashboard
which is tagging street signs and speed limits and other data, do I get a
residual if that data is used to make billions of dollars? Do I even get paid
.02/mile to collect it, or am I forced in order to have the gig in the first
place?

A morally straightforward way to make a more equitable future would be to
acknowledge how important it was to collect and classify all of this data, and
provide the humans that are doing that work with some part of the insane
returns of scale that will (and already have been) achieved by these
organizations. Sure, you contributed a really really small amount to the
overall algorithm, but that really small amount generates billions / trillions
of profit, so maybe it scales, and it will scale over time after training is
done.

I hope we see efforts to do this kind of thing.

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melling
Yes, we need lots of correctly tagged data.

Waymo released a tagged data set for self-driving:

[https://techcrunch.com/2019/08/21/waymo-releases-a-self-
driv...](https://techcrunch.com/2019/08/21/waymo-releases-a-self-driving-open-
data-set-for-free-use-by-the-research-community/)

The FT article is a little better:

[https://www.ft.com/content/2eed925a-c3cf-11e9-a8e9-296ca6651...](https://www.ft.com/content/2eed925a-c3cf-11e9-a8e9-296ca66511c9)

"Its data, collected using cameras and sensors on Waymo vehicles in a variety
of environments and road conditions, include 1,000 high-resolution driving
scenes that have been “painstakingly labelled” to indicate the presence of 12m
objects such as pedestrians, cyclists and signage."

~~~
mlb_hn
Interesting that FT adds that first bit to copy/paste.

~~~
melling
Ugh. Forgot to remove that. Didn’t see it on my iPhone.

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asdfman123
I think the lack of engineers in the US government is becoming a bigger
liability every year. Here science is changing the globe at an ever increasing
pace and our congresspeople are baffled and confused by the word "encryption."

~~~
hugey010
I completely agree. One cannot pass fair laws on topics one doesn't
understand. It's even worse if understanding is based on input from a
consultant or lobbyist!

There aren't many reasons an engineer would want to jump into the political
fray besides altruism. It's like choosing to join the largest, most corrupt,
bureaucratic, change-averse, and valueless company that ever existed. For
lawyers, that probably sounds like a dream come true.

My perspective as an engineer: Yes, there are huge important problems I would
like to help solve. No, I don't think I'm willing or capable of solving that
class of problems in a system like that.

~~~
sharadov
Incentivize engineers/technologists to join the government, that's what China
has been pushing for the past 3 decades. Partner with the FAANG companies,
have them sponsor their employees to go on a paid sabbatical wherein they can
contribute to technology solutions within government. I know some form of this
was happening under Obama.

~~~
opportune
I would totally be willing to do this, however I fear the actual
implementation would be more of the same:

\- Terrible consultants, middlemen, and lifers making progress too hard or
impossible.

\- Constantly changing or unclear requirements

\- Making penny-wise, pound-foolish decisions for political reasons or
budgeting idiosyncracies

\- Resistance from lawmakers since it would give more government influence to
people from states that lean towards some of other party (put more bluntly,
Republicans don't want to give a bunch of liberal or left-leaning people from
California, Washington, and New York more influence)

\- The government only seeing the value in surveillance/military software that
people are likely to refuse to work on. Not sponsoring software that actually
directly helps people domestically

What I think we need instead is something like the US Digital Service, along
with some other government programs, rolled into a Department of Technology
that will hopefully have a completely different culture, payscale, etc.
compared to the rest of the government. And maybe even something like jury
duty, but for software people, engineers, scientists, etc. so it's more
representative of the general public and not the old-school government
culture.

~~~
jointpdf
> _Terrible consultants, middlemen, and lifers making progress too hard or
> impossible._

Can you elaborate on this? I hear lots of criticism around inept and ill-
intentioned consultants and “govvies” alike, but I think a lot of it is a bit
unfairly harsh. There are certainly some adverse incentives (chiefly that it’s
easy enough to coast along with minimal effort in these jobs if you’re
inclined), but I’d say the slight majority of individuals in this space are
qualified, capable, and motivated to improve the world via good work—technical
or otherwise. Slowly but surely, projects get done and positive change is
made.

> _Not sponsoring software that actually directly helps people domestically_

This really isn’t true. Every US agency has technology initiatives, some more
effective than others. See the work that the Department of Veterans Affairs
does, as one example. The US government also spends ~$750B on grants annually,
much of which goes to fundamental research as well as tech projects. If you
really want to dig in, there’s an API to access data on every item of spending
(e.g. contract awards, grants):
[https://www.usaspending.gov/#/](https://www.usaspending.gov/#/)

~~~
opportune
>Terrible consultants, middlemen, and lifers making progress too hard or
impossible.

I can mostly only echo hearsay, however I have been tangentially involved in
government-focused projects. The big issue I see with the government getting
involved in tech is that they don't know what they really want, they don't
know how to filter out bullshit/upsells, and they'll frequently overpay for
things they don't need and underpay for things that would be very helpful.

I'm not one of those people who wants to defund the government or privatize
everything, however I do think the government incentive structure needs to be
redesigned and become less cushy while simultaneously becoming more lucrative,
accompanied by a huge culture change. The government isn't inherently
inefficient, it's only like that because we let it be, one has only to look at
other countries (see: Estonia, China) to see how much more effective we could
be here.

Regarding actual spending, I want to measure that by its effectiveness, not by
the total amount spent. The government could blow all its money on tech
initiatives and EMR upgrades and have nothing to show for it, and I wouldn't
call that helping people domestically. To address your examples, a lot of
those grants are for defense contractors (which only indirectly helps people,
at best, and is itself a pretty corrupt old-boys industry). Others are for
things like direct academic research though, which I do think is decently well
run in general, but isn't really a direct government relationship to tech.

~~~
jointpdf
> _The big issue I see with the government getting involved in tech is that
> they don 't know what they really want, they don't know how to filter out
> bullshit/upsells, and they'll frequently overpay for things they don't need
> and underpay for things that would be very helpful._

These are good points (as were your original ones). Thanks for the thoughtful
reply—I’m just trying to push back slightly on the “government/contractors are
all incompetent” narrative where I see it, since I don’t think that’s the root
of the problem (the DMV area is the most highly education region of the US, as
one counterpoint). Discussion around incentive structures is a lot more
productive.

I didn’t give very specific examples with grants, but I just wanted to draw
attention to that as an often overlooked and major source of government
spending. The federal grants process does have multiple stages of project
performance monitoring/evaluation, though that process itself could be made
more efficient. Also, sometimes grants do directly support software projects
with public benefits. Just as a single example, Stanford DeepDive (now
Snorkel) is a system for knowledge base construction that has been used to
fight human trafficking, among other things:
[http://deepdive.stanford.edu/showcase/apps](http://deepdive.stanford.edu/showcase/apps)

------
bookofjoe
[https://news.ycombinator.com/item?id=20733878](https://news.ycombinator.com/item?id=20733878)

------
not_a_cop75
Learning or Remembering? or Classifying? lol

------
codesushi42
The AI isn't "learning" anything. It's being supplied with more observations
so that it can better approximate whatever "curve" that is being fit to the
data.

~~~
dekhn
do you think humans do something differently?

~~~
beatgammit
I do. I think humans are pretty bad at fitting data to curves consistently,
but we're pretty good at learning to fit data to curves. AI doesn't work until
you tell it which data to use and what output you expect, and then it
functions quite consistently. Humans are also capable of trying new things and
hypothesizing results.

The gap is certainly closing, but it's nowhere near where it needs to be to
replace the need for humans. Maybe we'll get there soon, but it won't happen
without some new approaches IMO.

Then again, I'm no longer active in the research aspect of the field, so it's
hard to gauge how close we might be.

~~~
dekhn
"AI doesn't work until you tell it which data to use and what output you
expect, and then it functions quite consistently." -> you mean supervised ML,
not AI.

Unsupervised ML is different. From what I can tell (I work in ML and have
extensive biology experience), human brains use a combination of approaches
that combine unsupervised and supervised learning and oneshot learning and
it's not clear that a true "learning AI" requires more technology than what we
have today. I think that's an open question in the field but nobody is really
addressing it head-on.

------
ChuckMcM
I always wondered how an AI would enslave humans to teach it more things :-)

~~~
Jun8
Tangential: this could have been a better premise for _The Matrix_ , rather
than the battery thing. It would make a great story, if it hasn’t been written
already.

In a sense babies do this, i.e. they are cute and smile to engage parents and
other adults so they engage with them, which increases rate of learning.

~~~
Jack000
about the battery thing: [https://scifi.stackexchange.com/questions/19817/was-
executiv...](https://scifi.stackexchange.com/questions/19817/was-executive-
meddling-the-cause-of-humans-as-batteries-in-the-matrix)

the original idea makes much more sense in the context of the story, it's
basically my head-canon now.

~~~
Jun8
Oh boy, Matrix theories do run deep. My favorite is the Matrix in a Matrix
theory
([https://matrix.fandom.com/wiki/Matrix_in_a_Matrix_theory](https://matrix.fandom.com/wiki/Matrix_in_a_Matrix_theory)),
I really wish they would pursue this in Matrix 4 (just announced). It's
matrices all the way up!

------
mindgam3
Also,
[https://news.ycombinator.com/item?id=20717961](https://news.ycombinator.com/item?id=20717961)

~~~
sp332
No conversation there though.

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gorzynsk
I hope A.I. is smart enough to learn only from smart people. The are not so
many of them though...

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CzarnyZiutek
...A PRIORI ==> MULTIVERSE ==> UNIVERSE ==> HUMAN ==> AI ==> A POSTERIORI...

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seibelj
AI's key innovation has been the proper marketing of outsourced low-wage labor
to investors. Still waiting on those self-driving cars, though... weren't they
supposed to be taking me to the airport last year?

~~~
what-the-grump
Stop offending the to be blockchain millionaires.

