There is a blind spot in AI research

http://www.nature.com/news/there-is-a-blind-spot-in-ai-research-1.20805

by _lm_ • 10 years ago

98 51 10 years ago

ggchappell• 10 years ago

Key quote:

“People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.”

-- Pedro Domingos, in The Master Algorithm (2015)

Mz6• 10 years ago

I think this is rooted in the fact that humans don't really do intelligence all that well themselves. Most of us raise kids in a manner that assumes chuldren aren't independent thinking beings and we have a lot of social "rules" that fail to take into account actual independent thought and then humans bring these big blind spots to AI work.

Until we overcome such issues in humans, they probably are not solvable in AI.

ChoHag5• 10 years ago

If you're going to go down that path then your entire argument is moot because the definition of "intelligence" is so unclear.

posterboy3• 10 years ago

children aren't independent from their parents pretty much by definition. They do have individual thoughts, but if their thoughts are concerned with their dependence, are those thoughts really independent?

ktRolster2• 10 years ago

It's an entertaining quote, I laughed, but I think everyone who works in AI already knows this. It's not a blind spot.

blazespin• 10 years ago

Right, try saying that the next time we have a flash crash that really kills the markets.

There should be an addition to the statement though, which is "Unfortunately, Humans en masse are even stupider."

hiddencost• 10 years ago

Whether the people that pay us know this, though? Less clear.

ChoHag5• 10 years ago

That it's not a blind spot among "everyone who works in AI" does not make it any less a blind spot.

pmyjavec4• 10 years ago

Calling people stupid isn't cool, it's unproductive overall and there is not place for it no matter how educated someone is this.

Society is ill right now and maybe people are hoping artificial intelligence will take them to a better place?

tintor• 10 years ago

He was talking about computers, not people.

ccvannorman• 10 years ago

This is another angle of the "Weapons of Math Destruction" argument, and it looks very relevant. Those who work on big data (esp. public sector) would be wise to consider the implications.

frozenport2• 10 years ago

The problem is the AI community is treating itself like non-experts. Explaining that AI needs to be controlled by telling horror stories of robot domination is good to motivate research work to lay people, but is a distraction for professionals.

ChoHag5• 10 years ago

So the "robots are going to kill us" meme is good because it makes "the rest of us" interested in the idea of AI?

frozenport2• 10 years ago

Kinda, but if you treat your own people (the AI community), like "the rest of us" - well then you disrupt real scientific work.

quickben2• 10 years ago

That's fiction.

visarga• 10 years ago

Systematic analysis of AI biases is certainly needed. We train models on data, but how is the data collected, and how biased is it? At least in AI we can compensate for biases, but in human society they are much harder to counter. There's hope for a better future if we can make fair AI.

mcguire• 10 years ago

AI biases come in new and unique varieties.

"As another example, a 2015 study9 showed that a machine-learning technique used to predict which hospital patients would develop pneumonia complications worked well in most situations. But it made one serious error: it instructed doctors to send patients with asthma home even though such people are in a high-risk category. Because the hospital automatically sent patients with asthma to intensive care, these people were rarely on the ‘required further care’ records on which the system was trained."

Itsdijital• 10 years ago

Look at Tesla with it's "autopilot" feature. It's not really a true autopilot, more just a driving assist, but people treat it like such. I think it's easy for people to fall into the trap of relying really hard on something that is shiny, new, and works well despite being imperfect - even if it is explicitly stated to be.

Nano tech has a similar problem at hand. There are indications that nanoparticles could have serious health related issues. Despite this researches are pushing ahead full steam with bringing nanotech to market. The money going to development far exceeds whats going to test safety. In an AMA with a nano materials researcher I asked if he ever has concerns about the safety of what he is making. His response was along the lines of "Sure I do, but it's not my job to deal with that. I just get paid to develop the tech."

Tech development has always had a shoot first ask questions later approach.

quickben2• 10 years ago

No, it was marketed as an autopilot in the first place.

FullMtlAlcoholc• 10 years ago

It's not really a true autopilot, more just a driving assist.

Then naming it autopilot is deceotive marketing at best. I love Elon as much as anyone else, but i find this marketing practice to be downright dangerous.

matco11• 10 years ago

Key thought: AI's social and cultural impact, in other words AI's implications on "social mobility" (your rags to riches stories, the American dream).

The authors are asking: in a hypothetical world where many decisions are AI assisted, what is the risk that AI systems slow social change because they are too dumb to understand exceptions, peculiarities, positive externalities? What can we do to establish parameters that will allow us to know when a certain AI system is trained well enough to be used in real world, with minimal risk of undesired social and cultural implications?

SFJulie• 10 years ago

With or without AI we already have issues with too much automation/assistance, and it get bad when automation they are failing/lack of maintaining.

Basically if you can drive a manual car, it is easy to drive an automatic one, but the opposite is not true.

Old GPS and even new one got 15% of the time the address wrong when I was a mover. Not only GPS failed, but what do you do when you have no usable maps?

Well, we have fired the people doing the maps, they are hardly updated at the pace mayors and real estates promoters are changing the territory, if you have an awesome GPS with no updated maps your GPS is useless, no?

We are forgetting to do the heavy underlying costly maintaining of maps, directions, forming drivers to read signs figuring GPS made them obsolete. Now we have to maintain: maps, satellite, computers and to live with people unable to use a map and a compass that are distracted when they drive by potentially wrong information and to dumb to read the sign saying there are entering a one way street in counter sense relying on their GPS.

Then too, the automation in Airbus/tesla and Boeing have proven to be less valuable then pilots' experience when computers fail due to false négative (frozen Pitot probes) or false positive (sun blinding cameras). I think civil and military records about accidents are a nice source of information about "right level of automation".

The problem is keeping up to date workers requires constant, heavy practice without too much automation. And human time nowadays is expensive.

That is one of the reason France (at the opposite of Japan) kept automation in nuclear plant rudimentary. Because when a system is critical, you really prefer human that can handle stuff at 99.999% than a computer that do great 100% of the time if and only if its sensors do works or nothing too catastrophic happens (flood, tsunamin, earthquake)

The problem is industry wants to spare on costly formations and educations (not the one from the university, I mean the one that is useful) but knowledge you have not yet crafted because of change of circumstances (I will be delighted to see how self driving car are behaving in massive congestion with dead locks) will be hard to program if we lose the common sense of doing the stuff by ourselves. How do you correct a machine misfunctioning to do something you have forgotten to do correctly yourself? You may even ignore when it will fail. Not because of it, but because of your lack of referential.

hyperpallium• 10 years ago

I wish HN discouraged clickbait titles, even when the article itself uses that title. One solution is to append the answer to the original title, separated by a "|", as used by: https://www.reddit.com/r/savedyouaclick/

For example:

There is a blind spot in AI research | Autonomous systems are already ubiquitous, but there are no agreed methods to assess their effects

If it's interesting, I'll still click.

ars• 10 years ago

I wish HN discouraged clickbait titles, even when the article itself uses that title

It actually does discourage that, I remember seeing a post from dang saying so.

goodplay2• 10 years ago

I second your proposal.

While I never post a comment on an article before reading it, I almost always read the comments before reading the article to avoid click baits. An brief one-line summary that serves the same role as an abstract would eliminate the need to read the comments first.

It might even help eliminate clickbaity titles in technical articles altogether.

basch• 10 years ago

i like this too

buzzfeed/upworthy had such an impact on the world of journalism, that after an eon of only ever using the original headline, techmeme was forced to start rewriting headlines

here was their post outlining their decision http://news.techmeme.com/130906/headlines

kevindeasis• 10 years ago

This would save lots people time

Animats2• 10 years ago

Scary robot video of the month.[1] This is not just a blind, repetitive operation; previous X-rays and laser scans tell it what to do.

[1] https://youtu.be/MZIv6WtSF9I?t=245

goodplay2• 10 years ago

As morbid as it may be, I wonder if that system can tell the difference between a lamb and a human of comparable size. The system might still able to identify (or misidentify) all targeted joints.

cs2818• 10 years ago

I'm not too sure how practical the suggested "social-systems analysis" approach is. It is summarized as:

"A practical and broadly applicable social-systems analysis thinks through all the possible effects of AI systems on all parties."

which seems incredibly difficult to do completely. Hopefully the authors will further describe their approach in future publications.

Also, somewhat of a nitpick, but the article states:

"The company has also proposed introducing a ‘red button’ into its AI systems that researchers could press should the system seem to be getting out of control."

in reference to Google, but cites a paper which discusses mitigating the effects of interrupting reinforcement learning [0]. The paper makes a passing reference to a "big red button" as this is a common method for interrupting physically situated agents, but that is certainly not the contribution or focus of the work.

[0] https://intelligence.org/files/Interruptibility.pdf

Animats2• 10 years ago

For a good analysis of the problems of living with AIs, read the web comic Freefall.[1] This long-running comic has addressed most of the moral issues over the last two decades. Of course, that's about 3000 comics to go through.

[1] http://freefall.purrsia.com/

Houshalter2• 10 years ago

This is vastly overblown. People already vastlh distrust algorithms. Psychologists have studied it and called it "algorithmic bias". That when given a choice between computer and human, even when the computer makes much better predictions, people distrust it.

In almost every domain where there is data and a simple prediction task, even really crude statistical methods outperform "experts". This has been known for decades. Yet in almost every domain algorithms are resisted. Because people distrust them so much, or fear losing their jobs, or all of the above.

But humans are vastly more biased. Unattractive people get twice as long sentences. People heavily discriminate based on political denomination. Not to mention race or gender. Judges give way harsher sentences when they are hungry. Interviews negatively correlate with job performance.

Humans are The Worst. Anywhere they can be replaced with an algorithm, they should be.

The referenced propublica result has been criticized here: https://www.chrisstucchio.com/blog/2016/propublica_is_lying.... "almost statistically significant"

gallerdude• 10 years ago

Agree, we need more algorithms replacing people.

pmyjavec4• 10 years ago

Release the algorithms!

In fairness though, it sounds like the point you and others are often making is this. Humans are now considered dumb, bias and unreliable. So we need to invest in some kind of external policing system (AI) to run our world for us and make sure we're doing it right. Basically establish reliance on something external to ourselves?

This is sad because it sounds like we're losing faith in ourselves to evolve for the better and hope the machines can do a better job at self-improvement ?

I'm generally curious about your point of view, sometimes I'm confused with the enthusiasm people have about this aspect of AI? Is it a form of distrust and dislike of society that makes us want to put faith in robots? A kind of adult angst?

I worry because we could be barking up the wrong tree if this is the case.

Houshalter2• 10 years ago

Humans are just not good at doing certain kinds of tasks. We can add numbers, but nowhere near as fast as a computer can. Similarly we can see patterns in data, but not to the exact precision of a statistical model that has it's parameters optimally tuned with gradient descent and bayesian inference. Humans will never be as good as statistical algorithms at certain tasks and that's ok.

I see fear about algorithms everywhere. Previous articles insist that algorithms could be unfair or racist. This article suggests things along those lines as well. The EU recently banned perhaps the majority of applications of machine learning, in any place where they might be used to rank individuals. This fear is hugely setting back society and technological progress. And almost every one of these places will have to revert back to human judgement. Which by every measure is far worse and far less fair.

lqdc132• 10 years ago

Why do humans distrust "algorithms"? Maybe they had past experiences where algorithms behaved worse than humans?

A recent example from recently: facebook replaced human-curated news with machine-curated, they started trending fake news [2].

Another example is algorithms that try to help you during automated phone calls, hence people always try to get to a human. This is because the speech-to-concept parsing/mapping is flawed or because they're not programmed to perform some specific tasks.

Another example is self-driving cars. Google cars have been involved in more accidents per mile than average humans[1].

In general, people's intuition is built through repeated encounters, that's why it is so great.

[1] https://www.bloomberg.com/news/articles/2015-12-18/humans-ar... [2] http://www.theverge.com/2016/8/30/12702478/facebook-trending...

titzer• 10 years ago

From [1],

Driverless vehicles have never been at fault, the study found: They’re usually hit from behind in slow-speed crashes by inattentive or aggressive humans unaccustomed to machine motorists that always follow the rules and proceed with caution.

Which completely negates the point you are trying to make.

There is a blind spot in AI research

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