A lot of the people that pay for "Watson" probably think they're paying for something really similar to the Watson that beat Ken Jennings at Jeopardy! and cracked jokes on TV. They're paying for something that might use some of the same algorithms and software, but they're not actually getting something that seems as sentient and "clever" as what was on TV.
To me, the whole "Watson" division does seem like false advertising.
https://www.space.com/35042-ibm-watson-computer-nasa-researc...
Given how often another person can't correctly infer meaning when people talk, I doubt it will ever be how people imagine it.
Initially, I imagine it will be a lot of people trying to talk normally and a lot of AI responses asking how your poorly worded worded request should be carried out, choice A, or choice B. You'll be annoyed because why can't the system just do the thing that's right 90% of the time? The problem is that 10% of the time you're just not explaining yourself well at all and 10% is really quite a lot of the time, and probably ranges from a few requests to dozens of requests a day, and while being asked what you meant is annoying, having the wrong thing done can be catastrophic.
As humans, we get around this to some degree by modeling the person we are conversing with as thinking "what would they want to do right now", which is another class of problem for AIs I assume, so I think we may not get human level interaction until AI's can fairly closely model humans themselves.
I imagine we'll probably develop some AI pidgin language that provides more formality that as long as we follow it AI voice interactions become less annoying (but you have to spend a bit of time before to formulate it).
Then again, maybe I'm way off base. You sound like you would know much better than me. :)
A lot of folks are too young to know this, but there was a time when it was accepted wisdom that much of personal computing would eventually converge to a pen-based interface, with the primary enabling technology being handwriting recognition.
What I found is that computer handwriting recognition can never ever be good enough to satisfy people's expectations. Why? Because no one is good enough to satisfy most people's expectations for handwriting recognition, including other humans, and often even including themselves!
Frustration with reading handwriting is a given in human interaction. It will be a given in computer interaction too--only, people don't feel like they need to be polite to a computer. So they freely get mad about it.
The companies that had succeeded with pen computing were those that had figured out a way to work around interpreting natural handwriting.
One category was companies who are specialized in pen computing as an art interface--Wacom being the primary example at the time. No attempt at handwriting recognition at all.
The other was companies who had tricked people into learning a new kind of handwriting. The primary example is the Palm Pilot's "Graffiti" system of characters. The neat thing about Graffiti is it reversed customer expectations. Because it was a new way of writing, when recognition failed, customers often blamed themselves for not doing it right!
We all know what happened instead of pens: touchscreen keyboards. The pen interface continues to be a niche UI, focused more on art than text.
It's interesting to see the parallels with spoken word interfaces. I don't know what the answer is. I doubt many people would have predicted in 2001 that the answer to pen computing was a touchscreen keyboard without tactile keys. Heck people laughed about it in 2007 when the iPhone came out.
But I won't be surprised if the eventual product that "solves" talking to a computer, wins because it hacks its way around customer expectations in a novel way--rather than delivering a "perfect" voice interface.
Well, here's a possibility: we'll meet in the middle. Companies will train humans into learning a new kind of speech which is more easily machine-recognisable. These dialects will be very similar to English but more constrained in syntax and vocabulary; they will verge on being spoken programming languages. They'll bear a resemblence to, and be constructed in similar ways to, jargon and phrasing used in aviation, optimised for clarity and unambiguity over low-quality connections. Throw in optional macros and optimisations which increase expressive power but make it sound like gibberish to the uninitiated. And then kids who grow up with these dialects will be able to voice-activate their devices with an unreal degree of fluency, almost like musical instruments.
The challenge with learning anything new from our voicebots is the same as it already is: discoverability. I don't have the patience to listen to Siri's canned response when it's done what I've asked it to, and I'm probably not going to listen to it tell me "Next time, you can say xyz and I'll work better."
The easiest way to learn a new language is to be a kid and listen to native speakers converse. Unless Amazon produces a kids' show starring a family of Echos speaking their machine code, I don't see that happening.
The commands and syntax he uses to interact with the system might be a decent approximation of the custom English syntax you suggest.
We do this in a hundred ways in English, emphasis, meta-words, too many to fold into a system. But with a little user prodding, I think you could cover enough of this ground to still sound almost natural.
Asst.: Would you like me to read that back to you?
User: Yes
A: The click brown ox...
U: The _quick_ brown _fox_...
A: Ok. The the quick brown fox jumped over the lazy log.
Is that correct?
U: No.
A: Which part [is incorrect]?
U: The the quick
A: The the quick. What should it be?
U: The quick.
A: The quick brown fox jumped over the lazy log. Is that
correct?
U: No. Lazy dog.
A: Lazy log?
U: No. Lazy dog.
A: Spell "log." <Or "Spell" + recording of user's voice saying ambiguous word>
U: D-O-G.
A: Ah. The quick brown fox jumped over the lazy dog. Do
I have it now?
U: Yes.
A: Say 'send' to send message.
If people enjoyed this kind of interaction with their computer, it would become common place and they'd likely become so much better at interaction.
From what we know, those techiques play an important roles in how humans themselves go from baby glibberish to actual language fluency - and from what I understand there is already a lot of research ongoing how reinforcement learning algorithms can be used to learn walking cycles and similar things.
So I'd say, if you find a way to read the non-/semiverbal cues humans use to communicate understanding or misunderstanding among themselves and use those as penalties/rewards for computers, you might be on a way to learn some kind of languages that humans and computers can communicate with.
The same goes into the other direction. There is a sector of software where human users not only frequently master highly intricate interfaces, they even do it out of their own motivation and pride themselves on archieving fluency: Computer games. The secret here is a blazing fast feedback loop - which gives back penalty and reward cues in a similar way to reinforcement learning - and a carefully tuned learning curve which starts with simple, easy to learn concepts and gradually becomes more complex.
I would argue, if you combine those two techniques - using penalties and rewards to train the computers and communicate back to the user how well the computer understood you, you might be able to move to a middle-ground representation without it seeming like much effort on the human side.
Speech is way, way harder.
Finger-on-nose! It seems to be a question of utility and efficiency rather than primarily an emotional response to effectiveness of a given UI.
I type emails because it's faster. I handwrite class notes because I often use freeform groupings and diagrams that would make using a word processor painful.
Most owners eventually used them like laptops unless illustrating, or operating in a sort of "personal presentation mode," where folding the screen flat was convenient. For most people, handwriting recognition was a cool trick that didn't get used much (as I suspect it was for you, eventually).
The utility of a handwriting recognition system is ultimately constrained by the method of correcting mistakes. Even a 99% accuracy means that on average you'll be correcting about one word per paragraph, which is enough to feel like a common task. If the only method of correction is via the pen, then the options are basically to select from a set of guesses the system gives you (if it does that), or rewrite the word until it gets recognized.
But if a product has a keyboard, then you can just use the keyboard for corrections. But if you're going to use the keyboard for corrections, why not just use it for writing in the first place...
In alphabetic languages. What about Chinese, or Japanese?
For Japanese there are keyboard-based romaji and kana based input methods.
The correct Hanzi/Kanji is either inferred from context or, as a back-up, selected by the user.
You are right that the ten-key method is more common on cell phones (and older feature phones had kana assigned to number keys), although romaji input is also available.
It seems within the bounds of possibility to me (from having no experience in the field ;), if patterns could be predictably matched in real-time or better time than it takes to whack the keyboard or move the mouse (can EEG or FMRI make predictable sort of patterns like that?).
I doubt we're going to make much progress there anytime soon.
In my experience that 'solution' isn't a solution but rather a poorly guessed attempt at one single part of it. Whenever I've thought I have the architecture of a class all figured out there is one corner case that destroys all the lovely logic and you either start from scratch on yet another brittle monolith, or accept that you are essentially writing spaghetti code. At that point documentation that explains what does what and why is the only way to 'solve' the issue of coding.
This is based on my experience with the Muse [1] headset, which has 4 electrodes plus a reference electrode. I know there are similar devices with around a dozen or so electrodes, but I can't imagine they're a significant improvement.
So I think we're still a long way off from what you're describing :(
But also, when my college had a demo microsoft tablet in their store in 2003, I could sign my name as I usually do (typical poor male handwriting) and it recognized every letter. That seems pretty good to me.
I also had a Palm Pilot then and Grafitti sucked, but that's just one implementation.
No, we are not talking about the 1940s, why would anyone be talking about the 1940s? How does that make any sense at all?
We aren't talking about a Microsoft demo that worked well for you once, either. We are talking about the fact that, since the 2000s when it was tried repeatedly, people do not like to hand-write on computers. It is a strange thing not to be aware of when you're speaking so emphatically on the topic.
Since he didn't specify the timeframe, I gave him the benefit of the doubt and thought it he was talking about before my time.
Apart from the problems mentioned in the comment you replied to. You don't seem to have a point other than being contrarian (as a state).
What was interesting is that it was clear that search engines have trained a lot of people to speak 'search engine' rather than stick with English. Instead of "When is Pizza hut open?" you would see a query "Pizza Hut hours". That works for a search engine because you have presented it with a series of non stopword terms in priority order.
It reminded me of the constraint based naming papers that came out of MIT in the late 80's / early 90's. It also suggested to me ways to take dictated speech and reformat it into a search engine query. There is probably a couple of good academic papers in that data somewhere.
That experience suggests to me that what you are proposing (a pidgin type language for AI) is a very likely possibility.
One of the bits that Jimmy Fallon does on the Tonight Show is an interviewer who asks people a question but uses nonsense words that sound "right" in the question. The most recent example was changing the question
"Do you think you will see Avengers: Infinity War"
With things like "Do you think you will see Avengers something I swear." Similar sounds and people have already jumped to the question with enough context that they always answer as if he had said "Infinity War." How will conversational systems deal with that, I have no idea.
Yeah, that's exactly what I'm talking about. I suspect this works because the interviewees have a model of what they think Jimmy Fallon is going to ask, and when hearing a question, if they can't make out words or they sound wrong, the simplest thing is to assume you heard them wrong and think what it's likely he would have asked. To that, the answer is fairly obvious.
We've all experienced those moments when we're caught off guard when this fails. For example, you're at work and someone you're working with says something that sounds like it was wildly inappropriate, or out of character, or just doesn't follow the conversation at all, and you stop and say "excuse me? What was that?" because you think it's more likely you heard them wrong than to believe you fuzzy matched their statement "Hairy Ass?" and you were correct.
One thing that is very frustrating now is if there are two or three things out there related to a query, and Google prefers one of them, it's more difficult than ever to make small tweaks to the query to get the one you want. Of course, sometimes I don't know exactly what I want, but I do know I don't want the topic that Google is finding. The more "intelligent" it becomes, the harder it is to find things that diverge from its prejudices.
The Atlantic: Alexa Is a Revelation for the Blind. https://www.theatlantic.com/magazine/archive/2018/05/what-al...
Then I stop myself. Isn’t it possible that he expects Alexa to recognize a prompt that’s close enough? A person certainly would. Perhaps Dad isn’t being obstreperous. Maybe he doesn’t know how to interact with a machine pretending to be human—especially after he missed the evolution of personal computing because of his disability.
...
Another problem: While voice-activated devices do understand natural language pretty well, the way most of us speak has been shaped by the syntax of digital searches. Dad’s speech hasn’t. He talks in an old-fashioned manner—one now dotted with the staccato march of time. “Alexa, tell us the origin and, uh, well, the significance, I suppose, of Christmas,” for example.
There was a similar thing going around the Japanese Web a few years ago, where you'd try to sneak in soundalikes into conversation without anybody noticing, but the example I remember vividly was replacing "irasshaimase!" ("welcome!") with "ikakusaimase!" ("it stinks of squid!").
At least, assuming they have the proper context. Humans mostly fill in the blanks based on what they /expect/ to hear.
Maybe someday we'll get to a point where a device we classify as a 'computer' hosts something we would classify as an 'intelligent life form'; irrespective of origin. Something that isn't an analog organic processor inside of a 'bag of mostly salty water'. At that point persistent awareness and context(s) might provide that life form with a human-like meaning to exchanges with humans.
People usually judge AI systems based on superhuman performance criteria with almost no human baseline.
For example, both Google Translate and Facebook's translation system could reasonably be considered superhuman in performance because the singular systems can translate into dozens of languages immediately more accurately and better than any single human could. Unfortunately people compare these to a collection of the best translators in the world.
So you're exactly on track, that humans are heavily prejudiced against even simple mistakes that computers make, yet let consistent continuous mistakes slide for humans.
I don't think that's really true. They're comparing them to the performance of a person who is a native speaker of both of the languages in question. That seems like a pretty reasonable comparison point, since it's basically the ceiling for performance on a translation task (leaving aside literary aspects of translation). If you know what the sentence in the source language means, and if you know the target language, then you can successfully translate. Translation isn't some kind of super difficult task that only specially trained translators can do well. Any human who speaks two languages fluently (which is not rare, looking at the world as a whole) can translate between them well.
No, sadly, that's not the case. A bilingual person may create a passable translation, in that they can keep the main gist and that all the important words in the original text will appear in the translated text in some form, but that does not automatically make it a "well-translated" text. They are frequently contorted, using syntaxes that hardly appear in any natural sentences, and riddled with useless or wrong pronouns.
A good translation requires more skill than just knowing the two languages.
> They are frequently contorted, using syntaxes that hardly appear in any natural sentences, and riddled with useless or wrong pronouns.
I find it hard to believe that this is the case if the translator is a native speaker of the target language. I mean, I might do a bad job of translating a Spanish text to English (because my Spanish sucks), but my translation isn't going to be bad English, it's just going to be inaccurate.
As a Korean speaker, if I walk into a bookstore and pick up any book translated from English, and read a page or two, chances are that I will find at least one sentence where I can see what the original English expression must have been, because the translator chose a wrong Korean word which sticks out like a sore thumb. Like, using a word for "(economic/technological) development" to describe "advanced cancer". Or translating "it may seem excessive [to the reader] ..." into "we can consider it as excessive ..."
And yes, these translators don't think twice about making sentences that no native speaker would be caught speaking. Some even defends the practice by saying they are faithful to the European syntax of the original text! Gah.
That sounds like a mistake caused by the translator having a (relatively) poor knowledge of English. A bilingual English/Korean speaker wouldn't make that mistake. I mean, I don't know your linguistic background, but you clearly know enough English and Korean to know that that's a bad translation, and you presumably wouldn't have made the same mistake if you'd been translating the book.
>Some even defends the practice by saying they are faithful to the European syntax of the original text!
I think there's always a tension between making the translation faithful to the original text and making it idiomatic. That's partly a matter of taste, especially in literature.
Well, "bilingual" is not black and white. I think you have a point here, but considering that people who are paid to translate can't get these stuff right, the argument veers into the territory of "no true bilingual person".
Anyway, my pet theory is that it is surprisingly hard to translate from language A to B, even when you are reasonably good at both A and B. Our brain is wired to spontaneously generate sentences: given a situation, it effortlessly generates a sentence that perfectly matches it. Unfortunately, it is not trained at all for "Given this sentence in language A, re-create the same situation in your mind and generate a sentence in language B that conveys the same meaning." In a sense, it is like acting. Everybody can laugh on their own: to convincingly portray someone else laughing is quite another matter.
They are however consistent since their pay check depends on it.
Not entirely, but it is definitely possible for someone to be a native speaker of two languages, and they wouldn't make those kinds of mistakes if they were.
Which is synonymous with the best translators in the world. Those people are relatively few and far between honestly - I've traveled a lot and I'd argue that native bi-lingual people are quite rare.
https://www.researchgate.net/post/What_is_the_percentage_of_...
Our best AIs are superhuman only at tightly scoped tasks, and our prejudice encodes the utility we get from the flexibility and resilience of general intelligence.
I don't think any particular human is so general in intelligence. We can do stuff related to day to day survival (walk, talk, eat, etc) and then we have one or a few skills to earn a living. Someone is good at programming, another at sales, and so on - nobody is best at all tasks.
We're lousy at general tasks. General intelligence includes tasks we can't even imagine yet.
For thousands of years the whole of humanity survived with a mythical / naive understanding of the world. We can't even understand the world in one lifetime. Similarly, we don't even understand our bodies well enough, even with today's technology. I think human intelligence remained the same, what evolved was the culture, which is a different beast. During the evolution of computers, CPUs remain basically the same (just faster, they are all Turing machines) - what evolved was the software, culminating in current day AI/ML.
What you're talking about is better explained by prejudice against computers based on past experience, but we're bad at predicting the evolution of computing and our prejudices are lagging.
Venkatesh Rao had a great piece on how mediocre we really are recently:
https://www.ribbonfarm.com/2018/04/24/survival-of-the-medioc...
Generally people think superhuman = better than the best humans. I understand this and it's an obvious choice, but it assumes that humans are measured on a objective scale of quality for a task, which is rarely the case. Being on the front line of deploying ML systems, I think it's the wrong way to measure it.
I think Superhuman should be considered relative to the competence level of average person who has the average amount of training on the task. This is because from the "business decision" level, if I am evaluating between hiring a human with a few months or a year of training and a tensorflow docker container that is reliably good/bad, then I am going to pick the container every time.
That's what is relevant today - and the container will get better.
Because that's what it means.
Also, I shudder to think of the prose coming out of a company that decides to "hire" an AI instead of a translator...
There's been some tentative discussion of using Lojban as a basis for just that!
https://en.wikipedia.org/wiki/Lojban#Lojban_as_a_potential_m...
That's what Roger Schank is advocating against in his article: artificial intelligence that makes humans think like computers, rather than computers that think like humans.
Personally, I think it's a terrible idea and the path to becoming like the Borg: a species of people who "enhanced" themselves until they lost everything that made them people.
Also: people may get stuff wrong a lot of the time (way more than 10%). But, you can always make a human understand what you mean with enough effort. Not so with a "computer" (i.e. an NLP system). Currently, if a computer can't process an utterance, trying to explain it will confuse it even further.
In a world that moves too quick to have review/ratings companies for everything, you should come in skeptical and be proven wrong.
Its up to the merchant to make a great product, its up to you to compare and make good decisions.
I don’t even know who those ads are targeting. Anyone who knows anything at all about this stuff will be dismayed at the sheer BS of it all. Everyone else seeing the ads isn’t in a position to steer customers towards IBM for all their AI needs. They really need to kill the whole ad campaign, surely it’s doing IBM more harm than good.
And it is a very old problem, at least from the time of Drew McDermot and "Artificial Intelligence meets Natural Stupidity":
https://homepage.univie.ac.at/nicole.rossmanith/concepts/pap...
From which I quote:
However, in AI, our programs to a great degree are problems rather than solutions. If a researcher tries to write an "understanding" program, it isn't because he has thought of a better way of implementing this well-understood task, but because he thinks he can come closer to writing the _first_ implementation. If he calls the main loop of his program UNDERSTAND, he is (until proven innocent) merely begging the question. He may mislead a lot of people, most prominently himself, and enrage a lot of others.
I don't think anyone would have flinched at setting the stage like "At IBM we're working on technology so that some day your interaction with a computer can be as simple as sitting down and having a conversation."
Setting expectations you cannot meet is something you try to avoid in Marketing. Because you get angry op eds like the one that kicked off this conversation.
Like those old AT&T commercials (available on YouTube) where AT&T made all kinds of predictions about the future that seemed crazy in the 1980's, but are reality 35 years later. Video calls, instant electronic toll booth payment, etc...
/ R.I.P, AT&T.
Totally crap, especially since tmobile runs ads that have pink background and 1 word on the screen:
UNLIMITED
No. Its not unlimited. I know because I paid 25 extra dollars for a month for their international plan. Truly unlimited.
Nonetheless, I watched people get really worked up about what the computer was 'saying'. Partly because of the sarcastic stuff people would say, partly because of their expectations about 'cybernetic brains'.
Now the 'Cyc'le is back. And people actually working on this really hard problem are not helped by dumb marketing.
How about prosecuting them for false advertising? Seems like a classic case, albeit in a new domain.
False advertising is claiming to be something you are not, raising false expectations.
Warning, this advertisement is a lie. Believing this advertisement may harm your cognitive health.
You overestimate people's understanding of space. Many people thought "The Martian" was a true story like "Apollo 13".
Easy: just say that all Watson systems have the hardware needed for cognitive computing and full dialog support.
We’d all see the problem with such a situation. People with a 6th grade knowledge on space travel understand that the commercials were BS marketing and we should fire the executives for not knowing the same or doing their due diligence. We’d be mad at SpaceX for taking advantage of companies and failing to reach Mars as promised.
Google Assistant, Apple Siri and Amazon Echo are all quite fancy natural language parsers. After parsing, it's just a group of "dumb" (wo)man-made widgets.
Which is a really weird and nebulous thing to define, by the way. I think we aren't going to have super convincing cognitive computing until we have something approaching AGI. Which of course is waaay different from the AI and machine learning that is popular today, despite most laypeople conflating any mention of AI with AGI. Of course, when IBM is making an ad, they are largely aiming at laypeople.
Also we (science) know shockingly little about real dialogs and their challenges as far as I can find out - but I am not a linguist and am angling here fore some killer references !
> Full Self-Driving Hardware on All Cars
> All Tesla vehicles produced in our factory, including Model 3, have the hardware needed for full self-driving capability at a safety level substantially greater than that of a human driver.
https://www.theverge.com/2018/3/28/17172178/tesla-model-x-cr...
In the moralistic sense, yes, Tesla needs to be reprimanded for its actions. However, lying in this manner is often well-protected by law, if you manage to include enough legalese disclaimers somewhere, and I suspect Tesla has enough lawyers to make sure that legalese is sufficient to disclaim all liability.
That seems overly optimistic, if not an outright fabrication.
Please provide evidence.
Given that the only full-self driving system out there is Waymo's, which uses completely different hardware than Tesla's, it is impossible to back your claim, unless you develop a fully-self-driving system on top of Tesla's hardware.
So until that is done, your claim is false, no matter how many caps you use.
My phone also has cameras and a processor. Are you implying that my phone is as equipped to drive a car as a human?
A monkey has eyes, a brain, arms and legs. Are you implying that a monkey is as equipped to drive a car as a human?
This couldn't be further from the truth as automated vehicles still suffer from edge cases (remember the lethal accident involving a concrete pillar) where humans can easily make better decisions.
A system that is advertised as superior to human judgement ought to strictly improve on human performance. Nobody expects that to mean that the car drives perfect 95% of the time but accidentally kills you in a weird situation. This 'idiot savant' characteristic of ML algorithms is what makes them still dangerous in day-to-day situations.
Do you know how many people die in normal, non-self-driving cars? It's never possible to get 100% accuracy.
Who do you blame?
No one is saying guns, or cars, aren't dangerous. However this kind of false advertising leads people to use cars in dangerous ways while believing they are safe because they've been lied to.
(Side note, there is some fine print you never read that says the safe-gun technology only works when you point the gun at a single person and doesn't work on crowds.)
It means this will kill people but fewer people than humans would and they have actual data that backs this assertion up.
The benchmark is not an alert, cautious, and sober driver because that's often not how actual people drive. So right now it's often safer to drive other times it really is safer to use autopilot, net result fewer people die.
Ideally Tesla's marketing would say it's safer than drunk, sleepy, and reckless drivers, though it might not sell as many Autopilots.
I also imagine that cars will learn from both human and each others' driving patterns over time, which (under effective guidance) should enable an enormous improvement in a relatively short period of time.
However, I take the other interpretation. I don't think crashes are randomly distributed. That that scenario is absolutely perfect is really the problem because of humans. All a crash takes is a second of attention lapse at a really bad time. And in such perfect circumstances we get bored and take road safety for granted as opposed to driving at night or navigating around some tricky curves. And that's a perfect scenario to end up getting yourself killed in. And more importantly here, that's also the absolutely perfect scenario for self driving vehicles who will drive under such conditions far better than humans simply because it's extremely trivial, but they will never suffer for boredome or lack of attention.
Or well, I just put four cameras on my car and inserted their USB wires into an orange. I declare that this is enough for FSD now. I don't have to prove anything for such an absurd statement?
So, do you think it may be possible that people do understand the distinction and are STILL not convinced?
You may be breaking the law as well, depending on the gun laws in your area, but as I understand it (IANAL) the manslaughter charge of entirely on the shooter.
Tesla owner faces 18-month ban for leaving the driver's seat https://www.engadget.com/2018/04/29/tesla-owner-faces-road-b...
In that study there are two buckets, one which is total Tesla miles in TACC-enabled cars and then after the update total Tesla miles in cars with TACC + Autosteer and they calculated on airbag deployments. Human driven miles are going to dominate both of those buckets and there's a reason the NHTSA report makes zero claims about Tesla's safety relative to human drivers. It's totally outside the scope of the study. Then add in that some researchers who are skeptical of the methodology and have been asking for the raw data from NHTSA/Tesla have yet to receive it.
https://news.ycombinator.com/item?id=16932350
Autosteer, however, is relatively unique to Tesla. That’s what makes singling out Autosteer as the source of a 40 percent drop so curious. Forward collision warning and automatic emergency braking were introduced just months before the introduction of Autosteer in October 2015. A previous IIHS study shows that both the collision warning and auto emergency braking can deliver a similar reduction in crashes.
You can define it however you want. By any common sense definition of safety Tesla has not proven that their autopilot is 'safer' than a human driver.
>10x or 100x the number of deaths would be small price to pay to get everyone in autonomous vehicles.
This supposes a couple things. Mainly that autonomous vehicles will become safer than human drivers, that you know roughly how many humans will have to die to achieve that and that those humans have to die to achieve it. Those are all unknown at this point and even if you disagree about the first one (which I expect you might) you still have to grant me two and three.
Can Autopilot not run passively and prevent human errors? Why are the two options presented seem to be only "only a human behind the wheel, not assisted by even AEB" and "Full autopilot with no human in the car at all".
But if you build faulty staircases that make people slip, they can still put you in jail or sue you.
Same if you push them down the stairs.
false equivalency. you need at least compare per mile, at best by driver demographic since most tesla drivers are in the high income and maybe in the safety conscious bracket
Deaths caused by Uber and Tesla hold little repercussions for them other than bad PR.
The US govt celebrates removing regulations which benefit its corporations at the cost of its citizens
Financial ruin for the company that was willing to put that BS below it's letterhead? Yeah, sure, in proportion with the harm caused. That said, human life isn't sacred. It and everything else gets trades for dollars all the time. A death or three shouldn't cripple a big company like Tesla unless they were playing so fast and loose that there's significant punitive damages.
In a large company like Tesla it shouldn't be marketing's job to restrain itself. That's not safe at that scale. There should be someone or a group who's job it is to prevent marketing from getting ahead of reality just like it's security's job to spend all day playing whack-a-mole with the stupid ideas devs (especially the web ones) dream up. Efficiently mediating conflicting interests like that is what the corporate control structure is for.
People using your product in accordance with your marketing should be considered almost the same as in accordance with your documentation. While "people dying while using the product in accordance with TFM" is not treated as strict liability it's pushing awfully close.
I see it as a simple case of the company owning up to its actions. It failed to manage itself properly, marketing got ahead of reality. You screw up and someone gets hurt then you pay up.
It's one thing to talk about punitive damages and liability, these are factual mechanisms of our legal system. But just because damages can be paid and are on a regular basis they do not imply that there is some socially acceptable let alone codified price for a human life. And we should hope for our own sake there never is.
I agree that marketing should not be allowed to let their imagination run wild to the detriment of the company.
In the case of the liability bit IANAL but that's likely to differ between industries. Some sectors like aviation are highly regulated and require certification of the aircraft and the airplane flight manual is tied to that serial number and is expected to be, correct and free of gross errors for normal operation. So liability can vary. Are you suggesting from experience that there is no liability in the case of Tesla taking into account their industry's context? I don't know enough about their industry to judge, just looking for clarification.
Wow. Uhm, slavery is illegal if you haven't heard. We made it illegal because life is sacred.
Punitive damages go part way to help prevent this, but not far enough to guarantee that it never happens.
Had the society truly believed life to be sacred, I suspect we’d have very different business practices and penalties that are not limited to financial ruin.
You can build a highway overpass with a center support on the median for X and there will by a small chance of someone crashing into it and getting killed. You could design one without a support on the median but it will cost Y (Y is substantially more than X). Now scale that decision to all overpasses and you've got a substantial body count. At the end of the day it's a trade-off between lives/injury and dollars.
It seems odd to argue that. Yeah of course we can't stop doing things, but it doesn't mean we don't try really hard to avoid killing people.
Yes, and both Elon Musk as an individual and Tesla Motors as an organization agree. How they approach that idea is somewhat different from what we're used to though.
Their basic assertions are (in my words): 1. Vision and radar based technology, along with current generation GPUs and related hardware, along with sufficiently developed software, will be able to make cars 10x safer. 2. How quickly total deaths are reduced is tied directly to how quickly and widely such technology is rolled out and used. 3. Running in 'shadow' mode is a good source of data collection to inform improvements in the software. 4. Having the software/hardware actually control cars is an even better source of data collection to accelerate development. 5. There is additional, incremental risk created when the software/hardware is used in an early state. 6. This is key: the total risk over time is lessened with fast, aggressive rollouts of incomplete software and hardware, because it will allow a larger group of people to have access to more robust, safer software sooner than otherwise would be possible.
That last point is the balance: is the small additional risk Tesla is subjecting early participants to outweighed by how much more quickly the collected data will allow Tesla to produce a more complete safety solution?
We don't know for sure yet, but I think the odds are pretty good that pushing hard now will produce more total safety over time.
> life is sacred
This is my background as well, and its an opinion I personally hold.
At the same time, larger decisions, made by society, by individuals, and by companies, must put some sort of value on life. And different values on different lives. Talking about how much a life is worth is a taboo topic, but it's something that is considered, consciously or otherwise, all day, every day, by many people, myself included.
Most every big company, Tesla Motors included,make decisions based on these calculations all the time. Being a 'different kind of company' in many ways, Tesla makes these calculations somewhat differently.
Why then does Tesla have a pass? There's no evidence it's actually safer. And there's no evidence that the company is truthful. We don't accept when a pharmaceutical company says, "no, it's good. Trust us." That would be crazy. We should not accept Tesla's assurances with blind faith simply because they have better marketing and a questionable ethical standard.
http://driving.ca/tesla/model-s/auto-news/news/iihs-study-sh...
Tesla is safer for the community based on the statistical data. Also it is safer than a human driving. I’m not saying it will never crash just that it will crash less than a human.
Maybe another way to compare it would be to an autopilot in airplanes. Sometimes it fails so we might as well be angry at the airline companies if they advertise it. But a pilot would make more mistakes than the autopilot with the current workload.
Side note: if you are going to downvote you can comment on why. Negative feedback is very useful and helps build better argumentative skills.
What is lower and compared to what? I am tired of this vague misleading statements by Elon musk, Tesla and their supporters.
They claimed Autopilot + driver is 40% safer than a driver alone. And that includes Automatic emergency braking. Is it a surprise that AEB reduces accidents?
Why is that used as proof that Tesla's software is FSD. FSD implies that the car is capable of driving without a driver.
Is Autopilot alone safer than a driver? There is no proof of that
But what you should compare is Autopilot alone compared with a driver assisted by Autopilot. So, is Autopilot better than Driver+Autopilot? I can assure you its not, the driver still adds value.
Reddit is dominated by tesla's marketing team. Upvoting, downvoting, and commenting.
Here you get a real discussion regarding Elon's outlandish promises.
One of the big issues here is the concept of "human error", as though a statistical average is some sort of monolith that can be applied to all humans. The truth is that many people lack the basic skills and attributes needed to drive safely (concentration, attention to detail, the ability to multitask effectively). This is true even before factoring the millions of elderly people who are unable to tie their own shoes or operate a self-checkout kiosk who are out on the road making things more dangerous for everyone (including themselves). Performing virtually any task better than "the average human" is a very, very low bar to hurdle. The question is, what standard should we be using to determine who (or what, in the case of self-driving cars) should be allowed to pilot a multi-ton vehicle on public streets? The truth is that we favor convenience over safety (and I'm not even arguing that this is a bad thing - just that it is an often ignored fact) in many facets of society, and in order to have an intelligent debate about self-driving cars we ought to recognize and acknowledge this fact.
People just assume that if a computer does something, it's going to be perfect. It isn't.
Most humans can't even "self-walk" without occasionally stumbling and falling. Does that make human locomotion dangerous and false?
I admit I recently upped that number from "5-10 years minimum" after seeing the media reaction to recent driver-assist systems related accidents — it became clear to me that the old adage "the autonomous car does not need to be perfect, it only needs to be better than an {average, good, skilled} human driver" is simply wrong, because autonomous car brand X will be regarded - and judged - as if all X cars are one driver. Thus, these cars actually need to be much better than humans in essentially any traffic situation, because it simply won't be acceptable for "autonomous cars of brand X" to kill a few thousand people each year in every country. People would equate this to a single human driver mowing down thousands.
This effect is not necessarily bad, I don't have the inside information, but it's likely (or at least probable) that manufacturers invested in this technology observed the same and drew a similar conclusion.
The question now is whether the car makers make autonomous cars that good, or invest into massive PR campaigning to change public perception towards "each autonomous car is like an individual driver and it doesn't need to do much better than that".
We've seen the latter before. Jaywalking and avenues are just two examples.
Still a bit deceptive, to me. Reminds me of "...electroplated in 16 carat gold...".
At some point, critical thinking is required to navigate the world. The customer should ask “and when will the software catch up?” And I’ll concede that the overwhelming majority of the population doesn’t think like that. Should Tesla update the site with statements to confirm the negative cases? e.g. “Our software can’t yet do X, Y, Z, etc”
At some point, they will have to provide said demo or they will be facing a class action lawsuit that will bankrupt the company.
that's false too. how would one prove that the current shipped hardware is sufficient for autopilot? some hardware is present for sure, but is it all needed as they claim? they cannot know, since they don't have an autopilot using such hardware to achieve the stated goal. they believe it is sufficient, which is quite not the same as the claim and it is also being vocally challenged by experts that criticize the decision of omitting full lidar coverage
Also, how can we even know the hardware is sufficient unless said software exists and shows that what we think is possible is indeed possible?
Some hardware is present, but that it is sufficient for full self-driving is simple speculation for which Tesla has no reasonable basis. The only way for them to know it is sufficient is to have self-driving implemented on it, which they obviously don't.
Its at best empty puffery and at most outright fraud, but in either case it's a knowingly unjustified claim, even if not knowingly false.
Or are you suggesting that there are Tesla owners who are (a) sitting in their driveway wondering why their car isn't driving them to work or (b) returning their cars upon finding out many of the features on the Autopilot page require regulatory approval?
Tesla driver caught turning on autopilot and leaving driver’s seat on motorway Culprit admits he knew what he had done was ‘silly’ but that the car was capable of something ‘amazing’
It's really not that deceptive. People would have to be a lot dumber than they actually are to be confused about it.
I'd say that if they're claiming to be able to deliver full self-driving autonomy to existing cars via purely a SOFTWARE upgrade, then that's pretty deceptive, since I am pretty sure not even Tesla knows exactly what hardware might be required for such capability. They'll know when they build it, but not before.
That's one level past dishonest. Honest advertising would just be "none of our cars have full self-driving capability at a safety level substantially greater than that of a human driver".
But this is on another level. Have they ever actually ran software that does, indeed, have this capability? Or do they have a detailed enough specification of that software, so that they can verify that it will, indeed, run on that hardware once it's written?
It's probably a safe bet that they haven't, and they don't, and in fact there is no way to verify that the hardware is in fact capable of running such software. This is likely a good engineering bet (i.e. the hardware is probably enough to support their current software approach, and they'll hit the software's limitations before they hit the hardware's), but advertising engineering bets as safety-related selling points is really irresponsible. Bet with your own money all you want, but not with people's lives.
Who's to know if there isn't a third key component necessary for that, behind yet another technical term?
Isn't Tesla's autopilot doing better than humans do in the same number of miles? We just all hear about it every time a Tesla is in a crash. If we heard about every human driver car accident, it would be overwhelming.
edit:
from this article: https://electrek.co/2018/03/30/tesla-autopilot-fatal-crash-d...
In the US, there is one automotive fatality every 86 million miles across all vehicles from all manufacturers. For Tesla, there is one fatality, including known pedestrian fatalities, every 320 million miles in vehicles equipped with Autopilot hardware. If you are driving a Tesla equipped with Autopilot hardware, you are 3.7 times less likely to be involved in a fatal accident.
Disclosure: I am one of the co-authors
every 320 million miles in vehicles equipped with Autopilot hardware.
does not mean 320 million miles with autopilot controlling the vehicle. Who knows how many of those miles are human driven?
Since a Tesla is often owned by people with better economic means, their statistics is not representative of all vehicles. The average vehicular fatality rate of this demographics and vehicle type could be well below that of Tesla with Autopilot.
What is the accident statistic for Teslas not equipped with Autopilot hardware?
If Autopilot enabled cars are so much safer than human drivers, can they pass a written and road side driver's license test?
If SpaceX were to advertise like that, they would have famous people sitting in their living room, on mars, and talking about what they liked about the Martian way of life. In that case I believe that most people would understand that SpaceX wasn't already hosting people on Mars.
Unfortunately many, many people think that talking to your computer in actually already possible, they just haven't experienced it yet. Not sure how we fix that.