3 ms·

One other thing I'd like to add. The scenario of AI mostly replacing people like doctors and lawyers involves bizarre paradoxes beyond whether deep learning "A

One other thing I'd like to add. The scenario of AI mostly replacing people like doctors and lawyers involves bizarre paradoxes beyond whether deep learning "AI" works as advertised. Suppose you can train an "AI" to read legal papers or diagnose patients based on X-rays. That training is done from the data of real life lawyers and doctors actions. Suppose, best case scenario (very unrealistic imo btw), you have a complete "snapshot" of the behavior of lawyers and doctors in a given year. The problem is reality changes, you need new lawyering and doctoring behaviors after N years. Doctors need interpret new maladies, lawyers need to cite new decisions and both need to interpret new language forms that appear. But if you've actually removed the real lawyers and doctors, where would you get the new training data? And this is just taking AI at it's word.

rebelos 6y ago
The only way you could be beguiled by this framing is if you don't understand just how inept most doctors and lawyers really are. A future configuration will probably look something like: far fewer highly talented doctors and lawyers remain employable while the rest are replaced by AI that's shown to be vastly more capable, and that is continually enhanced by the encoded expertise of said highly talented remaining specialists.
- joe_the_user 6y ago
  You don't understand just how inept most doctors and lawyers really are. It doesn't matter how competent or incompetent whatever professional might be. The only thing a deep learning application is going to do is duplicate their behavior. Deep learning involves no "thinking" at all. Just a very elaborate, brute force curve fitting. If the doctors are on average "incompetent" so will be the deep learning app (ie, you kind fall for the sort of "since it's a machine, it will be accurate" fallacy that makes people want to trust self-driving cars) A future configuration will probably look something like: far fewer highly talented doctors and lawyers. If you really automated the work of lawyers and doctors with explicit, maybe. BUT that isn't how "deep learning" work. Deep learning just uses data and the problem is you need sufficient data, a sufficiently large corpus of data to show by many, many examples what the thing should do. Oddly enough, your scenario of high expert adding their expertise to the system is much more like the original Gofai model where a few experts would hypothetically program in their expertise. That scenario fell with difficulty of expertise programming. The present systems can't work that way.
  - rebelos 6y ago
    > Oddly enough, your scenario of high expert adding their expertise to the system is much more like the original Gofai model where a few experts would hypothetically program in their expertise. That scenario fell with difficulty of expertise programming. The present systems can't work that way. Taking a generalized approach will fail. Taking a tailored, domain-specific one that incrementally carves out use cases will be the basis of future success in these spaces.
  - smilekzs 6y ago
    > fallacy that makes people want to trust self-driving cars A lot of successful L4+ autonomous vehicles today, contrary to what the press releases want you to believe, are architectured first and foremost as non-learning (i.e. traditional robotics) systems, with relatively well-defined domain-specific sub-problems carved out and delegated to learning-based methods (e.g. recognizing all cars/humans/signs/... in images captured by the vehicle's cameras). These problems tend to have well-defined metrics and massive real-world data sets backing them up, and are increasingly more common to report how confident they are in the provided results. ADVs have come a long way despite all the doubt, and the top players are finally getting confident in removing the human from the driver's seat. This is not trivial in the post-Uber-ADV-fatal-accident world. Source: I work on ADVs.
- hooande 6y ago
  the opposite if this is true. with scifi ai on that level, bad lawyers would just pay to use the ai for legal work and focus on developing social relationships to get valuable clients. this is how a lot of professionals spend their time now most things in life that make a lot of money are social. if everyone has access to ai knowledge and skills that can be copied, then the social aspect is even more important
jay_kyburz 6y ago
I assume the author is using AI to mean software in its broader sense, not just a machine learning algorithm. Somebody will eventually write and algorithm that actually understands the laws as they are written, the case law that interpret them, and can read and write contracts. The algorithm might not have anything to do with ML. I would like to think one day we'll actually understand how our bodies work and can diagnose problems as if we were debugging software rather than stabbing into the dark with drugs.
auganov 6y ago
Some of it is just framing. You can replace a lot of what doctors do with regular tech and plain old organization. You could have done it for decades. Problem is regulations put a lot of limitations on who can perform what service. You can get the best well-informed advice from wherever, but you still need to go to a doctor for your prescription. I could very well see a situation where "AI" is what finally gets regulators to loosen up, but what actually gets implemented will be traditional stuff that works. It may take a "surgery robot" to allow greater freedom in training people to perform surgeries. Won't be surprised if in 20 years self driving cars will indeed come to dominate. But most "AI" will get dropped and roads will be retrofitted with something dead simple that assists cars in navigating (I believe that idea goes back to 50s or 60s too).

rebelos 6y ago

The only way you could be beguiled by this framing is if you don't understand just how inept most doctors and lawyers really are. A future configuration will probably look something like: far fewer highly talented doctors and lawyers remain employable while the rest are replaced by AI that's shown to be vastly more capable, and that is continually enhanced by the encoded expertise of said highly talented remaining specialists.

joe_the_user 6y ago
You don't understand just how inept most doctors and lawyers really are. It doesn't matter how competent or incompetent whatever professional might be. The only thing a deep learning application is going to do is duplicate their behavior. Deep learning involves no "thinking" at all. Just a very elaborate, brute force curve fitting. If the doctors are on average "incompetent" so will be the deep learning app (ie, you kind fall for the sort of "since it's a machine, it will be accurate" fallacy that makes people want to trust self-driving cars) A future configuration will probably look something like: far fewer highly talented doctors and lawyers. If you really automated the work of lawyers and doctors with explicit, maybe. BUT that isn't how "deep learning" work. Deep learning just uses data and the problem is you need sufficient data, a sufficiently large corpus of data to show by many, many examples what the thing should do. Oddly enough, your scenario of high expert adding their expertise to the system is much more like the original Gofai model where a few experts would hypothetically program in their expertise. That scenario fell with difficulty of expertise programming. The present systems can't work that way.
- rebelos 6y ago
  > Oddly enough, your scenario of high expert adding their expertise to the system is much more like the original Gofai model where a few experts would hypothetically program in their expertise. That scenario fell with difficulty of expertise programming. The present systems can't work that way. Taking a generalized approach will fail. Taking a tailored, domain-specific one that incrementally carves out use cases will be the basis of future success in these spaces.
- smilekzs 6y ago
  > fallacy that makes people want to trust self-driving cars A lot of successful L4+ autonomous vehicles today, contrary to what the press releases want you to believe, are architectured first and foremost as non-learning (i.e. traditional robotics) systems, with relatively well-defined domain-specific sub-problems carved out and delegated to learning-based methods (e.g. recognizing all cars/humans/signs/... in images captured by the vehicle's cameras). These problems tend to have well-defined metrics and massive real-world data sets backing them up, and are increasingly more common to report how confident they are in the provided results. ADVs have come a long way despite all the doubt, and the top players are finally getting confident in removing the human from the driver's seat. This is not trivial in the post-Uber-ADV-fatal-accident world. Source: I work on ADVs.
hooande 6y ago
the opposite if this is true. with scifi ai on that level, bad lawyers would just pay to use the ai for legal work and focus on developing social relationships to get valuable clients. this is how a lot of professionals spend their time now most things in life that make a lot of money are social. if everyone has access to ai knowledge and skills that can be copied, then the social aspect is even more important

jay_kyburz 6y ago

I assume the author is using AI to mean software in its broader sense, not just a machine learning algorithm. Somebody will eventually write and algorithm that actually understands the laws as they are written, the case law that interpret them, and can read and write contracts. The algorithm might not have anything to do with ML. I would like to think one day we'll actually understand how our bodies work and can diagnose problems as if we were debugging software rather than stabbing into the dark with drugs.

auganov 6y ago

Some of it is just framing. You can replace a lot of what doctors do with regular tech and plain old organization. You could have done it for decades. Problem is regulations put a lot of limitations on who can perform what service. You can get the best well-informed advice from wherever, but you still need to go to a doctor for your prescription. I could very well see a situation where "AI" is what finally gets regulators to loosen up, but what actually gets implemented will be traditional stuff that works. It may take a "surgery robot" to allow greater freedom in training people to perform surgeries. Won't be surprised if in 20 years self driving cars will indeed come to dominate. But most "AI" will get dropped and roads will be retrofitted with something dead simple that assists cars in navigating (I believe that idea goes back to 50s or 60s too).