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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 p

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

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