Welcoming Our New Robotic Overlords
newyorker.com
Welcoming Our New Robotic Overlords
1–10 of 49 posts
Re: Welcoming Our New Robotic Overlords
#2I think that soon it will be considered a bad practice to possess a skill or to use some knowledge for decisions..
If you have learned to do something, you will proceed by teaching a machine learning system that. And then you will use that, and not your internal knowledge.
The reason will be cited as follows: If you know something, this introduces bus factor. People can't get in your head to validate if you're applying your knowledge fairly, or biased, or maliciously misappropriating things. Your reasoning is unverifiable. You can leave for greener pastures, carrying your skills and knowledge with you.
While machine learning system is repeatable, you can have all kinds of checks and KPIs. And it's protected by IP laws.
Human domain knowledge will be discouraged.
Re: Welcoming Our New Robotic Overlords
#3I think that soon it will be considered a bad practice to possess a skill or to use some knowledge for decisions.. If you have learned to do something, you will proceed by teaching a machine learning system that. And then you will use that, and not your internal knowledge. The reason will be cited as follows: If you know something, this introduces bus factor. People can't get in your head to validate if you're applyi…
I don't know if this adds or subtracts from your dystopian view, but the act of training the machine would introduce the same reasoning/bias flaws one has.
(see the MIT moral machine)
Re: Welcoming Our New Robotic Overlords
#4I think that soon it will be considered a bad practice to possess a skill or to use some knowledge for decisions.. If you have learned to do something, you will proceed by teaching a machine learning system that. And then you will use that, and not your internal knowledge. The reason will be cited as follows: If you know something, this introduces bus factor. People can't get in your head to validate if you're applyi…
I don't know if this adds or subtracts from your dystopian view, but the act of training the machine would introduce the same reasoning/bias flaws one has. (see the MIT moral machine)
At least it is repeatable and measurable. But yours isn't.
I'm not sure it's dystopian. Maybe human decision making will be considered art. That's an awesome thing, but not necessary what you do in workplace.
Re: Welcoming Our New Robotic Overlords
#5I think that soon it will be considered a bad practice to possess a skill or to use some knowledge for decisions.. If you have learned to do something, you will proceed by teaching a machine learning system that. And then you will use that, and not your internal knowledge. The reason will be cited as follows: If you know something, this introduces bus factor. People can't get in your head to validate if you're applyi…
I don't know if this adds or subtracts from your dystopian view, but the act of training the machine would introduce the same reasoning/bias flaws one has. (see the MIT moral machine)
Weapons of Math Destruction is also a good resource on this topic, about how bias is already being encoded in "black box" algorithms that has real effects on things like the availability of credit.
Re: Welcoming Our New Robotic Overlords
#6I think that soon it will be considered a bad practice to possess a skill or to use some knowledge for decisions.. If you have learned to do something, you will proceed by teaching a machine learning system that. And then you will use that, and not your internal knowledge. The reason will be cited as follows: If you know something, this introduces bus factor. People can't get in your head to validate if you're applyi…
This is an interesting take, but I think part of what makes us human is our inability to disassociate our “domain knowledge” from our sense of self.
Much domain knowledge is in some sense innate or even subconscious, picked up in the field. I think it would be more efficient just to spy on people’s thoughts (and work) in some manner if there is a fear they could misapply their knowledge or leave a critical process hanging.
Re: Welcoming Our New Robotic Overlords
#7I think that soon it will be considered a bad practice to possess a skill or to use some knowledge for decisions.. If you have learned to do something, you will proceed by teaching a machine learning system that. And then you will use that, and not your internal knowledge. The reason will be cited as follows: If you know something, this introduces bus factor. People can't get in your head to validate if you're applyi…
This is an interesting take, but I think part of what makes us human is our inability to disassociate our “domain knowledge” from our sense of self. Much domain knowledge is in some sense innate or even subconscious, picked up in the field. I think it would be more efficient just to spy on people’s thoughts (and work) in some manner if there is a fear they could misapply their knowledge or leave a critical process ha…
Yes they will allow for a degree of inefficiency if it removes human factor.
The reasoning will go, yes we are losing $1 on every automated transaction, but we can make more of them, and we certainly avert one $10,000 corruption case and one $100,000 case where we get sued for human decision.
You can't sue machine learning algorighm (that how it would go). But human, you can, even frivolously.
Re: Welcoming Our New Robotic Overlords
#8Earlier quoted context omitted.
This is an interesting take, but I think part of what makes us human is our inability to disassociate our “domain knowledge” from our sense of self. Much domain knowledge is in some sense innate or even subconscious, picked up in the field. I think it would be more efficient just to spy on people’s thoughts (and work) in some manner if there is a fear they could misapply their knowledge or leave a critical process ha…
Yes they will allow for a degree of inefficiency if it removes human factor. The reasoning will go, yes we are losing $1 on every automated transaction, but we can make more of them, and we certainly avert one $10,000 corruption case and one $100,000 case where we get sued for human decision. You can't sue machine learning algorighm (that how it would go). But human, you can, even frivolously.
Yes but you can sue the company that owns the machine learning algorithm, probably for much more money than you can sue an individual. You can even imagine class action law suites and the like.
(I am one of the researchers mentioned in the article.)
Re: Welcoming Our New Robotic Overlords
#9Earlier quoted context omitted.
This is an interesting take, but I think part of what makes us human is our inability to disassociate our “domain knowledge” from our sense of self. Much domain knowledge is in some sense innate or even subconscious, picked up in the field. I think it would be more efficient just to spy on people’s thoughts (and work) in some manner if there is a fear they could misapply their knowledge or leave a critical process ha…
Yes they will allow for a degree of inefficiency if it removes human factor. The reasoning will go, yes we are losing $1 on every automated transaction, but we can make more of them, and we certainly avert one $10,000 corruption case and one $100,000 case where we get sued for human decision. You can't sue machine learning algorighm (that how it would go). But human, you can, even frivolously.
Well, where "Machine Learning" (aka: black box you can only get weights for a given question), one can train a machine to be racist, sexist, ageist, or whatever.
The problem is that the end weight distribution is different than the GB's or TB's of training data. How do we know the training was fair and impartial? How did the trainers even know if it was? What biases crept in on this stage?
Worse yet, what if the bias of the black box does denigrate black people... Say, we take in all pictures of convicted criminals- it's disproportionaly black. I would argue part of that is because of inherent policing biases, but that's embedded in "guilty" verdict. Who's at fault for this "bias"? Is there a fault? How do we detect, other than exhaustively?
I'm eagerly awaiting for methods to "open up" ML black boxes and see what makes them tick. See their decision trees, their neural weights. I want to poke and prod to see what's behind those series of numbers like [.888271829 1.10999292992 37.999999921 1000.32 .73] . Right now, it's shove data in exhaustively and hope for the best. I don't particularly care for that way of analysis.
Re: Welcoming Our New Robotic Overlords
#10Earlier quoted context omitted.
Yes they will allow for a degree of inefficiency if it removes human factor. The reasoning will go, yes we are losing $1 on every automated transaction, but we can make more of them, and we certainly avert one $10,000 corruption case and one $100,000 case where we get sued for human decision. You can't sue machine learning algorighm (that how it would go). But human, you can, even frivolously.
Yes but you can sue the company that owns the machine learning algorithm, probably for much more money than you can sue an individual. You can even imagine class action law suites and the like. (I am one of the researchers mentioned in the article.)
You can also have paper trail documenting that you never did anything illicit during the development of the model.
There will be protocols for sensitive areas.
Can't do the same with individual decision making.