A lot of people share private details with the world without being aware of it. For example, they take nude pictures with their phones (NSA keeps a copy, just in case) or they sell the phone without wiping it properly, allowing the next owner to get a good idea who you are, or they install apps like the one from Facebook which ask “can I do whatever I want with anything I find on your phone?” and people happily click the “Yeah, whatever” button (a.k.a “Accept”).
When people use modern technology, they have a mental model. That model tells them what to expect when they do something (“press here and the screen will turn on”). It also contains other expectations that are rooted in social behavior. Like “I take good care of my phone and it will take good care of me (and my data)”.
That, when you think about it, is nonsense.
A phone is not a butler. In essence, a phone is a personal data collecting device with additional communication capabilities. But the main goal is to learn about you and then manipulate you to buy stuff. It’s about money. Companies want it, you have it, they want you to give it to them. Anything else only exists to facilitate this process. If pain would increase revenue, we’d be living in hell.
Case in point: Speech based input. When you click on a page, that doesn’t tell much about you. When you use your finger, the phone can at least feel when you’re trembling. Are you angry or enthusiastic? We’re getting there. But your voice is rich with detail about your emotional state. More data to milk to make you perfect offers which you simply don’t want to refuse.
A butler, on the other hand, has your interests in mind. They keep private information private instead of selling it to the highest bidder. They look out for you.
The source of the difference? You pay a butler. (S)he is literally working for you. On the phone, a lot of people expect the same service to happen magically and for free. Wrong planet, pals.
Wouldn’t it be great if phones were like butlers? Trustworthy, discreet and helpful instead of just trying to be helpful?
I hope we’ll see more technology like the app Nude (which hides sensitive photos on your phone).
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Posted by digulla 
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Artificial Ethics
24. October, 2017While watching this video, I wondered: We’re using machine learning to earn money on the stock market and to make computers understand speech. Why not ethics?
Around @26:00 , Isaac talks about ways to develop AIs to control androids. He would like to use the safe approach of manual programming all the specific details to create an AI.
The “manual programming” path has been tried since 1960 and it’s now deemed a failure. The task is simply too complex. It’s like manually writing down all possible chess positions: Even if you tried, you’d run out of time. Machine learning is the way to go.
Which means we have to solve a “simple” problem: Encode the rules of ethics. That is, a machine learning algorithm must check itself (or be checked by another algorithm) against a basic set of ethical rules to determine whether “a solution” to “a problem” is “ethical” (quotes mean: “We still have to figure out exactly what that means and how to put it into code”).
Just like intelligence, ethics is somewhat of a soft and moving target. Fortunately, we have a huge body of texts (religious, laws, philosophy, polls) which a machine learning algorithm could be trained on. To test this machine, we could present it with artificial and real life incidents and see how it rules. Note: The output of this algorithm would be a number between 0 (very unethical) and 1 (very ethical). It would not spit out solutions on how to solve an ethical dilemma. It could just judge an existing solution.
It’s important that the output (judgement) is checked and the result (how good the output was) is fed back into the algorithm so it can tune itself. Both output and feedback needs to be checked for the usual problems (racism, prejudice, etc.).
Based on that, another machine learning algorithm (MLA) could then try many different solutions, present those to the ethics one, and pick the best ones. At the beginning, humans would supervise this process as well (feedback as above). Eventually, the MLA would figure out the hidden rules of good solutions.
That would eventually lead to ethical machines. Which would cause new problems: There will eventually be a machine, very impartial, that “is” more ethical than almost all humans. Whatever “is” might mean, then.
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