Off-topic: this same idea has been cropping up a lot on HN recently with respect to salaries when moving to lower CoL areas. The argument on one side is that their work hasn't become less useful, and on the other side we hear that with a lower CoL you need the money less, and we have a bit of a holy war going on trying to describe why one side or the other has some moral claim to the entirety of that surplus.
I understand this article. I still want to see a penny every time my data is used/accessed/sold/etc, if anything to drive up the cost of contracts around or servicing of my data. If my data is made functionally anonymous then make it a dime payment and then a penny every time that block of data is used sold. Send it as a check to my mailing address with a letter including the legal entities involved, initial source of the data, what type or category of data they have relating to me (like PII category ex address, name, purchase history, etc), their intended use for the data (research vs marketing), and how I can contact to have my data removed from the set. Also if my data is made anonymous, provide a 1 penny check and above information for any use or sale of the data set.
Yes this regulation would kill the industry in overhead costs aimed at making the information somewhat close to the 'informed consent' required for medical approvals and breaking down how the industry works. Maybe make it so on initial sale and usage you get a check then at the start of each following year that entity pays out for annual usage.
Our data is valuable collectively to identify trends, markets, and opportunity and I'd like to know how I'm manipulated into being a part of that as well as what entities I cannot trust with any personal data. And I think this should apply to Experian/etc too. Chase wants to find out my credit score to market CC reward offers to me? Make it known and pay me the same way farms are paid for the useful manure their animals produce.
Now let's do a little thought-experiment with the Uber ride and look at the information you and Uber have to make your price and choice on:
For Uber:
- What time is it? +
- Are you far away from home? +
- Have you been here before? -
- What have you paid before? +
- Where do you shop usually? +
- Are you rich? ++
- Are you ill? +
- Are you pregnant? +
- Are you drunk? ++
- Are you very drunk? +++ (bonus!)
- Are you sad? +
- Did you just break up? ++
- Do you have any friends? +/-
- Do you have any friends with cars? -
- Are you alone? +
- Are you going home? +
- Are you already home? -
- probably a lot more...
For you:
- Price?
- How screwed am I if I don't take the ride?
There are not many other options. Maybe a taxi's while they last and Lyft probably has the same algorithm.
Upside? Plausible deniability! An NN AI that happens to score based on age, gender, gender preference, religion, disability status, and ethnicity, but buried among other factors and not explicitly exposed? Perfectly fine! (At least until you can hire stats PhDs to prove statistically significant bias.)
Bad news? The engineers have no idea why (or when) the model gives bad results. It's answers without insight.
The seller is a company. Its only purpose is to satisfy its customers' needs.