[dikaiosune]

Because I'm lazy and switching would be time consuming. Each new privacy-related "innovation" motivates me a little more. You're right that the practical effect of this new service is negligible on a technical level, but it still reminds me that I should find an alternative I find acceptable.

[TeMPOraL]

So basically, because pretty much every useful data-and-automation-based thing - especially on the social, not individual level - can be considered an erosion of privacy, should we just stop progress? That's the sentiment I feel radiating from yours and others' complaints about privacy here.

[dikaiosune]

Certainly not. I quite enjoy the features I get from having my data run through a lot of systems. However, you don't need to be a Luddite to recognize that sometimes some users of data (like sometimes Google) aren't as responsible or considerate of the privacy implications of their actions as they should be.

When their primary financial incentive is user engagement to sell ads, I have a hard time believing that the latter doesn't influence the use of my data as much as the former.

I still use a variety of Google products all the time, but when they're training machines to understand the meaning of my emails, I begin to think perhaps that's beyond my comfort zone. I think that machine learning has tremendous things to offer society, but I'm not sure I'm super excited about a company using smartish machines to pull meaning and context from my emails so that we can save some percentage of users 10 seconds when they reply to something. I get that in most cases this isn't ever going to have a practical effect, but I would be a lot more comfortable if our society's data stewards were less blase about that side of things.

[TeMPOraL]

I see your point better now, thanks for clarifying.

> When their primary financial incentive is user engagement to sell ads, I have a hard time believing that the latter doesn't influence the use of my data as much as the former.

I don't agree with it in case of Google. I may be mistaken, but my impression was that they sort of separate their products into two groups - the ad-related are earning the money, and then the money is spent on funding something else (like GMail), with little direct connection between the two groups. That is, products like GMail certainly help Google earn more money on ads, but are not themselves optimized for ad-related purposes.

> I think that machine learning has tremendous things to offer society, but I'm not sure I'm super excited about a company using smartish machines to pull meaning and context from my emails so that we can save some percentage of users 10 seconds when they reply to something.

I think you're seriously underestimating the potential for productivity gains here. Mobile use case is perfect for replying to e-mails, but mobile experience totally sucks. This service, if it works as advertised, will be probably saving not 10 seconds, but something like one minute per e-mail. That + friction reduction have enabling properties that make people do things they didn't before (e.g. I often don't reply to e-mails on a phone only because it's too slow, opting to browse Facebook instead), and aggregated that can help liberate a lot of time.

[microtonal]

should we just stop progress?

I would love if companies would explore on-device processing more. While it might not work in this case, it should work fine for e.g. data extraction for flight tracking, hotel bookings, package tracking, etc.

[TeMPOraL]

Oh yes, so much this. The cloud business model thing leads to not just privacy-eroding solutions, but to implementations that are absolutely ridiculous from the engineering point of view, and exist only because the company thought it's a good way to extracting rent from the user. See, for instance, most of the work done around IoT, home automation and by hardware startups.