Fred Ehrsam Quotes

Artificial intelligence is just a new tool, one that can be used for good and for bad purposes and one that comes with new dangers and downsides as well. We know already that although machine learning has huge potential, data sets with ingrained biases will produce biased results - garbage in, garbage out.

Apple knows a lot of data. Facebook knows a lot of data. Amazon knows a lot of data. Microsoft used to, and still does with some people, but in the newer world, Microsoft knows less and less about me. Xbox still knows a lot about people who play games. But those are the big five, I guess.

The people who are thinking most about big data right now are corporations and governments.

You can't talk about big data without talking about things like privacy and ownership.

Google's screen for privacy settings does give you more options for what you share than Apple's does. But it's not a complete list, and people aren't aware of whether or not that information will go to a third party.

Facebook mistreats its users. Facebook is not your friend; it is a surveillance engine. For instance, if you browse the Web and you see a 'like' button in some page or some other site that has been displayed from Facebook. Therefore, Facebook knows that your machine visited that page.

Facebook's privacy policies are confusing to many people, and the company has changed them frequently, almost always allowing more information to be exposed in more ways.

I clearly say yes to Big Data, yes to greater security and convenience, but no to paternalism and Big Brother.'

Apple and Google want to create encryption for which they could not provide you the key. Their business model will not survive if the American government has a special relationship with them that requires them to surrender this kind of information.

Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.

I believe in the power of shared data and technology to help build a better future.

In a world of shared data services, where you have third-party networks selling ads on your behalf and displaying them in real time to your users, it's very difficult for you to control everything.

Data is valuable, so let's be mindful of how we're sharing it.

Facebook and Google are essentially an advertising duopoly, and we have almost no idea how their algorithms work.

As medical data has such power to deliver better understanding of disease and better patient outcomes, it is important we find the best way of sharing it.

People should have to opt in for any kind of data sharing, and they should know what the data is being used for.

Everything is changing now that we are in the cloud in terms of sharing our data, understanding our data using new techniques like machine learning.

AIs are only as good as the data they are trained on.

I was very taken aback and disappointed in Sheryl Sandberg's public statement that if an individual did not want to continue to share their data with FB they would have to pay. To me, that sounds like a threat. Continue to let us use your property or pay?

And I think the greatest danger that AI poses isn't so much these anthropomorphic beings who look like us and are beguiling are going to fool us. It's the fact that a intelligence without a body or corporeal form will fool us into trusting it with data, which we seem to think is... it has no repercussions.

I worry about Google's data ethics and about the idea of handing over the corpus of my life, but I can't deny that it is exceptional at making sense of my ever-growing photo library.

Sharing data allows us to research, communicate, consume media, buy and sell, play games, and more. In return, businesses develop products, scientists undertake research, and governments use data to enable voting, inform policies, collect tax, and provide better public services.

We need a sweeping debate about ethics, boundaries, and regulation for location data technologies.

Our view is that sensitive, contractual, market-moving, private data should be kept private.

We should always be suspicious when machine-learning systems are described as free from bias if it's been trained on human-generated data. Our biases are built into that training data.