Kate Crawford 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.

Machine learning is looking for patterns in data. If you start with racist data, you will end up with even more racist models. This is a real problem.

People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.

Hidden biases in both the collection and analysis stages present considerable risks and are as important to the big-data equation as the numbers themselves.

Algorithms learn by being fed certain images, often chosen by engineers, and the system builds a model of the world based on those images. If a system is trained on photos of people who are overwhelmingly white, it will have a harder time recognizing nonwhite faces.

Machines are neither Republicans nor Democrats and therefore can never be consciously or even unconsciously biased.

We get better search results and we see more appropriate advertising when we let Google know who we are.

What all of us have to do is to make sure we are using AI in a way that is for the benefit of humanity, not to the detriment of humanity.

I think the first wave of deep learning progress was mainly big companies with a ton of data training very large neural networks, right? So if you want to build a speech recognition system, train it on 100,000 hours of data.

I could do a whole talk on the question of is AI dangerous.' My response is that AI is not going to exterminate us. It's a tool that's going to empower us.

AIs are only as good as the data they are trained on. And while many of the tech giants working on AI, like Google and Facebook, have open-sourced some of their algorithms, they hold back most of their data.

Only by developing a deeper understanding of AI systems as they act in the world can we ensure that this new infrastructure never turns toxic.

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

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.

Sexism, racism, and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many 'intelligent' systems that shape how we are categorized and advertised to.

I would argue that racism, for example, is a feature of machine learning - it's not a bug.

Except for Wikipedia, maybe, no independent website has provided as much raw training data for as many AI firms, authorized or not, as Reddit. As a corpus for machines trying to sound or reason like people, it’s immensely valuable: pre-organized, pre-moderated, cleaned and sorted by the input of millions of volunteers and users, and written, unlike so much else on the web, without SEO, traffic, or advertisers in mind. Likewise, its relationship with OpenAI runs deeper than the deal announced in early 2024 through which Reddit licensed data to OpenAI for training and to bring Reddit content directly into ChatGPT.

As we continue to apply AI to new fields, ethical dilemmas will arise and the answers will not be clearly defined.

The challenge for what everybody's seeing in deep learning - the software richness is really quite high. In training, you have to wait days and weeks before it comes back to tell you whether your model works or not. And in the beginning, they all don't work.

Once your computer is pretending to be a neural net, you get it to be able to do a particular task by just showing it a whole lot of examples.

We need to build EQ in our AI systems because, otherwise, they're not going to be as effective as they were designed to be.

It's challenging to drive in a way that's human-like.

I often tell my students not to be misled by the name 'artificial intelligence' - there is nothing artificial about it. AI is made by humans, intended to behave by humans, and, ultimately, to impact humans' lives and human society.

After an afternoon of interviewing Siri it turns out there are millions of questions that it can't or won't answer: How did you get my phone number? How many Siris are there? Did you have a Christmas party? Who is playing the tiny xylophone before and after each interaction? Are you spying on us, plotting the downfall of our species?

The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.