Sandra Matz

It's so little, right? So I remember when my colleagues published a study, I think the average, and this is 10 years ago now, the average number of likes was 230. So back in the day, the computer was already better than everybody except for the spouse. And you can very easily project into the here and now where you have a lot more data, you have a lot more sophisticated models.

So by now, the computer is probably better than the spouse. And again, it sounds so intimate, but then if you think about the fact that a computer has access to the entirety of your digital life and some of the aspects that you're potentially trying to hide from other people you don't necessarily intend to signal, it's not as surprising.

So by now, the computer is probably better than the spouse. And again, it sounds so intimate, but then if you think about the fact that a computer has access to the entirety of your digital life and some of the aspects that you're potentially trying to hide from other people you don't necessarily intend to signal, it's not as surprising.

So by now, the computer is probably better than the spouse. And again, it sounds so intimate, but then if you think about the fact that a computer has access to the entirety of your digital life and some of the aspects that you're potentially trying to hide from other people you don't necessarily intend to signal, it's not as surprising.

So in this case, it's actually you complete a questionnaire. So you tell us, here's how I think of myself when it comes to personality. And it's all kind of asking you about behavior. So how often do you enjoy socializing? To what extent are you making a mess of your environment? And then the spouse completes the same questionnaire. So on your behalf.

So in this case, it's actually you complete a questionnaire. So you tell us, here's how I think of myself when it comes to personality. And it's all kind of asking you about behavior. So how often do you enjoy socializing? To what extent are you making a mess of your environment? And then the spouse completes the same questionnaire. So on your behalf.

So in this case, it's actually you complete a questionnaire. So you tell us, here's how I think of myself when it comes to personality. And it's all kind of asking you about behavior. So how often do you enjoy socializing? To what extent are you making a mess of your environment? And then the spouse completes the same questionnaire. So on your behalf.

So I think Jordan would answer strongly agree to the question. I make a mess of things. Not sure. Hypothetically.

So I think Jordan would answer strongly agree to the question. I make a mess of things. Not sure. Hypothetically.

So I think Jordan would answer strongly agree to the question. I make a mess of things. Not sure. Hypothetically.

And you also have a certain bias. There's like certain ways in which you want to see your spouse. So once you have a certain way of seeing them, the way that you integrate new information is just almost aligned with the perception that you have anyway. So it's much harder for humans to update just because it's in a way functional to stick with the impressions that we have.

And you also have a certain bias. There's like certain ways in which you want to see your spouse. So once you have a certain way of seeing them, the way that you integrate new information is just almost aligned with the perception that you have anyway. So it's much harder for humans to update just because it's in a way functional to stick with the impressions that we have.

And you also have a certain bias. There's like certain ways in which you want to see your spouse. So once you have a certain way of seeing them, the way that you integrate new information is just almost aligned with the perception that you have anyway. So it's much harder for humans to update just because it's in a way functional to stick with the impressions that we have.

Uh-huh. That's actually how they learn, right? So machine learning is called that way because they learn by trial and error. So the way that we train a model, for example, to predict your personality from, say, Facebook likes, is we give it a lot of data where people completed a questionnaire giving us answers of here's how I think about myself in terms of personality.

Uh-huh. That's actually how they learn, right? So machine learning is called that way because they learn by trial and error. So the way that we train a model, for example, to predict your personality from, say, Facebook likes, is we give it a lot of data where people completed a questionnaire giving us answers of here's how I think about myself in terms of personality.

Uh-huh. That's actually how they learn, right? So machine learning is called that way because they learn by trial and error. So the way that we train a model, for example, to predict your personality from, say, Facebook likes, is we give it a lot of data where people completed a questionnaire giving us answers of here's how I think about myself in terms of personality.

And then they have access to all of the likes and they just play the trial and error game. So maybe if you like the fan page of Lady Gaga, maybe that makes you more extroverted. Did I get it right or wrong?

And then they have access to all of the likes and they just play the trial and error game. So maybe if you like the fan page of Lady Gaga, maybe that makes you more extroverted. Did I get it right or wrong?

And then they have access to all of the likes and they just play the trial and error game. So maybe if you like the fan page of Lady Gaga, maybe that makes you more extroverted. Did I get it right or wrong?

got it okay i'm going to update my belief of what lady gaga actually means same for the fan page of cnn maybe that makes you more conscientious and organized and reliable so essentially you just throw a lot of data at them in the beginning they're just randomly guessing and over time they become a lot better because you give them feedback you tell them yep that was a good guess no this was a terrible guess