Yesterday, as I was standing in line in my campus bookstore, I heard someone on the radio talk about a new study published in the Proceedings of the National Academy of Sciences (PNAS) showing that a computer algorithm, relying only on the things you “Like” on Facebook, makes more accurate judgments of your personality than your friends. If you also heard about this study, you probably did not react the way I did yesterday. Having been a reviewer on this study, I had already read the paper. So my reaction was, “Yeah, the study did show that, but it isn’t as simple as this report makes it sound.”
So what does the study show? I personally was intrigued by three things.
1) Clearly there is a sexy news story in saying that computers make better judgments than humans. And that is precisely how this study has been discussed so far. However, the data show that self-other agreement with human judges was about r = .49 (across all Big 5 traits) while self-other agreement with computer-based judgments was about r = .56. Yes, these differences are statistically significant and NO we shouldn’t care that they are statistically significant. What these effectively mean is that if you judge yourself to be above average (median) on a trait, your friends are likely to guess that you are above average 74.5% of the time, while the computer algorithm guesses correctly 78% of the time. This is a real difference, so I don’t want to downplay it, but it is important not to oversell it either.
2) To me, and I noted this in my review, one of the most interesting findings from this paper was the fact that both computer-based personality judgments from Facebook Likes *AND* peer judgments of personality predicted self-reports of personality largely independently of each other. This is discussed on p. 3 of the paper in the first full paragraph under (the beautiful looking) Figure 2. You can also see the results for yourself in Supplemental Table 2 here. Average self-other agreement with human judgments was r = .42 when controlling for computer judgments. Likewise, average self-other agreement with computer judgments was r = .38 when controlling for human judgments. Both the computer algorithm and human judgments have substantial and unique contributions to self-other agreement. That is pretty cool if you ask me.
3) Although the paper and the reports make it sound as if computers have some sort of knowledge that we do not, this is of course not true. The computer-based algorithm for making personality judgments is based entirely on the person’s behavior. That is, “Liking” something on Facebook is a behavior. The computer is taking the sum total of those behaviors into account and using them as a basis for “judgment.” And these behaviors came from the person whose personality is being judged. Thus, one could argue that the computer judgments are merely linking self-reports of behavior or preferences (e.g., I like Starbucks) with self-reports of personality.
I don’t mean to downplay the study here. I thought it was a really interesting and well-conducted study when I reviewed it, and I still do. The study combines a large sample, multiple methodologies, and sophisticated (but appropriate) analytic techniques to examine something really interesting. In those respects, this study is a model for how many of us should be doing psychological research.
 All I did was Google “computers are better than humans” and those were the top three stories to appear. I’m told there are many more.
Note: Thanks to David Funder and Simine Vazire for prior comments on this post.