Facebook Algorithms: Doing What Users Expect Maybe
August 9, 2016
I read an AOL-Yahoo post titled “Inside Facebook Algorithms.” With the excitement of algorithms tingeing the air, explanations of smart software make the day so much better.
I learned:
if you understand the rules, you can play them by doing the same thing over and over again
Good point. But how many Facebook users are sufficiently attentive to correlate a particular action with an outcome which may not be visible to the user?
Censorship confusing? It doesn’t need to be. I learned:
Mr. Abbasi [a person whose Facebook post was censored] used several words which would likely flag his post as hate speech, which is against Facebook’s community guidelines. It is also possible that the number of the words flagged would rank it on a scale of “possibly offensive” to “inciting violence”, and the moderators reviewing these posts would allocate most of their resources to posts closer to the former, and automatically delete those in the latter category. So far, this tool continues to work as intended.
There is nothing like a word look up list containing words which will result in censorship. We love word lists. Non public words lists are not much fun for some.
Now what about algorithms? The examples in the write up are standard procedures for performing brute force actions. Algorithms, as presented in the AOL Yahoo article, seem to be collections of arbitrary rules. Straightforward for those who know the rules.
A “real” newspaper tackled the issue of algorithms and bias. The angle, which may be exciting to some, is “racism.” Navigate to “Is an Algorithms Any Less Racist Than a Human?” Since algorithms are often generated by humans, my hunch is that bias is indeed possible. The write up tells me:
any algorithm can – and often does – simply reproduce the biases inherent in its creator, in the data it’s using, or in society at large. For example, Google is more likely to advertise executive-level salaried positions to search engine users if it thinks the user is male, according to a Carnegie Mellon study. While Harvard researchers found that ads about arrest records were much more likely to appear alongside searches for names thought to belong to a black person versus a white person.
Don’t know the inside rules? Too bad, gentle reader. Perhaps you can search for an answer using Facebook’s search systems or the Wow.com service. Better yet. Ask a person who constructs algorithms for a living.
Stephen E Arnold, August 9, 2016
Comments
-
- Subscribe to Beyond Search
Feature archive
News archive
-
