Learn more about Russian war crimes in Ukraine.

Old people conference

Who should speak at QCon 2015?

How should speakers be picked for conferences?

My initial reaction was to use subjective criteria: have I seen them on YouTube? do I find them convincing? do I like the stuff they’ve done? do my friends name-drop them?

During this mental search I realized something: nearly all the good speakers are old. They are not the thirty-something upstarts from startups. They are the seventy-something giants who have been doing this for decades. Immediate corollary: many of the good speakers will soon be dead. These octogenarians, giants still working away in the field that they created, will soon never talk again. Suddenly my subjective criteria became insignificant compared to an obvious two-axis way to rate potential speakers:

  1. life expectancy.
  2. influence on computer science.

If we can quantify both of these, we can draw a scatter plot in which the most desirable speakers are in one corner. First off we need a list of candidates. For that we can use Wikipedia, and find all people in the ‘Computer scientists’ category. The SPARQL endpoint on Dbpedia allows this. We of course restrict the candidates to ones that are still living.

To quantify life expectancy we can use the candidate’s age and sex, and look it up in a ‘life table’. Here’s a recent life table from the Social Security Administration which says, for example, that males aged 80 today are expected to live another 8.1 years. Dbpedia also records candidates’ birth date which we can use to get their age. To quantify influence on computer science -  we’ve already restricted to computer scientists, so we just need to quantify influence in general.

As assets, humans follow a strange depreciation pattern: they get progressively more valuable with age, and then they suddenly die.

For a list of candidates along with their age, we can use Dbpedia. It has a SPARQL endpoint that we can query.

select distinct ?person, ?birthDate where {
  ?person a dbpedia-owl:Person.
  ?subcategory skos:broader?/skos:broader?/skos:broader category:Computer_scientists.
  ?person dcterms:subject ?subcategory.
  ?person dbpedia-owl:birthDate ?birthDate.
  optional { ?person dbpedia-owl:deathDate ?deathDate }.
  filter(!bound(?deathDate)).
}
order by ?birthDate

(I tried to use SPARQL to get the sex of the returned people, but the dbpedia-owl:sex property doesn’t work.)

(This was originally planned back in 2015.)

https://docs.google.com/spreadsheets/d/1FGwhT4P5QsmEStopM3NY1RG-j9vO7qFSVdmQqsd-buw/edit?usp=sharing

What can computers do? What are the limits of mathematics? And just how busy can a busy beaver be? This year, I’m writing Busy Beavers, a unique interactive book on computability theory. You and I will take a practical and modern approach to answering these questions — or at least learning why some questions are unanswerable!

It’s only $19, and you can get 50% off if you find the discount code ... Not quite. Hackers use the console!

After months of secret toil, I and Andrew Carr released Everyday Data Science, a unique interactive online course! You’ll make the perfect glass of lemonade using Thompson sampling. You’ll lose weight with differential equations. And you might just qualify for the Olympics with a bit of statistics!

It’s $29, but you can get 50% off if you find the discount code ... Not quite. Hackers use the console!

More by Jim

Tagged . All content copyright James Fisher 2019. This post is not associated with my employer. Found an error? Edit this page.