[Public Service Message] Jury Nullification: Please inform yourself about this fundamental right
First a public service message... Please inform yourself of the right of Jury Nullification. This is a fundamental right you posses as a juror, that doesn't get a lot said about it. If the law is unjust, you have the right to acquit - to say "Not Guilty" - even in the face of the defendant's violation of the letter of the law.
Image via WikipediaYou can read more about Jury Nullification here: http://www.law.umkc.edu/faculty/projects/ftrials/zenger/nullification.htmlt http://en.wikipedia.org/wiki/Jury_nullification I will not lie - exercising your right to Jury Nullification takes guts. I have never yet practiced jury nullification. In my jury duty career I have only had the guts to admit to the prosecuting attorney during jury selection that I could not find any defendant guilty of a drug offense, even if the defendant was a drug dealer (which was the nature of this trial). I was excused, and all I did was make the jury selection for this particular drug trial slightly harder to complete. I felt a little conspicuous back in the juror duty waiting room, when I returned, because the majority of people in my area are very conservative, and I don't welcome people pointing at me behind my back. But in the end, I felt not too bad, because through the whole process I was simply being completely truthful. If I was a twelfth juror, I am not sure I would have the guts to be the lone holdout and have the whol
Image via Wikipediae weight of the trial proceedings on my shoulders. So, what I did was a compromise, by being truthful to the prosecuting attorney during jury selection. But no matter what your personal values, it is important to not throw away your right to Jury Nullification, without some consideration first. After consideration, you can proceed as you see fit. OK, done with the public service message...
The book I would take if I had jury duty today would be Judea Pearl's _Causality: Models, Reasoning, and Inference_, because I have to review the book again (and review the notes I wrote in the margins in my own copy). It is a very difficult book - I was only able to read about six pages a day. The book is about Causality -- effect following cause. We take the concept for granted, but it has been on shaky ground since David Hume in the 18th century. But now, because of researchers like Judea Pearl, it is on solid footing. Here is the 5 minute summary: Write down all the possible causes and effects on a piece of paper - we will call these "points". Draw arrows from things you think are direct causes to the things you think are direct effects. Now you will have a bunch of "points" and "arrows" between those points. Look for loops - search for any "loops" that can be made by tracing your finger from point to point, always tracing your finger from arrow tail to arrow head. Are there zero loops? If so - good! - you have a description of causality, and you can use this diagram to understand the casual effects and interactions. Now, how can you tell if your diagram is, in fact, representative of the real world? Well, on the points of the graph, there is a "DO operation" linked with a manipulation you can do in the real world. Manipulations can be like fixing different variables in a scientific experiment, or like making a careful experiment that isolates the object of interest from anything that might mess things up. Consider these points: (A) Lawn Sprinkler near sidewalk; (B) Rain cloud over sidewalk; (C) wetness of sidewalk; (D) slipperiness of sidewalk; (E) number of people falling on slippery sidewalk Consider these arrows: (A -> C); (B -> C); (C -> D -> E) Draw it, run finger over graph, cannot find any loops - good! - ready to begin. We will try the DO operation on (C). On the graph, I just set "wetness" to "very wet" or "very dry" or whatever, and make a prediction. In the real world, I can either water down the sidewalk with a garden hose, or shield the sidewalk from the sprinklers with a tarp and shield from rain with a canopy and dry the sidewalk with a towel then a hairdryer. If the predictions match between the graph and number of people falling on the slippery sidewalk, I feel good that I have a graph representative of the real world. (This is a dumb example, because humans can handle the casual analysis of this situation with no problem. It only gets interesting as the graph gets more complicated.) Check the book out of your nearest university library (there is a 2nd edition coming out soon, but I wouldn't worry about it - no major revisions). Read only the last chapter, which is the text and slides from an informal lecture Judea Pearl gave. It is enough. The rest of the book is very difficult, or at least it was for me. I will probably have to read it two or three more times, on top of already reading it once carefully, to fully understand everything developed. My copy is heavily marked up, and I think I made a lot of mistakes, because I needed to think through it all more. So you probably don't want to borrow my marked up copy (not that I would actually lend it to you - the guy who lends out my books is sick today :P )