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> For the privacy advocates when it comes to public transportation like flying: what do you fear may happen as a result of greater background checks? False pos

by drcube 13y ago

> For the privacy advocates when it comes to public transportation like flying: what do you fear may happen as a result of greater background checks? False positives, increased harassment/inconveniece of innocent people, chilling effects, driving people away from airlines towards other, less efficient means of long distance travel, even as airlines are struggling to stay in business. TSA becoming more powerful, free citizens becoming desensitized to privacy invasions, increased rape-scans, crotch fondling, etc. Generally, it makes our country a worse place to travel to/from/within. And what are the benefits, again? Because I'm not seeing any, and that is the question you should be asking, not simply "what's the harm?".

EGreg 13y ago
I would argue that there are MORE false positives when you don't have enough information. After all, mathematically speaking let's say you sample X things versus X + Y things. Assuming there to be a similar probability distribution for the decision making (same first moments at least), a greater sample size would lead to greater accuracy and therefore less false positives, as well as less false negatives.
- hdevalence 13y ago
  You should consider applying Bayes' rule here. For reference, there are 800 million airline passengers in the US every year. Good luck.
  - EGreg 13y ago
    ?
    - minor_nitwit 13y ago
      Ex. You have a test that detects cancer with 99% certainty, and a prevalence of cancer of 1 in 1 million people. In a sample size of 100 million people: People with cancer correctly identified: 99%*100=99 people People with cancer not identified: 1%*100=1 person People without cancer falsely identified= 1%*99,999,900 = 999,999 people People without cancer correctly identified:99%*99,999,900=98,999,901 people Even with 99% accuracy you have nearly a million people falsely identified, but only identify 99 people with cancer. Now extend this to terrorism, 800 million riders for 12 years, and a prevalence of 2? possible terrorists (shoe, underwear) in the last 12 years. Also keep in mind that since both of these guys made it on the plane, the accuracy of the the terrorist screening process may not be too high.

by drcube 13y ago

EGreg 13y ago

I would argue that there are MORE false positives when you don't have enough information. After all, mathematically speaking let's say you sample X things versus X + Y things. Assuming there to be a similar probability distribution for the decision making (same first moments at least), a greater sample size would lead to greater accuracy and therefore less false positives, as well as less false negatives.

hdevalence 13y ago
You should consider applying Bayes' rule here. For reference, there are 800 million airline passengers in the US every year. Good luck.
- EGreg 13y ago
  ?
  - minor_nitwit 13y ago
    Ex. You have a test that detects cancer with 99% certainty, and a prevalence of cancer of 1 in 1 million people. In a sample size of 100 million people: People with cancer correctly identified: 99%*100=99 people People with cancer not identified: 1%*100=1 person People without cancer falsely identified= 1%*99,999,900 = 999,999 people People without cancer correctly identified:99%*99,999,900=98,999,901 people Even with 99% accuracy you have nearly a million people falsely identified, but only identify 99 people with cancer. Now extend this to terrorism, 800 million riders for 12 years, and a prevalence of 2? possible terrorists (shoe, underwear) in the last 12 years. Also keep in mind that since both of these guys made it on the plane, the accuracy of the the terrorist screening process may not be too high.