<story><title>How Cambridge Analytica’s Facebook targeting model really worked</title><url>http://www.niemanlab.org/2018/03/this-is-how-cambridge-analyticas-facebook-targeting-model-really-worked-according-to-the-person-who-built-it/</url></story><parent_chain><item><author>etiam</author><text>Spoiler warning. Article punchline ahead.&lt;p&gt;&amp;quot;The whole point of a dimension reduction model is to mathematically represent the data in simpler form. It’s as if Cambridge Analytica took a very high-resolution photograph, resized it to be smaller, and then deleted the original. The photo still exists — and as long as Cambridge Analytica’s models exist, the data effectively does too.&amp;quot;&lt;p&gt;That&amp;#x27;s an eloquent piece of explanation of a very important point.
And apropos the discussion about privacy legislation, it&amp;#x27;s also going to be a very interesting point. Will the Cambridge Analyticas of the world be able to claim they have held on to no personal data, when strictly speaking the raw data has indeed been deleted after being used to create a derivative work that can for all important purposes be used to recreate the original?
Assuming I find out I&amp;#x27;m being profiled and demand to have my data removed, will society grant me rights to have derivative forms removed or adjusted too?
I&amp;#x27;m somewhat pessimistic that legal hairsplitting about matters like these will make enforcement very difficult.</text></item></parent_chain><comment><author>darawk</author><text>&amp;gt; when strictly speaking the raw data has indeed been deleted after being used to create a derivative work that can for all important purposes be used to recreate the original?&lt;p&gt;To be precise, you almost certainly cannot use this data to recreate anything remotely resembling the original dataset. This type of dimensionality reduction would throw away enormous volumes of data. There is no meaningful sense in which you can reconstruct the data from it.&lt;p&gt;What they have done is distill some insights about people from this data. It&amp;#x27;s arguable whether they should be allowed to keep those insights, but there&amp;#x27;s no privacy risk there really.&lt;p&gt;It&amp;#x27;s honestly kind of disingenuous to describe dimensionality reduction in the way that they do here. It &lt;i&gt;is&lt;/i&gt; like reducing the resolution of a photo, but it&amp;#x27;d best be described as reducing that resolution to say, the 20 most representative pixels. There&amp;#x27;s no real sense in which the photo still exists.</text></comment>
<story><title>How Cambridge Analytica’s Facebook targeting model really worked</title><url>http://www.niemanlab.org/2018/03/this-is-how-cambridge-analyticas-facebook-targeting-model-really-worked-according-to-the-person-who-built-it/</url></story><parent_chain><item><author>etiam</author><text>Spoiler warning. Article punchline ahead.&lt;p&gt;&amp;quot;The whole point of a dimension reduction model is to mathematically represent the data in simpler form. It’s as if Cambridge Analytica took a very high-resolution photograph, resized it to be smaller, and then deleted the original. The photo still exists — and as long as Cambridge Analytica’s models exist, the data effectively does too.&amp;quot;&lt;p&gt;That&amp;#x27;s an eloquent piece of explanation of a very important point.
And apropos the discussion about privacy legislation, it&amp;#x27;s also going to be a very interesting point. Will the Cambridge Analyticas of the world be able to claim they have held on to no personal data, when strictly speaking the raw data has indeed been deleted after being used to create a derivative work that can for all important purposes be used to recreate the original?
Assuming I find out I&amp;#x27;m being profiled and demand to have my data removed, will society grant me rights to have derivative forms removed or adjusted too?
I&amp;#x27;m somewhat pessimistic that legal hairsplitting about matters like these will make enforcement very difficult.</text></item></parent_chain><comment><author>salty_biscuits</author><text>I guess the question is what are you trying to protect? The model is fundamentally lossy as it is a rank reduction method so your original data is gone (i.e. no one would be able to accuse you of liking a particular controversial post, just that you are likely to like that post). So it sort of has the differential privacy thing going on. I guess it is another question as to if such models should be built at all. I think the fidelity of the models will answer that in time, if they work really well it is scary, if they are poor models they will cease to be used. I suspect that it will be in the middle and highly sensitive to the quality of the original data and the quality of the implementation like all ml applications.</text></comment>