we hear a lot hot air about data is the new oil - implying there's a rush of innovation and profits as with a gold rush (there's money in them there data hills etc)-
this is so baly broken a metaphor, we need to unpick (deconstruct) it further
1. data is free to copy (nearly), i.e. data is in some sense renewable, while oil gets used up (its nearly 50% gone now).
2. using oil does as much harm (or possibly more) as good
3. using data can do harm or good
4. AI/ML is compute intensive- deep learning in particular is massively inefficient, and data centers (like power stations, in close proximity to which they are sometimes built) burn %ages of globally generated electricity - not always renewable energy
5. data can increase in value as you have more of it, up to some point (sampling more about a population of people or things)
6. privacy could be modelled as efficiency (what's relevant/pertinent and what is none-of-your-business) in space and time (why do you still want to know that out-of-date thing about me or about that?).
7. much personal data collected by cloud providers is treated as if free, though some lawyers now are starting to point out that if you have a business model based on this, it is possibly a form of payment - so while facebook/zuckerberg might claim we are the product, if this legal position is true, we are customers, and he's working for us....
8. this mission creep really implies data could be the new fur (or indeed as john naughton has said, the new tobacco)
9. the models (e.g. face recognition, recommender networks etc) are often surprisingly bad - occasional successes of GANs&deep learning are relatively rare compared with a plethora of rather shoddy systems&applications.
10. perhaps data is the new oil after all, but its rapeseed or snake oil that would be a more precise metaphor.
this is so baly broken a metaphor, we need to unpick (deconstruct) it further
1. data is free to copy (nearly), i.e. data is in some sense renewable, while oil gets used up (its nearly 50% gone now).
2. using oil does as much harm (or possibly more) as good
3. using data can do harm or good
4. AI/ML is compute intensive- deep learning in particular is massively inefficient, and data centers (like power stations, in close proximity to which they are sometimes built) burn %ages of globally generated electricity - not always renewable energy
5. data can increase in value as you have more of it, up to some point (sampling more about a population of people or things)
6. privacy could be modelled as efficiency (what's relevant/pertinent and what is none-of-your-business) in space and time (why do you still want to know that out-of-date thing about me or about that?).
7. much personal data collected by cloud providers is treated as if free, though some lawyers now are starting to point out that if you have a business model based on this, it is possibly a form of payment - so while facebook/zuckerberg might claim we are the product, if this legal position is true, we are customers, and he's working for us....
8. this mission creep really implies data could be the new fur (or indeed as john naughton has said, the new tobacco)
9. the models (e.g. face recognition, recommender networks etc) are often surprisingly bad - occasional successes of GANs&deep learning are relatively rare compared with a plethora of rather shoddy systems&applications.
10. perhaps data is the new oil after all, but its rapeseed or snake oil that would be a more precise metaphor.
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