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152

Data: The Raw Material of the Information Age

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language translations getting better due to exponential growth in data. he's not wrong here, though he overreaches ... he mentions on p160 that Papua New Guinea has great natural resources, but 850 languages, which scares off foreign investors, and implies that better translation software will overcome those barriers? first of all, foreign investors can fuck right off, and second of all, idk where i was going with this but his argument is pretty gross

mentions that Alex Karp, one of the founders of Palantir, studied under Habermas ... wtf happened to him

J. Ross, A. (2016). Data: The Raw Material of the Information Age. In J. Ross, A. The Industries of the Future. Simon Schuster, pp. 152-185

165

Precision agriculture will not end hunger in India or turn its subsistence-level farmers into serious agribusinesses, but in an environment of scarcity, it can take those scarce resources, be they seed, fertilizer, or water, and get the most out of them. India does not have a national network of agronomist to provide expertise and resources to its country's farmers as China, the Americas, and Europe do. The budgetary resources in India are spread too thin. [...]

I mean, more efficient agriculture is not a bad idea, but the current problem we're facing is not efficiency, it's d i s t r i b u t i o n

—p.165 by Alec J. Ross 3 years, 2 months ago

Precision agriculture will not end hunger in India or turn its subsistence-level farmers into serious agribusinesses, but in an environment of scarcity, it can take those scarce resources, be they seed, fertilizer, or water, and get the most out of them. India does not have a national network of agronomist to provide expertise and resources to its country's farmers as China, the Americas, and Europe do. The budgetary resources in India are spread too thin. [...]

I mean, more efficient agriculture is not a bad idea, but the current problem we're facing is not efficiency, it's d i s t r i b u t i o n

—p.165 by Alec J. Ross 3 years, 2 months ago

in a way that cannot be removed or forgotten

174

digital data is practically indelible

—p.174 by Alec J. Ross
notable
3 years, 2 months ago

digital data is practically indelible

—p.174 by Alec J. Ross
notable
3 years, 2 months ago
181

Serendipity fades with everything we hand over to algorithms. Most of these algorithms are noiseless. They gently guide us in our choices. But we don't know why we are being guided in certain directions or how these algorithms work. And because they constitute the value of a company's intellectual property, there is an incentive to keep them opaque to us.

this is a strong argument against intellectual property tbh

—p.181 by Alec J. Ross 3 years, 2 months ago

Serendipity fades with everything we hand over to algorithms. Most of these algorithms are noiseless. They gently guide us in our choices. But we don't know why we are being guided in certain directions or how these algorithms work. And because they constitute the value of a company's intellectual property, there is an incentive to keep them opaque to us.

this is a strong argument against intellectual property tbh

—p.181 by Alec J. Ross 3 years, 2 months ago
182

Who owns the data is as important a question as who owned the land during the agricultural age and who owned the factory during the industrial age. Data is the raw material of the information age.

—p.182 by Alec J. Ross 3 years, 2 months ago

Who owns the data is as important a question as who owned the land during the agricultural age and who owned the factory during the industrial age. Data is the raw material of the information age.

—p.182 by Alec J. Ross 3 years, 2 months ago
184

Correlations made by big data are likely to reinforce negative bias. Because big data often relies on historical data or at least the status quo, it can easily reproduce discrimination against disadvantaged racial and ethnic minorities. The propensity models used in many algorithms can bake in a bias against someone who lived in the zip code of a low-income neighborhood at any point in his or her life. If an algorithm used by human resources companies queries your social graph and positively weighs candidates with the most existing connections to a workforce, it makes it more difficult to break in in the first place. In effect, these algorithms can hide bias behind a curtain of code.

[...] it is largely unregulated because we need it for economic growth and because efforts to try and regulate it have tended not to work; the technologies are too far-reaching and are not built to recognize the national boundaries of our world's 196 nation-states.

Yet would it be best to try to shut down these technologies entirely if we could? No. Big data simultaneously helps helps solve global challenges while creating an entirely new set of challenges. [...]

he's falling into the same trap that Evgeny Morozov describes people falling into re: the Internet: thinking of it as this one amorphous thing. instead, we have to treat it as just another tool, and isolate the use cases

—p.184 by Alec J. Ross 3 years, 2 months ago

Correlations made by big data are likely to reinforce negative bias. Because big data often relies on historical data or at least the status quo, it can easily reproduce discrimination against disadvantaged racial and ethnic minorities. The propensity models used in many algorithms can bake in a bias against someone who lived in the zip code of a low-income neighborhood at any point in his or her life. If an algorithm used by human resources companies queries your social graph and positively weighs candidates with the most existing connections to a workforce, it makes it more difficult to break in in the first place. In effect, these algorithms can hide bias behind a curtain of code.

[...] it is largely unregulated because we need it for economic growth and because efforts to try and regulate it have tended not to work; the technologies are too far-reaching and are not built to recognize the national boundaries of our world's 196 nation-states.

Yet would it be best to try to shut down these technologies entirely if we could? No. Big data simultaneously helps helps solve global challenges while creating an entirely new set of challenges. [...]

he's falling into the same trap that Evgeny Morozov describes people falling into re: the Internet: thinking of it as this one amorphous thing. instead, we have to treat it as just another tool, and isolate the use cases

—p.184 by Alec J. Ross 3 years, 2 months ago
185

The choices we make about how we manage data will be as important as the decisions about managing land during the agricultural age and managing industry during the industrial age. We have a short window of time--just a few years, I think--before a set of norms set in that will be nearly impossible to reverse. Let's hope humans accept the responsibility for making these decisions and don't leave it to the machines.

good

(I sound like I'm grading this or something lmao)

—p.185 by Alec J. Ross 3 years, 2 months ago

The choices we make about how we manage data will be as important as the decisions about managing land during the agricultural age and managing industry during the industrial age. We have a short window of time--just a few years, I think--before a set of norms set in that will be nearly impossible to reverse. Let's hope humans accept the responsibility for making these decisions and don't leave it to the machines.

good

(I sound like I'm grading this or something lmao)

—p.185 by Alec J. Ross 3 years, 2 months ago