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IMHO, a scientist capable of striking any tone in their work, positive or negative, is doing marketing / PR work rather than science. There's nothing wrong wit

by _cs2017_ 6y ago

IMHO, a scientist capable of striking any tone in their work, positive or negative, is doing marketing / PR work rather than science. There's nothing wrong with that. Just like any other member of society, a scientist may want to contribute to a (for-profit or non-profit) organization of their choice, be it for material or spiritual rewards. However, I think it's important not to get science and marketing confused. So, I think a more precise title would be "Google told its scientists to strike a positive tone when they use academic papers as a marketing tool".

FemmeAndroid 6y ago
Any scientist writing prose will necessarily strike a tone. Unless they’re just publishing raw data, the way you use that data in your prose will lead to a different tone. I have read a good deal of historical and modern scientific papers and they all had different tones.
chaboud 6y ago
When I was young and (more) idealistic, my department chair pulled me aside after I’d been dogmatic about something and said “everything is political... The sooner you realize that, the better off you’ll be.” It took 10 years for that to really sink in, but I knew that every paper has an angle well before that. There’s a position of inevitability about AI around Google, and, to an extent, I agree. Unlike tobacco, alcohol, firearms, cars, fuel, AI is applied mathematics. It’s virtually impossible to restrict functionally, requiring macro behavioral constraints on businesses and governments that are very difficult to enforce if you want to regulate it. Furthermore, ceding the technological lead and removing the business incentive likely has defense (read: offense) implications on the global stage. Some things are going to be hard to explain. Some skin tones, hair styles, accents, pitches, timbres, writing styles, etc. may have more/less separable entropy, and that’s going to inevitably make models seem racist/sexist for some applications. However, we’re pretty far from those edges. Instead, our model biases have likely been driven by our datasets, drawn from our coworkers, family, and friends. In this industry, that’s currently a recipe for over sampling in some demographics and under sampling in others.
- _cs2017_ 6y ago
  Pick randomly a list of top papers in ML, for example https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-know.html https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-k.... Most (if not all) all of them have no "positive" or "negative" tone, as far as I can tell.
- izacus 6y ago
  The thing is - I don't think the bias in AI is fixable. The way we fix it is to regulate (not self-regulate, Google, Apple, Facebook and other AI companies aren't trustworthy to do it right) where AI is allowed to be used and how much of a negative impact of a persons livelihood can it impact. In other words, we need to use all the power we have to avoid "The computer said NO, you're homeless/jailed/poor forever now" scenarios.
  - benlivengood 6y ago
    Unfortunately a legal solution is weaker because it has to enumerate the precise conditions that are unacceptable. Do you ban the logistic function? Tanh? Statistics? Actuarial tables have been a part of decision-making for a very long time and it's not possible to form a comprehensive legal statement of "all decisions must be made in good faith with respect to inherent biases and to the most rigorous epistemological standards".
    - chaboud 6y ago
      Funny enough, Aggregability is NP-Hard, so comprehensive consideration of the larger set is not actually practical/possible. Here's the proof: http://www.cs.utep.edu/vladik/2006/tr06-29.pdf http://www.cs.utep.edu/vladik/2006/tr06-29.pdf Perhaps there are mechanisms around performance under external test, auditing, or safe harbor due to documented good-faith, but it is not possible to guarantee correctness for the full set from a subset. Similarly, some approaches will plainly fail to perform well with subgroups of people due to sensing technologies. That may appear as model bias, but it's really a matter of physics and available entropy. For the time being, mechanisms that use machine inference as an aid rather than a guide (leaving the judgment to the human in the loop) are probably the best we can hope for.
YinglingLight 6y ago
Yet Redditor's and HN'ers treat Scientists as centuries ago people treated men of the cloth. Their word is not to be scrutinized. You wouldn't want to be outed as being critical of the Scientific Method would you? (the irony between those two sentences have been lost in the last 5 years)
ritchiea 6y ago
When scientists write results sections and abstracts they strike a tone. They make an argument for why the raw data is meaningful. Scientists interpret data, which involves a layer of human analysis that is not objective but is attempting to find the correct language and narrative to describe the results of an objective, quantitative process. Outside of the methods and data sections, academic science writing absolutely has to strike a tone. And especially when you are seeking grants and career progression one of the tones you have to strike is to highlight the importance of the work. Once in a science course in college, I had to present a paper to my class. I tried to present it "objectively" as you would describe it, avoid striking a tone or making judgements. My professor told my presentation was technically correct but failed to highlight the broad significance of the research, which comes from tone. Science writing requires selecting a tone of voice.
ClumsyPilot 6y ago
'is doing marketing / PR work rather than science. There's nothing wrong with that' I like how we learned nothing from decades of lies and billions of damages in big tabacco, asbestos, lead in petrol and climate change. Whats next, can we tell aircraft safety inspectors to strike a positive tone and declare a damaged airframe flight worthy? How about rating some securities in a positive tone? Lets call it what it is, corruption
indymike 6y ago
Scientific papers often have a "research implications" or "implications" section that generally is optimistic or pessimistic depending on the results. There's nothing wrong with this, so long as the implications are not steering the results.

FemmeAndroid 6y ago

Any scientist writing prose will necessarily strike a tone. Unless they’re just publishing raw data, the way you use that data in your prose will lead to a different tone. I have read a good deal of historical and modern scientific papers and they all had different tones.

chaboud 6y ago

When I was young and (more) idealistic, my department chair pulled me aside after I’d been dogmatic about something and said “everything is political... The sooner you realize that, the better off you’ll be.” It took 10 years for that to really sink in, but I knew that every paper has an angle well before that. There’s a position of inevitability about AI around Google, and, to an extent, I agree. Unlike tobacco, alcohol, firearms, cars, fuel, AI is applied mathematics. It’s virtually impossible to restrict functionally, requiring macro behavioral constraints on businesses and governments that are very difficult to enforce if you want to regulate it. Furthermore, ceding the technological lead and removing the business incentive likely has defense (read: offense) implications on the global stage. Some things are going to be hard to explain. Some skin tones, hair styles, accents, pitches, timbres, writing styles, etc. may have more/less separable entropy, and that’s going to inevitably make models seem racist/sexist for some applications. However, we’re pretty far from those edges. Instead, our model biases have likely been driven by our datasets, drawn from our coworkers, family, and friends. In this industry, that’s currently a recipe for over sampling in some demographics and under sampling in others.

_cs2017_ 6y ago
Pick randomly a list of top papers in ML, for example https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-know.html https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-k.... Most (if not all) all of them have no "positive" or "negative" tone, as far as I can tell.
izacus 6y ago
The thing is - I don't think the bias in AI is fixable. The way we fix it is to regulate (not self-regulate, Google, Apple, Facebook and other AI companies aren't trustworthy to do it right) where AI is allowed to be used and how much of a negative impact of a persons livelihood can it impact. In other words, we need to use all the power we have to avoid "The computer said NO, you're homeless/jailed/poor forever now" scenarios.
- benlivengood 6y ago
  Unfortunately a legal solution is weaker because it has to enumerate the precise conditions that are unacceptable. Do you ban the logistic function? Tanh? Statistics? Actuarial tables have been a part of decision-making for a very long time and it's not possible to form a comprehensive legal statement of "all decisions must be made in good faith with respect to inherent biases and to the most rigorous epistemological standards".
  - chaboud 6y ago
    Funny enough, Aggregability is NP-Hard, so comprehensive consideration of the larger set is not actually practical/possible. Here's the proof: http://www.cs.utep.edu/vladik/2006/tr06-29.pdf http://www.cs.utep.edu/vladik/2006/tr06-29.pdf Perhaps there are mechanisms around performance under external test, auditing, or safe harbor due to documented good-faith, but it is not possible to guarantee correctness for the full set from a subset. Similarly, some approaches will plainly fail to perform well with subgroups of people due to sensing technologies. That may appear as model bias, but it's really a matter of physics and available entropy. For the time being, mechanisms that use machine inference as an aid rather than a guide (leaving the judgment to the human in the loop) are probably the best we can hope for.

YinglingLight 6y ago

Yet Redditor's and HN'ers treat Scientists as centuries ago people treated men of the cloth. Their word is not to be scrutinized. You wouldn't want to be outed as being critical of the Scientific Method would you? (the irony between those two sentences have been lost in the last 5 years)

ritchiea 6y ago

When scientists write results sections and abstracts they strike a tone. They make an argument for why the raw data is meaningful. Scientists interpret data, which involves a layer of human analysis that is not objective but is attempting to find the correct language and narrative to describe the results of an objective, quantitative process. Outside of the methods and data sections, academic science writing absolutely has to strike a tone. And especially when you are seeking grants and career progression one of the tones you have to strike is to highlight the importance of the work. Once in a science course in college, I had to present a paper to my class. I tried to present it "objectively" as you would describe it, avoid striking a tone or making judgements. My professor told my presentation was technically correct but failed to highlight the broad significance of the research, which comes from tone. Science writing requires selecting a tone of voice.

ClumsyPilot 6y ago

'is doing marketing / PR work rather than science. There's nothing wrong with that' I like how we learned nothing from decades of lies and billions of damages in big tabacco, asbestos, lead in petrol and climate change. Whats next, can we tell aircraft safety inspectors to strike a positive tone and declare a damaged airframe flight worthy? How about rating some securities in a positive tone? Lets call it what it is, corruption

indymike 6y ago

Scientific papers often have a "research implications" or "implications" section that generally is optimistic or pessimistic depending on the results. There's nothing wrong with this, so long as the implications are not steering the results.