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IMF researchers: digital footprint yields better credit assessment

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Re: IMF researchers: digital footprint yields better credit assessment

#61

Post by thegrimmest »

layoutIfNeeded wrote: post #19
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

Let me illuminate the problem: s/tall/black/ (inb4 downvotes)

I actually wasn't thinking that at all. I chose tall because there is actually a major disparity in income between tall and short people. This disparty seems to be the ultimate counter-argument to any misguided attempt at "levelling the playing field".

Re: IMF researchers: digital footprint yields better credit assessment

#62

Post by dredmorbius »

pvg wrote: post #57
dredmorbius wrote: post #50

Earlier quoted context omitted.

The HN submission guidelines do allow for changes in title, though usually it's to combat undue sensationalism. Otherwise please use the original title, unless it is misleading or linkbait; don't editorialize. https://news.ycombinator.com/newsguidelines.html In this case, the problem is an excess of bureaucratese, euphemism, jargon, and vagueness. As Orwell wrote in "Politics and the English Language" on five badly w…

The title is neither misleading nor linkbait. If you think the article is bad, you can't fix it by making up the title, just find a better article. It's really much more straightforward than you are making it out to be and does not require analysis of Orwells works. Although it is a somewhat curious choice on your part given that you seem to be trying to show that plain editorializing (i.e. "I found that to be the mo…

The original IMF title is a lie by vagueness.

The article is evil in large part because it proposes an absolutely Orwellian regime ... well, pretty much precisely as Orwell suggests such things happen. In vague, political, bureaucratic, anodyne language, with no awareness or consideration of consequences, damage, or alternatives.

As a reference to the evil, the article is invaluable. It is the primary source, straight from the horse's mouth. Much as, say, Mein Kampf was, and the reason a young journalist violated copyright to ensure that it was prominently available in the United States in unexpurgated form:

https://www.latimes.com/archives/la-xpm-1988-02-14-mn-42699-...>

You're presenting a false dichotomy of "making up a the title". The question is how best to find a truth within the mealy-mouthed source. Which has mostly been done (I'm not entirely satisfied with the present HN title "IMF researchers: digital footprint yields better credit assessment", but it certainly improves on the original.

Re: IMF researchers: digital footprint yields better credit assessment

#63

Post by aneemzic »

hntrader wrote: post #46
aneemzic wrote: post #40

Earlier quoted context omitted.

No. Credit worthiness should be because of an individuals past actions and not some attribute they may have been born with. Why should a tall individual who's never missed a payment have some invisible penalization applied because some other tall people are worse at re-paying loans. Don't you see the issue here? You're penalizing individuals not based on their own measurable behavioral signals, but simply due to some…

We must disambiguate between political objectives and the practice of credit risk modelling. Credit risk, f(X), is an unknown population function that needs to be estimated using observed data X. If including tallness into X improves our estimate of f(X), then we've gotten a better model. You've asserted that X should only contain an individual's past actions instead of their inherent traits such as tallness. This ma…

I don't agree that this has anything to do with political objectives. It's a question of ethics. My domain knowledge is irrelevant, the ML Modelling aspect is irrelevant. The discussion was specifically around whether it's ok to include inherent traits when determining the credit worthiness of an individual.

If you think it is, that's fine. We might as well just taking the same approach to crime, and start locking individuals up or not extending job offers, NOT because they've done a single thing wrong, but simply because they're statistically more likely to.

Re: IMF researchers: digital footprint yields better credit assessment

#64

Post by insert_coin »

warkdarrior wrote: post #43
insert_coin wrote: post #27

Earlier quoted context omitted.

I think it gets to the point. If blacks are for some reason (and I am not saying they are I do not know) less likely to pay back loans, then that is the problem that needs addressing. It might be a little painful to admit the huge racial divide but it is real and that is a problem we need to solve, taking the easy way out lying to ourselves only harms society in the long run and destroys the lives of people who canno…

Of course we should address those problems as we identify them. But solutions may take years, even decades, to take root. What should lenders do in the mean time?

> What should lenders do in the mean time?

They could start by not making the problem worse giving loans to people who can't pay them back.

Re: IMF researchers: digital footprint yields better credit assessment

#65

Post by dredmorbius »

dredmorbius wrote: post #59

I'm trying and failing to come up with a concise expression of just how utterly evil and wrong this proposal is, and what the assumptions and presumptions it makes I think the first question needs to be "mu". Unask the question of how, or even whether , individuals' entire personal and informational histories should be deposited in the perpetual datastores of banks, credit lenders, collections agents, slumlords, and…

On authors who were publishing information technology panopticon concerns in the 1980s, or earlier

Paul Baran / RAND

- "On the Engineer's Responsibility in Protecting Privacy"

- "On the Future Computer Era: Modification of the American Character and the Role of the Engineer, or, A Little Caution in the Haste to Number"

- "The Coming Computer Utility -- Laissez-Faire, Licensing, or Regulation?"

- "Remarks on the Question of Privacy Raised by the Automation of Mental Health Records"

- "Some Caveats on the Contribution of Technology to Law Enforcement"

Largely written/published 1967--1969.

https://www.rand.org/pubs/authors/b/baran_paul.html

Willis Ware / RAND

Too numerous to list fully, 1960s --1990s. Highlights:

- "Security and Privacy in Computer Systems" (1967)

- "Computers in Society's Future" (1971)

- "Records, Computers and the Rights of Citizens" (1973

- "Privacy and Security Issues in Information Systems" (1976)

- "Information Systems, Security, and Privacy" (1983)

- "The new faces of privacy" (1993)

https://www.rand.org/pubs/authors/w/ware_willis_h.html

Misc

Shoshana Zuboff, In the Age of the Smart Machine: The Future of Work and Power (1988) Notably reviewed in the Whole Earth Catalog's Signal: Communication Tools for the Information Age (1988).

https://www.worldcat.org/title/in-the-age-of-the-smart-machi... https://archive.org/details/inageofsmartmach00zubo/page/n7/m...

"Danger to Civil Rights?", 80 Microcomputing (1982)

https://archive.org/stream/80_Microcomputing_Issue_26_1982-0... (https://news.ycombinator.com/item?id=14329877)

"Computer-Based National Information Systems: Technology and Public Policy", NTIS (September 1981)

http://govinfo.library.unt.edu/ota/Ota_5/DATA/1981/8109.PDF

"23 to Study Computer ‘Threat’" (1970)

https://www.nytimes.com/1970/03/12/archives/23-to-study-comp...

The Stanford Encyclopedia of Philosophy

"Privacy and Information Technology" bibliography is largely 1990--present, but contains some earlier references.

https://plato.stanford.edu/entries/it-privacy/#Bib

Similarly "Privacy"

https://plato.stanford.edu/entries/privacy/

Credit Reporting / Legislation

US Privacy Act of 1974

https://www.justice.gov/opcl/privacy-act-1974

Invasion of Privacy Act 1971 - Queensland Government, Australia

https://www.legislation.qld.gov.au/view/pdf/inforce/current/...

Arthur R. Miller, The assault on privacy: computers, data banks, and dossiers

https://archive.org/details/assaultonprivacy00mill/page/n7/m...

"The Computer, the Consumer and Privacy" (1984)

https://www.nytimes.com/1984/03/04/weekinreview/the-computer... Richard Boeth / Newsweek

The specific item I'd had in mind:

Richard Boeth, "Is Privacy Dead", Newsweek, July 27, 1970

http://www.thedailybeast.com/articles/2013/06/11/is-privacy-...

Direct PDF: https://assets.documentcloud.org/documents/712228/1970-newsw...

Based on an HN comment: https://news.ycombinator.com/item?id=2

Re: IMF researchers: digital footprint yields better credit assessment

#66

Post by pvg »

dredmorbius wrote: post #62
pvg wrote: post #57

Earlier quoted context omitted.

The title is neither misleading nor linkbait. If you think the article is bad, you can't fix it by making up the title, just find a better article. It's really much more straightforward than you are making it out to be and does not require analysis of Orwells works. Although it is a somewhat curious choice on your part given that you seem to be trying to show that plain editorializing (i.e. "I found that to be the mo…

The original IMF title is a lie by vagueness. The article is evil in large part because it proposes an absolutely Orwellian regime ... well, pretty much precisely as Orwell suggests such things happen. In vague, political, bureaucratic, anodyne language, with no awareness or consideration of consequences, damage, or alternatives. As a reference to the evil, the article is invaluable. It is the primary source, straigh…

Let's wrap up here but, again, there is a totally trivial remedy for an article being "evil". Just don't post it to HN.

Re: IMF researchers: digital footprint yields better credit assessment

#67

Post by dredmorbius »

pvg wrote: post #66
dredmorbius wrote: post #62

Earlier quoted context omitted.

The original IMF title is a lie by vagueness. The article is evil in large part because it proposes an absolutely Orwellian regime ... well, pretty much precisely as Orwell suggests such things happen. In vague, political, bureaucratic, anodyne language, with no awareness or consideration of consequences, damage, or alternatives. As a reference to the evil, the article is invaluable. It is the primary source, straigh…

Let's wrap up here but, again, there is a totally trivial remedy for an article being "evil". Just don't post it to HN.

Exposing the evil is the utility here. Letting this proposal float unobserved is the greater evil.

Sunshine ... isn't always a great disinfectant, but it is in this case.

Re: IMF researchers: digital footprint yields better credit assessment

#68

Post by dredmorbius »

throwaway189262 wrote: post #32
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

More accurate isn't always good because creditworthiness is all about stereotyping people. Consider this example: lesbians are statistically more likely to divorce. The ML models decides that lesbians are a higher mortgage risk and raises their interest rates. It does this indirectly by raising interest rates on married couples with different last names and owners of Subaru vehicles. In another, the model sees that p…

Cathy O'Neil's done some excellent work in this area. "Algorithms are opinions embedded in code."

There's a summary of it on the TED Radio Hour here:

https://www.npr.org/2018/01/26/580617998/cathy-oneil-do-algo...

TED Talk https://embed-ssl.ted.com/talks/cathy_o_neil_the_era_of_blin... (video)

Cathy O’Neil Is Unimpressed by Your AI Bias Removal Tool (A RedTail Q&A) https://redtailmedia.org/2018/10/29/redtail-talks-about-flip...

Weapons of Math Destruction: Cathy O'Neil adds up the damage of algorithms https://www.theguardian.com/books/2016/oct/27/cathy-oneil-we...

Human Insights missing from Big Data: https://www.ted.com/talks/tricia_wang_the_human_insights_mis...

Further references:

Weapons of Math Detruction outlines dangers of relying on data analytics: https://www.npr.org/2016/09/12/493654950/weapons-of-math-des...

Can Big Data Really Help Screen Immigrants? https://www.npr.org/2017/12/15/571199955/dhs-wants-to-build-...

Re: IMF researchers: digital footprint yields better credit assessment

#69

Post by dredmorbius »

thegrimmest wrote: post #42
throwaway189262 wrote: post #32

Earlier quoted context omitted.

More accurate isn't always good because creditworthiness is all about stereotyping people. Consider this example: lesbians are statistically more likely to divorce. The ML models decides that lesbians are a higher mortgage risk and raises their interest rates. It does this indirectly by raising interest rates on married couples with different last names and owners of Subaru vehicles. In another, the model sees that p…

A lot to unpack here, let me try. Are machine learning algorythms capable of stereotyping people? How accurate does a stereotype have to be before it's a useful predictor? If these models lead to good data, then what's wrong with them? If people who follow the NBA do in fact default on their loans more, shouldn't they pay higher interest? I agree that the healthy should not be compelled to subsidize the costs of heal…

Algorithms:

- May be based on bad, inaccurate, or nonrepresentative data.

- May be based on factors intrinsic to individuals which they cannot change.

- May mask underlying bias factors (as in the NBA example above.)

- May reflect existing biases in behaviours. E.g., arrest, promotion, recruitment, or admissions data used to encode an AI selector, which merely codify biases reflected in the underlying historical data.

- May reverse causality, implying A causes B, when in fact B results in A.

- Amplify existing inequalities. Starting points in life matter, and an algorithm which simply amplifies the existing inequities of wealth, race, place of birth, religion, health, etc., compound rather than address these issues.

- Fail to consider fairness or equity in decisionmaking. This is the underlying fundamental problem in credit-based resource allocation. People need access to resources regardless of their creditworthiness, though there might well be cases in which allocations are modified or managed given behavioural issues. Reinforcing standing biases does not address the underlying inequities.

Re: IMF researchers: digital footprint yields better credit assessment

#70

Post by dredmorbius »

JohnJamesRambo wrote: post #24
naurupatel wrote: post #3

Truly a dystopian world we are entering. Now more than ever is the time for funding and developing alternative tools that utilize decentralization. What's coming cannot be stopped but it can be broken.

It is already in motion, cryptocurrency will accept you no matter what your credit score or browsing history is. “The computer can be used as a tool to liberate and protect people, rather than to control them.” -Hal Finney

How are you planning on allocating those bitcoin distributions?

Do you have the context for the Finney quote? Apparently from a set of released emails:

https://news.bitcoin.com/researcher-publishes-never-before-s...

The larger context, from a 1992 Cypherpunks email:

"Here we are faced with the problems of loss of privacy, creeping computerization, massive databases, more centralization - and [David] Chaum offers a completely different direction to go in, one which puts power into the hands of individuals rather than governments and corporations. The computer can be used as a tool to liberate and protect people, rather than to control them."

https://web.archive.org/web/20140326104029/http://www.forbes...

Argument by unsupported assertion is ... relatively weak.

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