Welcome to the Nexus of Ethics, Psychology, Morality, Philosophy and Health Care

Welcome to the nexus of ethics, psychology, morality, technology, health care, and philosophy
Showing posts with label Racial Bias. Show all posts
Showing posts with label Racial Bias. Show all posts

Saturday, June 17, 2023

Debt Collectors Want To Use AI Chatbots To Hustle People For Money

Corin Faife
vice.com
Originally posted 18 MAY 23

Here are two excerpts:

The prospect of automated AI systems making phone calls to distressed people adds another dystopian element to an industry that has long targeted poor and marginalized people. Debt collection and enforcement is far more likely to occur in Black communities than white ones, and research has shown that predatory debt and interest rates exacerbate poverty by keeping people trapped in a never-ending cycle. 

In recent years, borrowers in the US have been piling on debt. In the fourth quarter of 2022, household debt rose to a record $16.9 trillion according to the New York Federal Reserve, accompanied by an increase in delinquency rates on larger debt obligations like mortgages and auto loans. Outstanding credit card balances are at record levels, too. The pandemic generated a huge boom in online spending, and besides traditional credit cards, younger spenders were also hooked by fintech startups pushing new finance products, like the extremely popular “buy now, pay later” model of Klarna, Sezzle, Quadpay and the like.

So debt is mounting, and with interest rates up, more and more people are missing payments. That means more outstanding debts being passed on to collection, giving the industry a chance to sprinkle some AI onto the age-old process of prodding, coaxing, and pressuring people to pay up.

For an insight into how this works, we need look no further than the sales copy of companies that make debt collection software. Here, products are described in a mix of generic corp-speak and dystopian portent: SmartAction, another conversational AI product like Skit, has a debt collection offering that claims to help with “alleviating the negative feelings customers might experience with a human during an uncomfortable process”—because they’ll surely be more comfortable trying to negotiate payments with a robot instead. 

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“Striking the right balance between assertiveness and empathy is a significant challenge in debt collection,” the company writes in the blog post, which claims GPT-4 has the ability to be “firm and compassionate” with customers.

When algorithmic, dynamically optimized systems are applied to sensitive areas like credit and finance, there’s a real possibility that bias is being unknowingly introduced. A McKinsey report into digital collections strategies plainly suggests that AI can be used to identify and segment customers by risk profile—i.e. credit score plus whatever other data points the lender can factor in—and fine-tune contact techniques accordingly. 

Monday, January 3, 2022

Systemic Considerations in Child Development and the Pursuit of Racial Equality in the United States

Perry, S., Skinner-Dorkenoo, A. L., 
Wages, J., & Abaied, J. L. (2021, October 8). 

Abstract

In this commentary on Lewis’ (2021) article in Psychological Inquiry, we expand on ways that both systemic and interpersonal contexts contribute to and uphold racial inequalities, with a particular focus on research on child development and socialization. We also discuss the potential roadblocks that may undermine the effectiveness of Lewis’ (2021) recommended strategy of relying on experts as a driving force for change. We conclude by proposing additional strategies for pursuing racial equality that may increase the impact of experts, such as starting anti-racist socialization early in development, family-level interventions, and teaching people about racial injustices and their connections to systemic racism.

From the Conclusion

Ultimately, the expert (Myrdal) concluded that the problem was White people and how they think about and structure society. Despite the immense popularity of his book among the American public and the fact that it did motivate some policy change (Brown v. Board of Education, Warren& Supreme Court of The United States, 1953), many of the same issues persist to this day. As such, we argue that, although relying on experts may be an appealing recommendation, history suggests that our efforts to reduce racial inequality in the U.S. will require substantial, widespread investment from White U.S. residents in order for real change to occur. Based on the literature reviewed here, significant barriers to such investment remain, many of which begin in early childhood. Beyond pursuing policies that promote structural equality on the advice of experts in ways that do not trigger backlash, we should support policies that educate the public—with a special emphasis on childhood socialization—on the history of systemic racism and the past and continued intentional efforts to create and maintain racial inequalities. 

Building upon recommendations offered by Lewis, we also argue that we need to move the societal bar from simply being non-racist, to being actively anti-racist. As a society, we need to recalibrate our norms, such that passively going along with systemic racism will no longer be acceptable (Tatum, 2017). In the summer of 2020, after the police killings of George Floyd and Breonna Taylor, many organizations released statements in support of the Black Lives Movement, confronting systemic racism, and increasing social justice (Nguyen, 2020). But one question that many posed was whether these organizations and institutions were genuinely committed to tackling systemic racism, or if their acts were performative (Duarte, 2020). If groups, organizations, and institutions want to claim that they are committed to anti-racism, then they should be held accountable for these claims and provide concrete evidence of their efforts to dismantle the pervasive system of racial oppression. In addition to this, we recommend a greater investment in educating the public on the history of systemic racism (particularly with children; such as the Ethnic Studies Model Curriculum implemented in the state of California), prompting White parents to actively be anti-racist and teach their children to do the same, and equitable structural policies that facilitate residential and school racial integration to increase quality interracial contact.

Thursday, December 24, 2020

Google Employees Call Black Scientist's Ouster 'Unprecedented Research Censorship'

Bobby Allyn
www.npr.org
Originally published 3 Dec 20

Hundreds of Google employees have published an open letter following the firing of an accomplished scientist known for her research into the ethics of artificial intelligence and her work showing racial bias in facial recognition technology.

That scientist, Timnit Gebru, helped lead Google's Ethical Artificial Intelligence Team until Tuesday.

Gebru, who is Black, says she was forced out of the company after a dispute over a research paper and an email she subsequently sent to peers expressing frustration over how the tech giant treats employees of color and women.

"Instead of being embraced by Google as an exceptionally talented and prolific contributor, Dr. Gebru has faced defensiveness, racism, gaslighting, research censorship, and now a retaliatory firing," the open letter said. By Thursday evening, more than 400 Google employees and hundreds of outsiders — many of them academics — had signed it.

The research paper in question was co-authored by Gebru along with four others at Google and two other researchers. It examined the environmental and ethical implications of an AI tool used by Google and other technology companies, according to NPR's review of the draft paper.

The 12-page draft explored the possible pitfalls of relying on the tool, which scans massive amounts of information on the Internet and produces text as if written by a human. The paper argued it could end up mimicking hate speech and other types of derogatory and biased language found online. The paper also cautioned against the energy cost of using such large-scale AI models.

According to Gebru, she was planning to present the paper at a research conference next year, but then her bosses at Google stepped in and demanded she retract the paper or remove all the Google employees as authors.

Saturday, December 12, 2020

‘All You Want Is to Be Believed’: The Impacts of Unconscious Bias in Health Care

April Dembosky
KHN.com
Originally published 21 Oct 20

Here is an excerpt:

Research shows how doctors’ unconscious bias affects the care people receive, with Latino and Black patients being less likely to receive pain medications or get referred for advanced care than white patients with the same complaints or symptoms, and more likely to die in childbirth from preventable complications.

In the hospital that day in May, Monterroso was feeling woozy and having trouble communicating, so she had a friend and her friend’s cousin, a cardiac nurse, on the phone to help. They started asking questions: What about Karla’s accelerated heart rate? Her low oxygen levels? Why are her lips blue?

The doctor walked out of the room. He refused to care for Monterroso while her friends were on the phone, she said, and when he came back, the only thing he wanted to talk about was Monterroso’s tone and her friends’ tone.

“The implication was that we were insubordinate,” Monterroso said.

She told the doctor she didn’t want to talk about her tone. She wanted to talk about her health care. She was worried about possible blood clots in her leg and she asked for a CT scan.

“Well, you know, the CT scan is radiation right next to your breast tissue. Do you want to get breast cancer?” Monterroso recalled the doctor saying to her. “I only feel comfortable giving you that test if you say that you’re fine getting breast cancer.”

Monterroso thought to herself, “Swallow it up, Karla. You need to be well.” And so she said to the doctor: “I’m fine getting breast cancer.”

He never ordered the test.

Monterroso asked for a different doctor, for a hospital advocate. No and no, she was told. She began to worry about her safety. She wanted to get out of there. Her friends, all calling every medical professional they knew to confirm that this treatment was not right, came to pick her up and drove her to the University of California-San Francisco. The team there gave her an EKG, a chest X-ray and a CT scan.

Monday, November 25, 2019

Racial bias in a medical algorithm favors white patients over sicker black patients

Carolyn Johnson
Scientists discovered racial bias in a widely used medical algorithm that predicts which patients will have complex health needs.  (iStock)The Washington Post
Originally posted October 24, 2019

A widely used algorithm that predicts which patients will benefit from extra medical care dramatically underestimates the health needs of the sickest black patients, amplifying long-standing racial disparities in medicine, researchers have found.

The problem was caught in an algorithm sold by a leading health services company, called Optum, to guide care decision-making for millions of people. But the same issue almost certainly exists in other tools used by other private companies, nonprofit health systems and government agencies to manage the health care of about 200 million people in the United States each year, the scientists reported in the journal Science.

Correcting the bias would more than double the number of black patients flagged as at risk of complicated medical needs within the health system the researchers studied, and they are already working with Optum on a fix. When the company replicated the analysis on a national data set of 3.7 million patients, they found that black patients who were ranked by the algorithm as equally as in need of extra care as white patients were much sicker: They collectively suffered from 48,772 additional chronic diseases.

The info is here.

Wednesday, September 9, 2015

How can healthcare professionals better manage their unconscious racial bias?

By April Dembosky
MedCity News
Originally published August 21, 2015

Here is an excerpt:

Racial Disparity In Medical Treatment Persists

Even as the health of Americans has improved, the disparities in treatment and outcomes between white patients and black and Latino patients are almost as big as they were 50 years ago.

A growing body of research suggests that doctors’ unconscious behavior plays a role in these statistics, and the Institute of Medicine of the National Academy of Sciences has called for more studies looking at discrimination and prejudice in health care.

For example, several studies show that African-American patients are often prescribed less pain medication than white patients with the same complaints. Black patients with chest pain are referred for advanced cardiac care less often than white patients with identical symptoms.

Doctors, nurses and other health workers don’t mean to treat people differently, says Howard Ross, founder of management consulting firm Cook Ross, who has worked with many groups on diversity issues. But all these professionals harbor stereotypes that they’re not aware they have, he says. Everybody does.

The entire article is here.