Hannah Devlin
The Guardian
Originally posted November 1, 2016
The human brain is predisposed to learn negative stereotypes, according to research that offers clues as to how prejudice emerges and spreads through society.
The study found that the brain responds more strongly to information about groups who are portrayed unfavourably, adding weight to the view that the negative depiction of ethnic or religious minorities in the media can fuel racial bias.
Hugo Spiers, a neuroscientist at University College London, who led the research, said: “The newspapers are filled with ghastly things people do ... You’re getting all these news stories and the negative ones stand out. When you look at Islam, for example, there’s so many more negative stories than positive ones and that will build up over time.”
The article is here.
Wednesday, November 30, 2016
Can Robots Make Moral Decisions? Should They?
Joelle Renstrom
The Daily Beast
Originally published November 12, 2016
Here is an excerpt:
Whether it’s possible to program a robot with safeguards such as Asimov’s laws is debatable. A word such as “harm” is vague (what about emotional harm? Is replacing a human employee harm?), and abstract concepts present coding problems. The robots in Asimov’s fiction expose complications and loopholes in the three laws, and even when the laws work, robots still have to assess situations.
Assessing situations can be complicated. A robot has to identify the players, conditions, and possible outcomes for various scenarios. It’s doubtful than an algorithm can do that—at least, not without some undesirable results. A roboticist at the Bristol Robotics Laboratory programmed a robot to save human proxies called “H-bots” from danger. When one H-bot headed for danger, the robot successfully pushed it out of the way. But when two H-bots became imperiled, the robot choked 42 percent of the time, unable to decide which to save and letting them both “die.” The experiment highlights the importance of morality: without it, how can a robot decide whom to save or what’s best for humanity, especially if it can’t calculate survival odds?
The article is here.
The Daily Beast
Originally published November 12, 2016
Here is an excerpt:
Whether it’s possible to program a robot with safeguards such as Asimov’s laws is debatable. A word such as “harm” is vague (what about emotional harm? Is replacing a human employee harm?), and abstract concepts present coding problems. The robots in Asimov’s fiction expose complications and loopholes in the three laws, and even when the laws work, robots still have to assess situations.
Assessing situations can be complicated. A robot has to identify the players, conditions, and possible outcomes for various scenarios. It’s doubtful than an algorithm can do that—at least, not without some undesirable results. A roboticist at the Bristol Robotics Laboratory programmed a robot to save human proxies called “H-bots” from danger. When one H-bot headed for danger, the robot successfully pushed it out of the way. But when two H-bots became imperiled, the robot choked 42 percent of the time, unable to decide which to save and letting them both “die.” The experiment highlights the importance of morality: without it, how can a robot decide whom to save or what’s best for humanity, especially if it can’t calculate survival odds?
The article is here.
Tuesday, November 29, 2016
Everyone Thinks They’re More Moral Than Everyone Else
By Cari Romm
New York Magazine - The Science of Us
Originally posted November 15, 2016
There’s been a lot of talk over the past week about the “filter bubble” — the ideological cocoon that each of us inhabits, blinding us to opposing views. As my colleague Drake wrote the day after the election, the filter bubble is why so many people were so blindsided by Donald Trump’s win: They only saw, and only read, stories assuming that it wouldn’t happen.
Our filter bubbles are defined by the people and ideas we choose to surround ourselves with, but each of us also lives in a one-person bubble of sorts, viewing the world through our own distorted sense of self. The way we view ourselves in relation to others is a constant tug-of-war between two opposing forces: On one end of the spectrum is something called illusory superiority, a psychological quirk in which we tend to assume that we’re better than average — past research has found it to be true in people estimating their own driving skills, parents’ perceived ability to catch their kid in a lie, even cancer patients’ estimates of their own prognoses. And on the other end of the spectrum, there’s “social projection,” or the assumption that other people share your abilities or beliefs.
Why does imprisoned psychologist still have license to practice?
Charles Keeshan and Susan Sarkauskas
Chicago Daily Herald
Originally published November 11, 2016
Here is an excerpt:
Federal prosecutors said Rinaldi submitted phony bills to Medicare for about $1.1 million over four years, collecting at least $447,155. In nearly a dozen instances, they said, she submitted claims indicating she had provided between 35 and 42 hours of therapy in a single day. In others, she submitted claims stating she had provided care to Chicago-area patients when she was actually in San Diego or Las Vegas.
The article is here.
Chicago Daily Herald
Originally published November 11, 2016
Here is an excerpt:
Federal prosecutors said Rinaldi submitted phony bills to Medicare for about $1.1 million over four years, collecting at least $447,155. In nearly a dozen instances, they said, she submitted claims indicating she had provided between 35 and 42 hours of therapy in a single day. In others, she submitted claims stating she had provided care to Chicago-area patients when she was actually in San Diego or Las Vegas.
The article is here.
Monday, November 28, 2016
CRISPR gene-editing tested in a person for the first time
David Cyranoski
Nature
Originally published November 16, 2016
A Chinese group has become the first to inject a person with cells that contain genes edited using the revolutionary CRISPR–Cas9 technique.
On 28 October, a team led by oncologist Lu You at Sichuan University in Chengdu delivered the modified cells into a patient with aggressive lung cancer as part of a clinical trial at the West China Hospital, also in Chengdu.
Earlier clinical trials using cells edited with a different technique have excited clinicians. The introduction of CRISPR, which is simpler and more efficient than other techniques, will probably accelerate the race to get gene-edited cells into the clinic across the world, says Carl June, who specializes in immunotherapy at the University of Pennsylvania in Philadelphia and led one of the earlier studies.
The article is here.
Nature
Originally published November 16, 2016
A Chinese group has become the first to inject a person with cells that contain genes edited using the revolutionary CRISPR–Cas9 technique.
On 28 October, a team led by oncologist Lu You at Sichuan University in Chengdu delivered the modified cells into a patient with aggressive lung cancer as part of a clinical trial at the West China Hospital, also in Chengdu.
Earlier clinical trials using cells edited with a different technique have excited clinicians. The introduction of CRISPR, which is simpler and more efficient than other techniques, will probably accelerate the race to get gene-edited cells into the clinic across the world, says Carl June, who specializes in immunotherapy at the University of Pennsylvania in Philadelphia and led one of the earlier studies.
The article is here.
Studying ethics, 'Star Trek' style, at Drake
Daniel P. Finney
The Des Moines Register
Originally posted November 10, 2016
Here is an excerpt:
Sure, the discussion was about ethics of the fictional universe of “Star Trek.” But fiction, like all art, reflects the human condition.
The issue Capt. Sisko wrestled with had parallels to the real world.
Some historians hold the controversial assertion that President Franklin D. Roosevelt knew of the impending attack on Pearl Harbor in 1941 but allowed it to happen to bring the United States into World War II, a move the public opposed before the attack.
In more recent times, former President George W. Bush’s administration used faulty intelligence suggesting Iraq possessed weapons of mass destruction to justify a war that many believed would stabilize the increasingly sectarian Middle East. It did not.
The article is here.
The Des Moines Register
Originally posted November 10, 2016
Here is an excerpt:
Sure, the discussion was about ethics of the fictional universe of “Star Trek.” But fiction, like all art, reflects the human condition.
The issue Capt. Sisko wrestled with had parallels to the real world.
Some historians hold the controversial assertion that President Franklin D. Roosevelt knew of the impending attack on Pearl Harbor in 1941 but allowed it to happen to bring the United States into World War II, a move the public opposed before the attack.
In more recent times, former President George W. Bush’s administration used faulty intelligence suggesting Iraq possessed weapons of mass destruction to justify a war that many believed would stabilize the increasingly sectarian Middle East. It did not.
The article is here.
Sunday, November 27, 2016
Approach-Induced Biases in Human Information Sampling
Laurence T. Hunt and others
PLOS Biology
Published: November 10, 2016
Abstract
Information sampling is often biased towards seeking evidence that confirms one’s prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled (“positive evidence approach”), the selection of which information to sample (“sampling the favorite”), and the interaction between information sampling and subsequent choices (“rejecting unsampled options”). The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.
The article is here.
PLOS Biology
Published: November 10, 2016
Abstract
Information sampling is often biased towards seeking evidence that confirms one’s prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled (“positive evidence approach”), the selection of which information to sample (“sampling the favorite”), and the interaction between information sampling and subsequent choices (“rejecting unsampled options”). The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.
The article is here.
Saturday, November 26, 2016
Harvard scientists think they've pinpointed the physical source of consciousness
Fiona McDonald
Sciencealert.com
Originally posted 8 November 2016
Here is an excerpt:
Now the Harvard team has identified not only the specific brainstem region linked to arousal, but also two cortex regions, that all appear to work together to form consciousness.
To figure this out, the team analysed 36 patients in hospital with brainstem lesions - 12 of them were in a coma (unconscious) and 24 were defined as being conscious.
The researchers then mapped their brainstems to figure out if there was one particular region that could explain why some patients had maintained consciousness despite their injuries, while others had become comatose.
What they found was one small area of the brainstem - known as the rostral dorsolateral pontine tegmentum - that was significantly associated with coma. Ten out of the 12 unconscious patients had damage in this area, while just one out of the 24 conscious patients did.
The article is here.
Sciencealert.com
Originally posted 8 November 2016
Here is an excerpt:
Now the Harvard team has identified not only the specific brainstem region linked to arousal, but also two cortex regions, that all appear to work together to form consciousness.
To figure this out, the team analysed 36 patients in hospital with brainstem lesions - 12 of them were in a coma (unconscious) and 24 were defined as being conscious.
The researchers then mapped their brainstems to figure out if there was one particular region that could explain why some patients had maintained consciousness despite their injuries, while others had become comatose.
What they found was one small area of the brainstem - known as the rostral dorsolateral pontine tegmentum - that was significantly associated with coma. Ten out of the 12 unconscious patients had damage in this area, while just one out of the 24 conscious patients did.
The article is here.
What is data ethics?
Luciano Floridi and Mariarosaria Taddeo
Philosophical Transactions Royal Society A
This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the sametime, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software and data—rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments.This article is part of the themed issue ‘The ethical impact of data science’.
The article is here.
Philosophical Transactions Royal Society A
This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the sametime, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software and data—rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments.This article is part of the themed issue ‘The ethical impact of data science’.
The article is here.
Subscribe to:
Posts (Atom)