Could a Rising Robot Workforce Make Humans Less Prejudiced?

Jackson, J., Castelo, N. & Gray, K. (2019).
American Psychologist. (2019)

Automation is becoming ever more prevalent, with robot workers replacing many human employees. Many perspectives have examined the economic impact of a robot workforce, but here we consider its social impact: how will the rise of robot workers affect intergroup relations? Whereas some past research suggests that more robots will lead to more intergroup prejudice, we suggest that robots could also reduce prejudice by highlighting commonalities between all humans. As robot workers become more salient, intergroup differences—including racial and religious differences—may seem less important, fostering a perception of a common human identity (i.e., “panhumanism.”) Six studies (∑N= 3,312) support this hypothesis. Anxiety about the rising robot workforce predicts less anxiety about human out-groups (Study 1) and priming the salience of a robot workforce reduces prejudice towards out-groups (Study 2), makes people more accepting of out-group members as leaders and family members (Study 3), and increases wage equality across in-group and out-group members in an economic simulation (Study 4). This effect is mediated by panhumanism (Studies 5-6), suggesting that the perception of a common human in-group explains why robot salience reduces prejudice. We discuss why automation may sometimes exacerbate intergroup tensions and other-times reduce them.

From the General Discussion

An open question remains about when automation helps versus harms intergroup relations. Our evidence is optimistic, showing that robot workers can increase solidarity between human groups. Yet other studies are pessimistic, showing that reminders of rising automation can increase people’s perceived material insecurity, leading them to feel more threatened by immigrants and foreign workers (Im et al., in press; Frey, Berger, & Chen, 2017), and data that we gathered across 37 nations—summarized in our supplemental materials—suggest that the countries that have automated the fastest over the last 42 years have also increased more in explicit prejudice towards out-groups, an effect that is partially explained by rising unemployment rates.

The research is here.

'DNA is not your destiny': Genetics a poor indicator of health

Nicole Bergot
Edmonton Journal
Originally posted 18 Dec 19

The vast majority of diseases, including many cancers, diabetes, and Alzheimer’s, have a genetic contribution of just five to 10 per cent, shows the meta-analysis of data from studies that examine relationships between common gene mutations, or single nucleotide polymorphisms (SNPs), and different conditions.

“Simply put, DNA is not your destiny, and SNPs are duds for disease prediction,” said study co-author David Wishart, professor in the department of biological sciences and the department of computing science.

But there are exceptions, including Crohn’s disease, celiac disease, and macular degeneration, which have a genetic contribution of approximately 40 to 50 per cent.

“Despite these rare exceptions, it is becoming increasingly clear that the risks for getting most diseases arise from your metabolism, your environment, your lifestyle, or your exposure to various kinds of nutrients, chemicals, bacteria, or viruses,” said Wishart.

The info is here.

Consciousness is real

Massimo Pigliucci
aeon.com
Originally published 16 Dec 19

Here is an excerpt:

Here is where the fundamental divide in philosophy of mind occurs, between ‘dualists’ and ‘illusionists’. Both camps agree that there is more to consciousness than the access aspect and, moreover, that phenomenal consciousness seems to have nonphysical properties (the ‘what is it like’ thing). From there, one can go in two very different directions: the scientific horn of the dilemma, attempting to explain how science might provide us with a satisfactory account of phenomenal consciousness, as Frankish does; or the antiscientific horn, claiming that phenomenal consciousness is squarely outside the domain of competence of science, as David Chalmers has been arguing for most of his career, for instance in his book The Conscious Mind (1996).

By embracing the antiscientific position, Chalmers & co are forced to go dualist. Dualism is the notion that physical and mental phenomena are somehow irreconcilable, two different kinds of beasts, so to speak. Classically, dualism concerns substances: according to René Descartes, the body is made of physical stuff (in Latin, res extensa), while the mind is made of mental stuff (in Latin, res cogitans). Nowadays, thanks to our advances in both physics and biology, nobody takes substance dualism seriously anymore. The alternative is something called property dualism, which acknowledges that everything – body and mind – is made of the same basic stuff (quarks and so forth), but that this stuff somehow (notice the vagueness here) changes when things get organised into brains and special properties appear that are nowhere else to be found in the material world. (For more on the difference between property and substance dualism, see Scott Calef’s definition.)

The ‘illusionists’, by contrast, take the scientific route, accepting physicalism (or materialism, or some other similar ‘ism’), meaning that they think – with modern science – not only that everything is made of the same basic kind of stuff, but that there are no special barriers separating physical from mental phenomena. However, since these people agree with the dualists that phenomenal consciousness seems to be spooky, the only option open to them seems to be that of denying the existence of whatever appears not to be physical. Hence the notion that phenomenal consciousness is a kind of illusion.

The essay is here.

Ethics In AI: Why Values For Data Matter

Marc Teerlink
forbes.com
Originally posted 18 Dec 19

Here is an excerpt:

Data Is an Asset, and It Must Have Values

Already, 22% of U.S. companies have attributed part of their profits to AI and advanced cases of (AI infused) predictive analytics.

According to a recent study SAP conducted in conjunction with the Economist’s Intelligent Unit, organizations doing the most with machine learning have experienced 43% more growth on average versus those who aren’t using AI and ML at all — or not using AI well.

One of their secrets: They treat data as an asset. The same way organizations treat inventory, fleet, and manufacturing assets.

They start with clear data governance with executive ownership and accountability (for a concrete example of how this looks, here are some principles and governance models that we at SAP apply in our daily work).

So, do treat data as an asset, because, no matter how powerful the algorithm, poor training data will limit the effectiveness of Artificial Intelligence and Predictive Analytics.

The info is here.

Inaccurate group meta-perceptions drive negative out-group attributions in competitive contexts

Lees, J., Cikara, M.
Nat Hum Behav (2019)

Abstract

Across seven experiments and one survey (N=4282) people consistently overestimated out-group negativity towards the collective behavior of their in-group. This negativity bias in group meta-perception was present across multiple competitive (but not cooperative) intergroup contexts, and appears to be yoked to group psychology more generally; we observed negativity bias for estimation of out-group, anonymized-group, and even fellow in-group members’ perceptions. Importantly, in the context of American politics greater inaccuracy was associated with increased belief that the out-group is motivated by purposeful obstructionism. However, an intervention that informed participants of the inaccuracy of their beliefs reduced negative out-group attributions, and was more effective for those whose group meta-perceptions were more inaccurate. In sum, we highlight a pernicious bias in social judgments of how we believe ‘they’ see ‘our’ behavior, demonstrate how such inaccurate beliefs can exacerbate intergroup conflict, and provide an avenue for reducing the negative effects of inaccuracy.

From the Discussion

Our findings highlight a consistent, pernicious inaccuracy in social perception, along withhow these inaccurate perceptions relate to negative attributions towards out-groups. More broadly, inaccurate and overly negative GMPs exist across multiple competitive intergroup contexts, and we find no evidence they differ across the political spectrum. This suggests that there may be many domains of intergroup interaction where inaccurate GMPs could potentially diminish the likelihood of cooperation and instead exacerbate the possibility of conflict. However, our findings also highlight a straight-forward manner in which simply informing individuals of their inaccurate beliefs can reduce these negative attributions.

A version of the research can be downloaded here.

French Executives Found Responsible for 35 Employees' Deaths by Suicide

Katie Way

vice.com

Originally posted 20 Dec 19

Today, in a landmark case for worker’s rights and workplace accountability, three former executives of telecommunication company Orange (formerly known as France Télécom) were charged with “collective moral harassment” after creating a work environment which was found to have directly contributed to the death by suicide of 35 employees. This included, according to NPR , 19 employees who died by suicide between 2008 and 2009, many of whom “left notes blaming the company or who killed themselves at work.”

Why would a company lead a terror campaign against its own workers? Money, of course: The plan was enacted as part of a push to get rid of 22,000 employees in order to counterbalance $50 million in debt incurred after the company privatized—it was formerly a piece of the French government’s Ministry of Posts and Telecommunications, meaning its employees were granted special protection as civil servants that prevented their higher-ups from firing them. According to the New York Times, the executives attempted to solve this dilemma by creating an “atmosphere of fear” and purposefully stoked “severe anxiety” in order to drive workers to quit. Former CEO Didier Lombard, sentenced to four months in jail and a $16,000 fine, reportedly called the strategies part of a plan to get rid of unwanted employees “either through the window or through the door.” Way to say the quiet part loud, Monsieur!

The info is here.

How should we balance morality and the law?

Peter Koch
BCM Blogs
Originally posted 20 Dec 19

I was recently discussing a clinical case with medical students and physicians that involved balancing murky ethical issues and relevant laws. One participant leaned back and said: “Well, if we know the laws, then that’s the end of the story!”

The laws were clear about what ought to (legally) be done, but following the laws in this case would likely produce a bad outcome. We ended up divided about how to proceed with the case, but this discussion raised a bigger question: Exactly how much should we weigh the law in moral deliberations?

The basic distinction between the legal and moral is easy enough to identify. Most people agree that what is legal is not necessarily moral and what is immoral should not necessarily be illegal.

Slavery in the U.S. is commonly used as an example. “Of course,” a good modern citizen will say, “slavery was wrong even when it was legal.” The passing of the 13 amendment did not make slavery morally wrong; it was wrong already, and the legal structures finally caught up to the moral structures.

There are plenty of acts that are immoral but that should not be illegal. For example, perhaps it is immoral to gossip about your friend’s personal life, but most would agree that this sort of gossip should not be outlawed. The basic distinction between the legal and the moral appears to be simple enough.

Things get trickier, though, when we press more deeply into the matter.

The blog post is here.

Emotion semantics show both cultural variation and universal structure

Jackson, C. J., Watts, J. and others.
Science  20 Dec 2019:
Vol. 366, Issue 6472, pp. 1517-1522
DOI: 10.1126/science.aaw8160

Abstract

Many human languages have words for emotions such as “anger” and “fear,” yet it is not clear whether these emotions have similar meanings across languages, or why their meanings might vary. We estimate emotion semantics across a sample of 2474 spoken languages using “colexification”—a phenomenon in which languages name semantically related concepts with the same word. Analyses show significant variation in networks of emotion concept colexification, which is predicted by the geographic proximity of language families. We also find evidence of universal structure in emotion colexification networks, with all families differentiating emotions primarily on the basis of hedonic valence and physiological activation. Our findings contribute to debates about universality and diversity in how humans understand and experience emotion.

Exceptionality Effect in Agency: Exceptional Choices Attributed Higher Free Will Than Routine

Fillon, A, Lantian, A., Feldman, G., & N'gbala, A.
PsyArXiv
Originally posted on 9 Nov 19

Abstract

Exceptionality effect is the widely cited phenomenon that people experience stronger regret regarding negative outcomes that are a result of more exceptional circumstances, compared to routine. We hypothesize that the exceptionality-routine attribution asymmetry would extend to attributions of freedom and responsibility. In Experiment 1 (N = 338), we found that people attributed more free will to exceptional behavior compared to routine, when the exception was due to self-choice rather than due to external circumstances. In Experiment 2 (N = 561), we replicated and generalized the effect of exceptionality on attributions of free will to other scenarios, with support for the classic exceptionality effect regarding regret and an extension to moral responsibility. In Experiment 3 (N = 128), we replicated these effects in a within-subject design. When using a classic experimental philosophy paradigm contrasting a deterministic and an indeterministic universe, we found that the results were robust across both contexts. We conclude that there is a consistent support for a link between exceptionality and free will attributions.

From the Conclusion:

Although based on different theoretical frameworks, our results on attributions of free will could be related to the findings of Bear and Knobe (2016). They found that a behavior that was performed “actively” rather than “passively” modifies people’s judgment about the compatibility of this behavior with causal determinism thesis. More concretely, people consider that a behavior performed actively (such as composing a highly technical legal document) is less possible (i.e., less compatible) in a causally deterministic universe than a behavior performed passively (such as impulsively shoplifting from a convenience store; Bear & Knobe, 2016). According to Bear and Knobe (2016), people relied on two cues to determine the active or passive feature of a behavior: mental effort and spontaneity (Bear & Knobe, 2016). By adopting this framework, we may assimilate an exceptional behavior to an active behavior (because its “breaking off from the flow of things,” and require mental effort and spontaneity) and a routine behavior to a passive effort (because it is “going with the flow,” and does not require a mental effort or spontaneity). In the same vein, an agent acting spontaneously is considered freer than an agent acting deliberately (Vierkantet al., 2019). Despite the fact that Vierkant et al. (2019) manipulated the agent’s choice (spontaneous vs. deliberate) in a within-design their study, it may suggest that when deliberation (or mental effort) and spontaneity are experimentally contrasted, it is spontaneity that seems to be the driving force behind the increase of perceived free will of the agent.

The research is here.