The evolution of cooperative behavior does not necessarily require that animals develop a sense of fairness

A pair of blue-throated macaws (Ara glaucogularis) at Chester Zoo, England. These birds, like most ... [+] parrot species, form strong life-long monogamous pair bonds.(Credit: David Friel / CC BY 2.0)

As anyone who lives with parrots knows, they are very jealous and protective of their mates whether their mate is another parrot or a human. But parrots are not jealous about food. Basically, if one parrot is given a less desirable food reward than its partner gets, there are no temper tantrums which is the typical response to unequal resource distribution seen in great apes (and even in a large number of humans). Apparently, unlike most primates, parrot couples are quite tolerant of inequality.

This was the conclusion reached recently by a team of scientists from theMax Planck Institute for Animal Behaviour, a newly-independent research institution in Germany formerly known as the Max Planck Institute for Ornithology.

A key feature in the evolution of cooperation is a sense of fairness, where individuals are provided rewards that are fair and equitable to avoid future breakdown in cooperation (ref). Humans, even children, show a clear and consistent preference for equal over unequal outcomes (ref), a trait known as inequity aversion. For example, children as young as six years old refuse a reward that is less valuable than that given to a peer (disadvantageous inequity aversion), whereas older children typically refuse a reward that is more valuable than that provided to a peer (advantageous inequity aversion). Social scientists consider disadvantageous inequity aversion to be a universal feature of human behavior (PDF), whilst advantageous inequity aversion is probably influenced strongly by cultural norms.

Scientists think that sensitivity to inequity evolved in parallel with the ability for individuals to cooperate because it helps sustain benefitting from cooperation. Additionally, it has been proposed that species that rely on cooperating with group members may benefit from evaluating the equality of their cooperative payoffs to assess whether to stay with a certain partner, or mate, or to look for a new one to gain better outcomes.

The token-exchange paradigm is a classic tool in animal behavior studies that is used to study fairness. It tests the willingness of an animal to sacrifice its own material pay-offs for the sake of greater equality. In this test, when an experimenter does not equally distribute rewards of equal value between experimental subjects, the study animals may express their displeasure with a variety of responses, ranging from refusing to participate in further tests, throwing the reward at the experimenter or even with a temper tantrum.

A team of scientists trained four species of parrots held by the Max-Planck Comparative Cognition Research Station at Loro Parque in Spain, to trade tokens for food. The researchers were under the leadership of Anastasia Krasheninnikova, a postdoctoral researcher at the Institute whose main research interest is the evolution of cognitive skills, particularly identifying whether these skills may be influenced by different socio-ecological living conditions.

This study was designed to provide data on inequity aversion in species, such as parrots, that are distantly related to primates. It also was designed to provide more data on inequity aversion in long-term monogamous species by testing the reaction to inequity of four parrot species belonging to the Psittacoidea superfamily: blue-throated macaws, Ara glaucogularis; great green macaws, Ara ambiguus; blue-headed macaws, Primolius couloni; and African grey parrots, Psittacus erithacus. These species all form long-term monogamous pair bonds and live in family groups. Both parents provide food to their young and offspring stay with their parents for at least one breeding season.

After the study parrots had been trained to trade tokens (a steel washer) for a food reward (either a sunflower seed or a piece of a walnut), the team of researchers then conducted a series of experiments where two parrots were placed into adjacent compartments and each was asked, in turn, by the experimenter to exchange a token for food. Depending upon the experimental treatment, the parrots were either rewarded unequally (Figure 1A) or equally (Figure1B,C) for their efforts. During the tests, the parrots could easily see each other and the food rewards that each parrot got.

Figure 1. Experimental design showing the test and control conditions. Sunflower seeds are ... [+] low-quality rewards and walnut seeds are high-quality rewards.(Image courtesy of Anastasia Krasheninnikova and colleagues.)

Dr. Krasheninnikova and her collaborators observed how the study parrots reacted when they received a food reward with a differing quality for the same effort (unequal reward; Figure 1A) or when one parrot was expected to work harder than his or her partner for the same reward (unequal effort; Figure 1E). When the study parrots reactions were compared to what was observed for equal treatment for each species (Figure 1BC), Dr. Krasheninnikova and her collaborators saw no differences and they definitely did not see any temper tantrums (data video and Figure 2).

Of course, the study parrots had their own opinions about the study. For example, in the control test (when the neighboring chamber was empty), the two bigger macaw species refused to exchange tokens if a better reward was delivered to the empty enclosure (Figure 1D), whilst the smaller parrot species did not refuse to exchange tokens but took longer to do so (African grey parrots) or longer to accept rewards (blue-headed macaws).

Dr. Krasheninnikova and her collaborators found that the blue-throated macaws apparently became increasingly frustrated with the test procedure, whereas the African grey parrots showed the opposite pattern and escalated their number of exchanges in all conditions during the course of the study. This response might indicate that the grey parrots became so familiar with the exchange procedure that they stopped caring about the rewards and their distribution.

These distinct responses reveal strong species differences in their innate sensitivity to reward quality and their frustration (or motivation) with the token exchange task itself, making comparative studies very difficult to interpret.

Figure 2. (AD) Exchanges across test conditions separately for each species (all test sessions ... [+] combined; EQUL = equal low, EQUH = equal high, UNEQ = unequal, FC = food control, EC = effort control, UNEF = unequal effort). (Anastasia Krasheninnikova et al. | doi:10.1038/s41598-019-52780-8)

This study raises an important question: why arent parrots jealous when their partner gets a better reward for the same effort or when one parrot must work harder for the same reward? The answer, we think, can be summed up in just one word: monogamy. Unlike most mammals, most parrot species form long-term monogamous pair bonds and both parents care for their nestlings.

In contrast, it turns out that in long-term monogamous species that form pair bonds for life and show biparental care, such as parrots, there is a much higher tolerance of inequity, Dr. von Bayern said. In such species, individuals greatly depend on their functioning pair-bond and consequently, disrupting such a valuable bond in order to look for a fairer partner would simply be too costly.

But not all parrot species are monogamous. For example, Eclectus parrots, Eclectus species, and Vasa parrots, Coracopsis species, are polygynandrous, whilst a number of other species are socially cooperative breeders, including the golden parakeet, Guaruba guarouba, New Caledonian parakeet, Cyanoramphus saisseti, the horned parakeet, Eunymphicus cornutus, and the monk (quaker) parakeet, Myopsitta monachus. Testing these species using the token-exchange paradigm could provide important insights into whether inequity aversion is a general trait amongst all parrots or whether it is linked to social organization and species mating system.

This is an important finding because inequity aversion, also termed sense of fairness has been considered an important mechanism in the evolution of cooperative behaviour, Dr. Krasheninnikova said in a press release.

It enables individuals to detect when their partner cheats upon them, e.g. by not sharing food equally or by avoiding effort, and therefore allows them to decide when it pays off to switch to a new cooperation partner.

It is a good strategy only for animals living in societies in which one can switch between cooperation partners easily, such as those of most primates, agreed senior author, zoologist Auguste von Bayern, in a press release.

Social organization plays a strong role in whether an individual can easily switch to a new mate or cooperation partner but how strong is the effect of social organization upon the evolution of cooperation?

Our study adds to the very recent evidence, that inequity aversion is not a general prerequisite for the evolution of cooperation, Dr. von Bayern said in a press release.

Anastasia Krasheninnikova,Dsire Brucks,Nina Buffenoir,Dniel Rivas Blanco,Delphine Soulet&Auguste von Bayern(2019). Parrots do not show inequity aversion, Scientific Reports9:16416 | doi:10.1038/s41598-019-52780-8

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Parrots Aren't Jealous When Their Mate Gets A Better Reward - Forbes

Evolutionary scientists have been thinking about same-sex sexual behavior all wrong.

That's the implication of a new study on same-sex behavior in animals. Instead of asking why animals engage in same-sex behavior (SSB), researchers should be asking, "Why not?" the authors said.

If they're right, same-sex sex may not have evolved independently in different animals for adpative reasons. Instead, same-sex sex may have emerged very early in time and could persist simply because engaging in it doesn't cost animals much, evolutionarily speaking.

"Usually, when evolutionary biologists see a trait that's really widespread across evolutionary lineages, we at least consider the idea that the trait is ancestral and was preserved in all those lineages," said Julia Monk, a doctoral candidate at Yale University, who co-authored the new research. "So why hadn't people considered that hypothesis for SSB?"

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In evolutionary science, same-sex sexual behavior has long been viewed as a conundrum: Why would animals spend time and energy doing something sexual that won't pass along their genes to the next generation? And yet, same-sex sexual behavior has been observed in at least 1,500 species, ranging from lowly squash bugs to humans.

(To avoid anthropomorphizing, the researchers don't use the terms "homosexual," "heterosexual," "gay" or "straight" to refer to animal behavior.)

"We can't assign sexuality to animals we're trying our best to learn about them by observing their behaviors," Monk told Live Science. "And those behaviors shouldn't be mapped onto human cultural and societal contexts."

The assumption that there must be an evolutionary reason for all this same-sex sex has led researchers to search for possible benefits to same-sex behavior. For example, in humans, researchers have found that having a gay son or brother seems to be associated with a woman having more offspring in total. Other studies have posited that same-sex sexual behavior is a side effect of other genes that have reproductive benefits.

In evolutionary biology, the ability of an animal to reproduce given its environment is called fitness. It's entirely possible that in some species, same-sex sex could have fitness benefits, Monk and her colleagues wrote in their paper, published Nov. 18 in the journal Nature Ecology & Evolution. But these evolutionary benefits may not be required for same-sex sexual behavior to exist.

Imagine, instead, that the earliest sexually reproducing animals simply tried to mate with any and all members of their species regardless of sex. This might have been a logical pathway for evolution, because all the bells and whistles that distinguish males from females are energetically costly to evolve. So any effort expended on mating with the same sex would be compensated for by not spending energy evolving and maintaining distinctive secondary sex characteristics, like differing colors, scents and behaviors. Those sex-distinguishing traits may have all come later in the evolutionary chain, the authors argued.

In this formulation, same-sex and different-sex sexual behavior would have started out on an equal footing, early in animal evolution. This could explain why same-sex sex is so common throughout the animal kingdom: It didn't evolve multiple times independently, but was instead part of the fabric of animal evolution from the start.

The new hypothesis undercuts old assumptions about same-sex behaviors, said Caitlin McDonough, a doctoral candidate at Syracuse University and a study co-author. Much of the research done on these sexual behaviors assumes that same-sex sex is costly for animals and that different-sex sex is not costly, she said.

"You really need to go through those assumptions and test the costs and benefits of both behaviors in a system," McDonough said.

If same-sex behaviors go back to the roots of animal evolution, the fact that these behaviors are so common today makes sense, Monk said.

"If you assume a trait like SSB is a new development and has high costs, it's going to be really hard to understand how it could become more and more common from those low initial frequencies," she said. "It would have to have really large fitness benefits, or be otherwise impervious to natural selection, for that outcome to be probable.

"On the other hand, if you assume a trait is ancestral and was originally common, and it has low costs, it's much more likely that it would remain widespread to this day, even if it doesn't seem to contribute much to fitness."

One piece of evidence supporting this hypothesis is that some echinoderms, including sea stars and sea urchins, engage in same-sex sexual behavior. Echinoderms evolved early in the history of life, likely in the Precambrian period more than 541 million years ago.

But other evidence is slim, largely because scientists haven't systematically studied same-sex sexual behavior in animals. Most observations have been accidental, and biologists have often viewed sex between two animals of the same sex as irrelevant or improper to note, Monk said. Sometimes, researchers automatically assume that same-sex behavior isn't really about sex but instead is about dominance or bonding. And often, if two animals are observed having sex, they're assumed to be male and female without any confirmatory evidence, McDonough said.

"The science that we do is really informed and influenced by cultural biases," she said.

Thinking of same-sex sexual behavior as a standard part of the animal repertoire would change how researchers approach the study of the evolution of these behaviors. The next step, Monk said, would be to gather more data on the prevalence of same-sex behavior in animals. Then, researchers could compare species from across the tree of life to determine if all linages show same-sex behavior. If so, it would strengthen the argument that same-sex sexuality was part of life for the ancestors of all of today's sexually reproducing animals.

Originally published on Live Science.

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Was Same-Sex Behavior Hardwired in Animals from the Beginning? - Livescience.com

Enlarge / But what does that car think that the spectator is thinking?

Imagine you're trying to make a left turn onto a busy road. Car after car rolls past, keeping you trapped as your frustration rises. Finally, a generous driver decelerates enough to create a gap. A check of the traffic from the opposite direction, a quick bit of acceleration, and you're successfully merged into traffic.

This same scene plays out across the world countless times a day. And it's a situation where inferring both the physics and the motives of your fellow drivers is difficult, as evidenced by the fact that the United States sees 1.4 million accidents each year from drivers in the process of turning. Now imagine throwing autonomous vehicles into the mix. These are typically limited to evaluating only the physics and to make conservative decisions in situations where information is ambiguous.

Now, a group of computer scientists has figured out how to improve autonomous vehicle (AV) performance in these circumstances. The scientists have essentially given their AVs a limited theory of mind, allowing the vehicles to better interpret what the behaviors of their nearby human drives are telling them.

Theory of mind comes so easily to us that it's difficult to recognize how rare it is outside of our species. We're easily able to recognize that our fellow humans have minds like our own, and we use that recognition to infer things like the state of their knowledge and their likely motivations. These inferences are essential to most of our social activities, driving included. While a friendly wave can make for an unambiguous signal that your fellow driver is offering you space in their lane, we can often make inferences based simply on the behavior of their car.

And, critically, autonomous vehicles aren't especially good at this. In many cases, their own behavior doesn't send signals back to other drivers. A study of accidents involving AVs in California indicated that over half of them involved the AV being rear-ended because a human driver couldn't figure out what in the world it was doing. (Volvo, among others, is working to change that.)

It's unrealistic to think that we'll give AVs a full-blown theory of mind any time soon. AIs are simply not that advanced, and it would be excessive for cars, which only have to deal with a limited range of human behaviors. But a group of researchers at MIT and Delft University of Technology has decided that putting an extremely limited theory of mind in place for certain driving decisions, including turns and merges, should be possible.

The idea behind the researchers' work, described in a new paper in PNAS, involves a concept called social value orientation, which is a way of measuring how selfish or community-oriented an individual's actions are. While there are undoubtedly detailed surveys that can provide a meticulous description of a person's social value orientation, autonomous vehicles generally won't have the time to be giving their fellow drivers surveys.

So the researchers distilled social value orientation into four categories: altruists, who try to maximize the enjoyment of their fellow drivers; prosocial drivers, who try to take actions that allow all other drivers to benefit (which may occasionally involve selfishly flooring it); individualists, who maximize their own driving experience; and competitive drivers, who only care about having a better driving experience than those around them.

The researchers developed a formula that would let them calculate the expected driving trajectory for each of these categories given the starting position of other cars. The autonomous vehicle was programmed to compare the trajectories of actual drivers to the calculated version and use that to determine which of the four categories the drivers were likely to be in. Given that classification, the vehicle could then project what their future actions would be. As the researchers wrote, "we extend the ability of AVs' reasoning by incorporating estimates of the other drivers' personality and driving style from social cues."

This is substantially different from some game-theory work that's been done in the area. That work has assumed that every driver is always maximizing their own gain; if altruism emerges, it's only incidental to this maximization. This new work, in contrast, bakes altruistic behavior into its calculations and recognizes that drivers are complicated and may change their tendencies as situations evolve. In fact, previous studies had indicated that in contexts other than driving, about half of the people tested showed prosocial behavior, with another 40% being selfish.

With the system in place, the researchers obtained data on vehicle locations and trajectories as drivers merged onto a highway, a situation that often requires the generosity of fellow drivers. With the social value orientation system in place, the autonomous driver was able make more accurate predictions of its fellow drivers' trajectories than it could withoutprediction errors dropped by 25%. The system also worked on lane changes on crowded freeways, as well as turns into traffic.

Using these evaluations, the researchers could also make some inferences using the traffic patterns they had. For example, they found that a highway driver may start out selfishly following the car in front of them, shift to altruistic as they decelerate to allow a driver to merge, then switch right back to a selfish approach. Similarly, drivers facing a merge onto a freeway typically ended up being competitivesomething you see every time a vehicle pulls out and slows down everyone who was stuck in the lane behind it.

While we're still a long way off from giving autonomous vehicles a general AI or a full theory of mind, the research shows that you can get significant benefits from giving AVs a very limited one. And it's a nice demonstration that if we want any autonomous system to integrate with something that's currently a social activity, then paying attention to what social scientists have figured out about those activities can be incredibly valuable.

PNAS, 2019. DOI: 10.1073/pnas.1820676116 (About DOIs).

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Improving autonomous autos by having them guess which humans are selfish - Ars Technica

Balancing out the benefits of artificial intelligence to prevent future pitfalls

Ethics surrounding artificial intelligence and the use of Big Data were among the topics discussed at the GRC Summit in London this week.

Organizations looking to implement data-driven tools and leverage the benefits of artificial intelligence (AI) must first understand the risks that these technologies can pose.

That was the consensus held by a panel of industry stakeholders, who cited transparency, standards, and explainability as factors for businesses to consider when creating AI products.

The panel, which took place in London on Monday (November 18), included Laura Turner of the UNs World Food Programme, and Anna Fellnder, co-founder of the AI Sustainability Center.

The reason why ethics is exploding is because AI is different from other data-driven technologies, AI moves faster, Fellnder said.

Theres no transparency and a lack of explainability models.

Machine learning (ML) data trained algorithms that facilitate the automation of tasks and AI human behavior learned in machines are increasingly seen on the marketplace amid confusion of their actual capability.

According to one survey, 40% of European startups are misusing the term AI in their products, The Verge reported in March leading to more funding from investors and a less efficient experience for consumers.

In the security sector, where ML and AI have the potential to identify cyber-threats far faster and more accurately, a quarter of organizations told the Ponemon Institute that they had been using some form of the technologies in their defense solutions.

Organizations supply this seductive technology into their business models and push down costs, nudging their customers to behaviors that could be unethical, Fellnder said.

Regardless of the amount of snake oil out there, the amount of data now available allows for the algorithmic maturity needed to build products and services and equally made ethics surrounding ML and AI a more pressing concern.

Global governments, most notably in the European Union, have even made calls to regulate the use of AI so to prevent potential societal issues such as bias within algorithmic decision-making, violations of user privacy, and dangers in line with cyber-offensive firepower.

When we enter AI you get no control of it, Fellnder said.

Its about having a goal to market readiness in your AI applications, so you dont lead to the [possible] pitfalls, and making sure your values are sustained.

Sir Nigel Shadbolt, chairman and co-founder of the Open Data Institute, who closed the first day of the conference, agreed that more literacy and communication was needed, not only around ML and AI, but the wider data ecosystem.

Were seeing people starting to really worry about the idea of the balance, the interests that they have, the rights that they have, in this data, is somehow way out of whack, he said.

Its not about owning the data, but having some agency on whats being done with it.

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Calls for AI regulation heard at London summit - The Daily Swig