Half of Earth’s satellites restrict use of climate data

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Dust storms in the Gulf of Alaska, captured by NASA’s Aqua satellite.

By Mariel Borowitz, Georgia Institute of Technology

Scientists and policymakers need satellite data to understand and address climate change. Yet data from more than half of unclassified Earth-observing satellites is restricted in some way, rather than shared openly.

When governments restrict who can access data, or limit how people can use or redistribute it, that slows the progress of science. Now, as U.S. climate funding is under threat, it’s more important than ever to ensure that researchers and others make the most of the collected data.

Why do some nations choose to restrict satellite data, while others make it openly available? My book, “Open Space,” uses a series of historical case studies, as well as a broad survey of national practices, to show how economic concerns and agency priorities shape the way nations treat their data.

The price of data

Satellites can collect comprehensive data over the oceans, arctic areas and other sparsely populated zones that are difficult for humans to monitor. They can collect data consistently over both space and time, which allows for a high level of accuracy in climate change research.

For example, scientists use data from the U.S.-German GRACE satellite mission to measure the mass of the land ice in both the Arctic and Antarctic. By collecting data on a regular basis over 15 years, GRACE demonstrated that land ice sheets in both Antarctica and Greenland have been losing mass since 2002. Both lost ice mass more rapidly since 2009.

Satellites collect valuable data, but they’re also expensive, typically ranging from US$100 million to nearly $1 billion per mission. They’re usually designed to operate for three to five years, but quite often continue well beyond their design life.

Many nations attempt to sell or commercialize data to recoup some of the costs. Even the U.S. National Oceanic and Atmospheric Administration and the European Space Agency – agencies that now make nearly all of their satellite data openly available – attempted data sales at an earlier stage in their programs. The U.S. Landsat program, originally developed by NASA in the early 1970s, was turned over to a private firm in the 1980s before later returning to government control. Under these systems, prices often ranged from hundreds to thousands of dollars per image.


In other cases, agency priorities prevent any data access at all. As of 2016, more than 35 nations have been involved in the development or operation of an Earth observation satellite. In many cases, nations with small or emerging space programs, such as Egypt and Indonesia, have chosen to build relatively simple satellites to give their engineers hands-on experience.

Since these programs aim to build capacity and demonstrate new technology, rather than distribute or use data, data systems don’t receive significant funding. Agencies can’t afford to develop data portals and other systems that would facilitate broad data access. They also often mistakenly believe that demand for the data from these experimental satellites is low.

If scientists want to encourage nations to make more of their satellite data openly available, both of these issues need to be addressed.

Landsat 8, an American Earth observation satellite.

Promoting access

Since providing data to one user doesn’t reduce the amount available for everyone else, distributing data widely will maximize the benefits to society. The more that open data is used, the more we all benefit from new research and products.

In my research, I’ve found that making data freely available is the best way to make sure the greatest number of people access and use it. In 2001, the U.S. Geological Survey sold 25,000 Landsat images, a record at the time. Then Landsat data was made openly available in 2008. In the year following, the agency distributed more than 1 million Landsat images.

For nations that believe demand for their data is low, or that lack resources to invest in data distribution systems, economic arguments alone are unlikely to spur action. Researchers and other user groups need to raise awareness of the potential uses of this data and make clear to governments their desire to access and use it.

Intergovernmental organizations like the Group on Earth Observations can help with these efforts by connecting research and user communities with relevant government decision-makers. International organizations can also encourage sharing by providing nations with global recognition of their data-sharing efforts. Technical and logistical assistance – helping to set up data portals or hosting foreign data in existing portals – can further reduce the resource investment required by smaller programs.

Promise for future

Satellite technology is improving rapidly. I believe that agencies must find ways to take advantage of these developments while continuing to make data as widely available as possible.

Satellites are collecting more data than ever before. Landsat 8 collected more data in its first two years of operation than Landsat 4 and 5 collected over their combined 32-year lifespan. The Landsat archive currently grows by a terabyte a day.

This avalanche of data opens promising new possibilities for big data and machine learning analyses – but that would require new data access systems. Agencies are embracing cloud technology as a way to address this challenge, but many still struggle with the costs. Should agencies pay commercial cloud providers to store their data, or develop their own systems? Who pays for the cloud resources needed to carry out the analysis: agencies or users?

The ConversationSatellite data can contribute significantly to a wide range of areas – climate change, weather, natural disasters, agricultural development and more – but only if users can access the data.

Mariel Borowitz, Assistant Professor of International Affairs, Georgia Institute of Technology

This article was originally published on The Conversation. Read the original article.

Chimpanzees eat plants that point to new ways of treating diseases

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The medicinal plants eaten by chimpanzees could develop improved traditional medicines.
Reuters/James Akena

By Ahoua Constant, Nangui Abrogoua University

As cancer and other non-infectious diseases continue to rise all over the world it’s become harder for scientists to find safe, effective treatments. In addition, bacteria are becoming more and more resistant to drugs and synthetic medicines have become harsher.

These challenges have led to searches for new solutions, including natural substances, like medicinal plants. Plant based medicines are known to have more benefits because they are less poisonous than synthetic versions. They also have compounds that compliment each other that help in disease prevention.

People have been using plants to make medicines for thousands of years. The World Health Organisation estimates that between 75% and 80% of the world’s population uses at least some plant based medicines.

Africa has its own store of medicinal plants, such as those used in Côte d’Ivoire, Kenya, Mauritius, South Africa and Zimbabwe.

I have been working with a group of scientists to find new ways to exploit plants for medicinal purposes. As part of the process we studied the eating habits and behaviour of some wild chimpanzees based at the Taï National Park in the south western region of Côte d’Ivoire. We identified what they ate, which included leaves, fruit and the stems of the plants. We then tested these in a laboratory.

Our idea followed on from a previous study on the park’s chimpanzees which focused on the energy and protein balance in their diets. Our study focused on the medicinal properties of what they ate.

Our results suggest that the diets of chimpanzees are made up of plants that are a rich source of compounds that improve their immune systems and protect them from certain diseases. Our findings have opened the door to exploring the properties of these plants to test their ability to treat disease in humans.

Tolerance to disease

Chimpanzees are the closest animal to humans genetically, sharing 98% of the human DNA. This genetic closeness means that these great apes share certain diseases with humans. These include yeast infections (candidiasis), Ebola and HIV/AIDS. Chimpanzees are also able to get cancer.

Our hypothesis was that some plants in the chimpanzees’ diet might be keeping them healthy and that this could be useful in developing medicine for humans too.

We tested about 132 extracts from 27 plants chosen based on:

  • how frequently they consumed the plants

  • the time of consumption

  • the quantity eaten

The plants were analysed for their ability to prevent the development of cancer and to inhibit cell damage, bacterial and fungal growth. Their nutritional benefits were also analysed.

The preventive diet

Some of the plants we analysed are already used by people as medicinal plants. But the parts extracted to make medicines are different to those eaten by the chimps. The plant Nauclea diderrichii is a good example. The fruits and leaves are eaten by chimps but the stem bark is used by people to treat fever and jaundice.

Promising plants such as Tristemma coronatum, whose leaf extract is known to induce sleep in humans, and Beilschmiedia mannii, which is already used to treat lung diseases, were identified.

The leaves of the Tristemma coronatum plant are known to induce sleep.
Author provided.

Other beneficial medicinal plants in their Latin and common names in Côte d’Ivoire dialects respectively include;

  • Klainedoxa gabonensis (kroma)

  • Nauclea diderrichii (badi)

  • Manniophyton fulvum (kolomodia, frafrabié, topué, dobuï ,zohé, zoobo)

  • Beilschmiedia mannii (biliè, tienabi, atiokwo, iréklé, biétou, btei, bhoukéssou)

All are abundant in the Taï National Park.

Our results showed that the tested plants induce an enzyme – quinone reductase – that prevents damage to the body cells. These plants inhibit NF-kB enzyme , which is responsible for causing more than 20% of all reported cases of cancer.

The tested plants showed that 24 extracts (18%) had activity to kill bacteria and six extracts (5%) destroyed yeasts that cause yeast infections. Tristemma coronatum killed both bacteria and yeast whereas Beilschmiedia mannii was active on bacteria, fungi and cancer. This means that the extracts of these plants have potential for medicinal use in humans.

Ground with calcium carbonate, fruit from the Klainedoxa Kabonensis plant is used on abscesses and ulcers. Fruit pulp is applied to swellings.
Author provided.

Developing new medicines

Our study highlighted the high therapeutic and nutritional potential of certain plants which can be considered in developing new medicines.

The ConversationThe next step will be to test these plants on laboratory animals to confirm their benefits. Once the safety and effectiveness is established, we could then start to test them on humans. If these pass the necessary standards, the development of drugs can follow.

Ahoua Constant, Post-Doctoral Fellow with Afrique One Aspire, Nangui Abrogoua University

This article was originally published on The Conversation. Read the original article.

Is it rational to trust your gut feelings? A neuroscientist explains

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Intuition happens as a result of fast processing in the brain.
Valerie van Mulukom, Author provided

By Valerie van Mulukom, Coventry University

Imagine the director of a big company announcing an important decision and justifying it with it being based on a gut feeling. This would be met with disbelief – surely important decisions have to be thought over carefully, deliberately and rationally?

Indeed, relying on your intuition generally has a bad reputation, especially in the Western part of the world where analytic thinking has been steadily promoted over the past decades. Gradually, many have come to think that humans have progressed from relying on primitive, magical and religious thinking to analytic and scientific thinking. As a result, they view emotions and intuition as fallible, even whimsical, tools.

However, this attitude is based on a myth of cognitive progress. Emotions are actually not dumb responses that always need to be ignored or even corrected by rational faculties. They are appraisals of what you have just experienced or thought of – in this sense, they are also a form of information processing.

Intuition or gut feelings are also the result of a lot of processing that happens in the brain. Research suggests that the brain is a large predictive machine, constantly comparing incoming sensory information and current experiences against stored knowledge and memories of previous experiences, and predicting what will come next. This is described in what scientists call the “predictive processing framework”.

This ensures that the brain is always as prepared to deal with the current situation as optimally as possible. When a mismatch occurs (something that wasn’t predicted), your brain updates its cognitive models.

This matching between prior models (based on past experience) and current experience happens automatically and subconsciously. Intuitions occur when your brain has made a significant match or mismatch (between the cognitive model and current experience), but this has not yet reached your conscious awareness.

For example, you may be driving on a country road in the dark listening to some music, when suddenly you have an intuition to drive more to one side of the lane. As you continue driving, you notice that you have only just missed a massive pothole that could have significantly damaged your car. You are glad you relied on your gut feeling even if you don’t know where it came from. In reality, the car in the far distance in front of you made a similar small swerve (since they are locals and know the road), and you picked up on this without consciously registering it.

When you have a lot of experience in a certain area, the brain has more information to match the current experience against. This makes your intuitions more reliable. This means that, as with creativity, your intuition can actually improve with experience.

Biased understanding

In the psychological literature, intuition is often explained as one of two general modes of thinking, along with analytic reasoning. Intuitive thinking is described as automatic, fast, and subconscious. Analytic thinking, on the other hand, is slow, logical, conscious and deliberate.

Many take the division between analytic and intuitive thinking to mean that the two types of processing (or “thinking styles”) are opposites, working in a see-saw manner. However, a recent meta-analysis – an investigation where the impact of a group of studies is measured – has shown that analytic and intuitive thinking are typically not correlated and could happen at the same time.

So while it is true that one style of thinking likely feels dominant over the other in any situation – in particular analytic thinking – the subconscious nature of intuitive thinking makes it hard to determine exactly when it occurs, since so much happens under the bonnet of our awareness.

Indeed, the two thinking styles are in fact complementary and can work in concert – we regularly employ them together. Even groundbreaking scientific research may start with intuitive knowledge that enables scientists to formulate innovative ideas and hypotheses, which later can be validated through rigorous testing and analysis.

Einstein valued intuition.

What’s more, while intuition is seen as sloppy and inaccurate, analytic thinking can be detrimental as well. Studies have shown that overthinking can seriously hinder our decision-making process.

In other cases, analytic thinking may simply consist of post-hoc justifications or rationalisations of decisions based on intuitive thinking. This occurs for example when we have to explain our decisions in moral dilemmas. This effect has let some people refer to analytic thinking as the “press secretary” or “inner lawyer” of intuition. Oftentimes we don’t know why we make decisions, but we still want to have reasons for our decisions.

Trusting instincts

So should we just rely on our intuition, given that it aids our decision-making? It’s complicated. Because intuition relies on evolutionarily older, automatic and fast processing, it also falls prey to misguidances, such as cognitive biases. These are systematic errors in thinking, that can automatically occur. Despite this, familiarising yourself with common cognitive biases can help you spot them in future occasions: there are good tips about how to do that here and here.

Similarly, since fast processing is ancient, it can sometimes be a little out of date. Consider for example a plate of donuts. While you may be attracted to eat them all, it is unlikely that you need this large an amount of sugars and fats. However, in the hunter-gatherers’ time, stocking up on energy would have been a wise instinct.

Thus, for every situation that involves a decision based on your assessment, consider whether your intuition has correctly assessed the situation. Is it an evolutionary old or new situation? Does it involve cognitive biases? Do you have experience or expertise in this type of situation? If it is evolutionary old, involves a cognitive bias, and you don’t have expertise in it, then rely on analytic thinking. If not, feel free to trust your intuitive thinking.

It is time to stop the witch hunt on intuition, and see it for what it is: a fast, automatic, subconscious processing style that can provide us with very useful information that deliberate analysing can’t. We need to accept that intuitive and analytic thinking should occur together, and be weighed up against each other in difficult decision-making situations.

You can learn more about intuition by listening to this episode of our podcast, The Anthill.

The ConversationIf you enjoyed this article and would like to take part in our research about thinking styles and beliefs, please click here for a 20 minute survey.

Valerie van Mulukom, Research Associate in Psychology, Coventry University

This article was originally published on The Conversation. Read the original article.

Birds wearing backpacks trace a path to conservation

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Like many migratory songbirds, tree swallows are experiencing population declines in parts of their breeding range – Julia Baak

By Samantha Knight, University of Guelph and Ryan Norris, University of Guelph

With the arrival of spring, we look forward to the return of hundreds of species of migratory songbirds from their wintering grounds.

Sparrows, swallows, warblers and thrushes, among other songbirds, will be returning from their wintering sites anywhere between the southern United States and distant South America.

Some of these birds will return with a small “backpack” that has recorded their entire migration from their North American breeding grounds to their wintering grounds and back.

Birds provide important ecosystem services, such as preying on insects, dispersing seeds, scavenging carcasses and pollinating plants. Unfortunately, there have been dramatic declines in many migratory songbirds over the past few decades, with some of these populations dropping by more than 80 per cent.

Read more:
How the hard work of wild animals benefits us too

If we are to find ways to slow or reverse these declines, we must first figure out what’s causing them. Climate change, habitat loss and predation by cats are among the leading causes of bird declines.

But with the vast distances these birds move over the course of the year, it can be difficult to pinpoint the main cause for a given species — and where it’s occurring.

Migratory connections

To answer this question, we need to know where individual birds spend their time throughout the year.

We have a good idea of the range — or the total area — the birds occupy during the breeding and wintering periods. But ranges are composed of many populations, and we still have a very poor understanding of how individuals within each of these populations are connected between seasons.

Individuals from different breeding populations may remain segregated during the winter. For example, some ovenbirds winter in the Caribbean whereas others spend their winters in Mexico and Central America.

Or a bird may mix with individuals that originate from other breeding populations, such as bobolinks that mix in South America during the winter.

These patterns of migratory connectivity have critical implications for predicting how migratory songbirds will respond to environmental change.

Habitat loss — deforestation, for example — in one place can have different effects. If habitat loss occurs in a wintering area where breeding populations mix, it may have wide-ranging, yet diffuse, effects on the breeding populations. But if the habitat loss occurs in a wintering area that is occupied by a single breeding population, the effect may be more focused.

For example, habitat loss in South America will likely have range-wide effects on bobolinks, while habitat loss in the Caribbean may only influence a portion of the breeding populations of ovenbirds.

Backpacks for birds

We know that the breeding and wintering populations of most species mix to some extent, but we don’t know by how much or where in the range that occurs. By understanding the migratory network, we can predict how populations across the range will respond to future changes in the environment.

How do we determine where particular individuals go? This is where the tracking “backpacks” come in handy.

These devices, known as “archival light-level geolocators,” weigh less than one gram and are small enough to be carried by songbirds.

A geolocator fitted onto the back of a tree swallow, using a harness that loops around the bird’s legs.
Dayna LeClair

Geolocators record ambient light levels every few minutes while in use. We can then use the geographic variation in sunrise and sunset times as well as day length to locate the individual bird.

We can figure out the bird’s longitude — its east-west position — by comparing solar noon, the midway point between sunrise and sunset, with the time of day (using Greenwich Mean Time). We calculate its latitude — its north-south position — from day length.

Each backpack provides a year’s worth of daily light levels, and a glimpse into one bird’s annual journey.

Tracking tree swallows

In 2011, we began deploying geolocators on tree swallows at 12 sites across their breeding range, from Alaska to Nova Scotia and North Carolina.

These iridescent blue birds with bright white bellies can be seen foraging for flying insects in marshes and fields across Canada and the United States in the spring and early summer. Like many migratory songbirds, tree swallows are experiencing population declines in parts of their breeding range. It is unclear what is driving these declines, however they coincide with declines in several species of birds that also feed on aerial insects.

By 2015, our team, comprising 27 collaborators, had retrieved more than 140 of these devices. We tracked these birds from the breeding sites to their wintering grounds in Mexico, Central America, Florida and the Caribbean.

With this information, we developed the most comprehensive songbird migration map to date. We found evidence for a high degree of mixing within three distinct migratory flyways between the breeding and wintering grounds of tree swallows.

The tree swallow migratory network.
Norris Lab

The tree swallow network

When we analyzed the network, we discovered that tree swallows migrated between their breeding and wintering grounds using three distinct migratory flyways: West of the Rocky Mountains, down the Mississippi River valley and along the Atlantic coast. Breeding populations within these flyways mixed extensively with one another at migration stopover and wintering regions.

We identified important regions within these flyways, such as areas in Florida, Louisiana, North Dakota, South Dakota and the U.S. Midwest, where tree swallows from many different breeding populations congregate. Such areas appear as critical connections within the whole network.

Now that we know more about the connections between breeding and wintering tree swallow populations, we can use this information to investigate threats to declining populations across their range. For example, using chemical markers, range-wide connectivity has been described in eastern North American monarch butterflies and then used to identify the primary threats in this declining population.

The ConversationThis spring, as the migratory songbirds return, take a moment to think about the amazing journey these birds have taken since last autumn — while wearing their backpacks.

Samantha Knight, Lab manager and researcher, University of Guelph and Ryan Norris, Associate Professor, Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists, University of Guelph

This article was originally published on The Conversation. Read the original article.

Ancient ancestors of modern baleen whales were toothy not-so-gentle giants

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A life-like reconstruction of Llanocetus denticrenatus, the second oldest “baleen” whale ever found.
Carl Buell, CC BY-SA

By Felix Georg Marx, Monash University and Robert Ewan Fordyce

The largest living whales – including the gigantic 30-metre blue whale – are fast predatory hunters that support their massive bodies by filtering large volumes of tiny prey from cool near-polar waters. They do this using baleen: plates of a tough substance hanging from their upper jaw.

Evidence of early evolution of baleen whales remains both sparse and controversial, with several ideas competing to explain the origin of baleen-based bulk feeding.

New evidence published today, based on our detailed analysis of a large, 34 million year old Antarctic fossil whale, Llanocetus denticrenatus (“yano-seetus” denticrenatus), shows that this whale was all gums and teeth, but had no baleen.

Read more:
How ‘Alfred’ the whale lost its teeth to become a giant filter feeder

Our findings suggest that large gums gradually became more complex over time and, ultimately, gave rise to baleen – and that these ancient whales became giants before they evolved their baleen feeding habits.

A snapshot of Llanocetus

The specimen is the second oldest “baleen” whale ever found. It is an ancestor of modern baleen whales, such as humpback and blue whales, except that it had no baleen. Instead, this whale had large gums and teeth, likely used to bite prey some 30 centimetres long.

The size of this whale is surprising, given its place in the evolution of whales. Its skull proportions indicate a body length of 8 metres, about the size of a modern minke whale.

Partially reconstructed cast of the skull of Llanocetus. Andrew Grebneff, who prepared much of the fossil, gives an idea of its size.
R Ewan Fordyce, CC BY-SA

The nearly complete skull, minus the tip, is more than 1.6 metres long, and in life was probably more than two metres. Other parts of the skeleton are similarly large and strongly built. There are other unexpected features: Llanocetus has huge openings for jaw muscles, implying a powerful bite, but its teeth are small relative to skull size.

Further, adjacent teeth are separated by wide gaps, and the bony palate has multiple grooves for soft tissues, reminiscent of baleen-related grooves of living species. Yet, we propose that Llanocetus was a predator that bit and sucked its prey, rather than filtering it from the surrounding water like modern baleen whales.

Serendipitous discovery

Field site on Seymour Island, Antarctica, where Llanocetus was discovered.
R Ewan Fordyce, CC BY-SA

Fossil discoveries in new territory are hoped for, and sometimes expected, but there is usually an element of serendipity. One of us, Ewan Fordyce, found the Llanocetus specimen at an inauspicious site while visiting Seymour Island, just east of the Antarctic Peninsula, with a US field party of paleontologists. Rocks on the island include shell-rich marine sediments – with reports of rare whale bone dating to about 34-35 million years.

Fordyce initially saw bone fragments scattered in an eroding gully, and followed them uphill to a mother-lode: hard cemented boulders containing obvious large skull bones and, finally, a distinctive tooth with finger-like projections. Our field party excavated more bones from their source in a layer of icy sandstone, and crated the material for eventual preparation and study in New Zealand.

Toothed “baleen” whales

A cheek tooth of Llanocetus.
R Ewan Fordyce, CC BY-SA

At 34-35 million years, Llanocetus is a little younger than a related whale, the roughly 36 million year old Mystacodon from Peru. These two whales are the oldest described for the lineage leading to modern baleen whales. They lived shortly before long-term global climates changed from warm greenhouse conditions to a cooler icehouse world.

Today’s baleen whales include the fast-swimming rorquals, such as the blue and minke whale, and the slower-moving right whales. These whales are toothless, but have hair-fringed flexible plates of baleen hanging from the upper jaw – hence their name.

Baleen plates have a distinct bony origin on the upper jaw bones, which in modern whales is often marked by a series of openings and grooves for associated blood vessels. We can trace that bony origin in fossil whales back to around 24-30 million years ago. Such fossils from New Zealand represent several groups in the early history of baleen-bearing whales.

For example, Mauicetus is near the start of the rorqual lineage, while Toipahautea is close to the common ancestor of modern rorquals and right whales. Tokarahia traces back to the very base of the baleen whale radiation.

If we go further down the evolutionary tree, we find smaller whales with ancient-looking skulls – the aetiocetids and mammalodontids. These animals lack clear evidence for baleen, but they do have functional teeth. Hence, we often use the formal name Mysticeti for the lineage of true baleen whales, modern and fossil, plus their toothed precursors such as Llanocetus.

Interpreting Llanocetus

Initially, the skull of Llanocetus looks like a hybrid: a flattened, triangular upper jaw like that of a minke whale, but with the teeth and the remaining skull reminiscent of a basal whale, such as Basilosaurus. Detailed comparison of structures amongst baleen and other whales, however, shows that Llanocetus indeed is in the lineage leading to modern baleen whales.

We used tooth form, wear and placement in the jaws to infer feeding. The cheek teeth are separated by wide gaps, but these gaps were not filled by alternating upper and lower teeth to form a mechanical sieve. Rather, polished wear patterns on the tooth crowns indicate that the upper and lower teeth sheared against one another to bite and slice food.

What, then, filled the large gaps between the adjacent teeth? Baleen is unlikely. The bony palate has multiple grooves probably for blood vessels and nerves, but the grooves run directly to the tooth sockets where baleen plates would be unlikely to function, given the shearing movement of the teeth. We propose that the palatal grooves supplied gum tissue both around and between the teeth.

Baleen origins

Earlier research proposed that several of the toothed ancestors of modern baleen whales sucked in small fish with a piston-like tongue. In some species, wear patterns on the teeth indicate that prey items were sheared apart. It seems, however, that no species fed using a combination of teeth and baleen, or fed using teeth to sieve prey from the water.

The ConversationLlanocetus confirms this pattern, and suggests that the earliest whales did not filter feed, but used raptorial and/or suction feeding. Baleen arose only later, probably from the enlarged gums that were already present in Llanocetus. Nevertheless, Llanocetus managed to grow large some 25 million years before our modern gentle giants. Long before orca and giant sperm whales, it was one of the largest predators of its time.

Felix Georg Marx, Post doctoral research fellow in evolutionary biology, Monash University and Robert Ewan Fordyce, Professor in paleontology

This article was originally published on The Conversation. Read the original article.

Can Artificial Intelligence help find alien intelligence?

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Artist’s impression of Proxima b, a planet orbiting the star Proxima Centauri within the closest known star system outside of our solar system.
(ESO/M. Kornmesser), CC BY-SA

By Michael P. Oman-Reagan, Memorial University of Newfoundland

In the search for extraterrestrial intelligence (SETI), we’ve often looked for signs of intelligence, technology and communication that are similar to our own.

But as astronomer and SETI trailblazer Jill Tarter points out, that approach means searching for detectable technosignatures, like radio transmissions, not searching for intelligence.

Now scientists are considering whether artificial intelligence (AI) could help us search for alien intelligence in ways we haven’t even thought of yet.

‘Decoding’ intelligence

As we think about extraterrestrial intelligence it’s helpful to remember humans are not the only intelligent life on Earth.

Chimpanzees have culture and use tools, spiders process information with webs, cetaceans have dialects, crows understand analogies and beavers are great engineers. Non-human intelligence, language, culture and technology are all around us.

A capuchin (Sapajus libidinosus) using a stone tool (T. Falótico). An octopus (Amphioctopus marginatus) carrying shells as shelter (N. Hobgood).
(Wikimedia/Tiago Falótico, Nick Hobgood), CC BY-NC-SA

Alien intelligence could look like an octopus, an ant, a dolphin or a machine — or be radically different from anything on Earth.

We often imagine extraterrestrial life relative to our ideas about difference, but those ideas aren’t even universal on Earth and are unlikely to be universal across interstellar space.

If some of us have only recently recognized non-human intelligence on Earth, what could we be missing when we imagine extraterrestrial life?

In early 2018, astronomers, neuroscientists, anthropologists, AI researchers, historians and others gathered for a “Decoding Alien Intelligence” workshop at the SETI Institute in Silicon Valley. Astrobiologist Nathalie Cabrol organized the workshop around her 2016 paper “Alien mindscapes,” where she calls for a new SETI road map and a long-term vision for “the search for life as we do not know it.”

In her paper, Cabrol asks how SETI can move past “looking for other versions of ourselves” and think “outside of our own brains” to imagine truly different extraterrestrial intelligence.

Thinking differently

Silicon Valley is famous for valuing “disruptive” thinking and this culture intersects with SETI research. Ever since the U.S. government stopped funding SETI in the mid-1990s, Silicon Valley ideas, technology and funding have been increasingly important.

For example, the SETI Institute’s Allen Telescope Array is named after Microsoft co-founder Paul Allen, who contributed over US$25 million to the project. And, in 2015, technology investor Yuri Milner announced Breakthrough Listen, a 10-year US$100 million SETI initiative.

Now, the SETI Institute, NASA, Intel, IBM and other partners are tackling space science problems through an AI research and development program called the Frontier Development Lab.

Read more:
Why I believe we’ll find aliens – leading expert on search for intelligent extra-terrestrial life

Lucianne Walkowicz, the Astrobiology Chair at the Library of Congress, described one AI-based method as “signal agnostic searching” at Breakthrough Discuss in 2017.

Walkowicz explained that this means using machine learning methods to look at any set of data without predetermined categories and instead let that data cluster into their “natural categories.” The software then lets us know what stands out as outliers. These outliers could then be the target of additional investigations.

It turns out that SETI researchers think AI might be useful in their work because they believe machine learning is good at spotting difference.

But its success depends on how we — and the AI we create — conceptualize the idea of difference.

Smarter than slime mould?

Thinking outside our brains also means thinking outside our scientific, social and cultural systems. But how can we do that?

AI has been used to look for simulations of what researchers imagine alien radio signals might look like, but now SETI researchers hope it can find things we aren’t yet looking for.

Graham Mackintosh, an AI consultant at the SETI Institute workshop, said extraterrestrials might be doing things we can’t even imagine, using technologies so different we don’t even think to look for them. AI, he proposed, might be able to do that advanced thinking for us.

We may not be able to make ourselves smarter, but perhaps, Mackintosh suggested, we can make machines that are smarter for us.

In a keynote at this year’s Breakthrough Discuss conference, astrophysicist Martin Rees shared a similar hope, that AI could lead to “intelligence which surpasses humans as much as we intellectually surpass slime mould.”

First contact

If we met extraterrestrial slime mould, what could we assume about its intelligence? One challenge of SETI is that we don’t know the limits of life or intelligence, so we need to be open to all possible forms of difference.

We might find intelligence in forms that Euro-American science has historically disregarded: Microbial communities, insects or other complex systems like the symbiotic plant-fungus relationships in mycorrhizal networks that learn from experience.

Intelligence might appear in atmospheres or geology at a planetary scale, or as astrophysical phenomena. What appears to be a background process in the universe, or just part of what we think of as nature, could turn out to be intelligence.

Consider that the largest living thing on Earth may be an Armillaria ostoyae fungus in Eastern Oregon’s Blue Mountains, which extends to 10 square kilometres and is between 2,000 and 9,000 years old.

While this fungus may not be what most people think of as intelligence, it reminds us to think about the unexpected when searching for life and intelligence, and of what we might be missing right under our feet.

Parts of the Armillaria ostoyae organism include the mushrooms, the black rhizomorphs and the white mycelial felts.
(USDA/Forest Service/Pacific Northwest Region)

Thinking differently about intelligence means understanding that anything we encounter could be first contact with intelligent life. This might include our first encounter with artificial general intelligence (AGI), also called Strong AI, something closer to the sentient computer HAL 9000 from 2001: A Space Odyssey or Data from Star Trek: The Next Generation.

As we work with machine learning to expand the SETI search, we also need social sciences to understand how our ideas shape the future of AI — and how AI will shape the future of our ideas.

Interdisciplinary futures

To avoid a human-centred point of view in SETI we need to consider how we encode ideas about difference into AI and how that shapes the outcomes. This is vital for finding and recognizing intelligence as we don’t yet know it.

Some of the methods used in anthropology can help us identify ideas about difference that we’ve naturalized — concepts so familiar they seem invisible, like the divides many still see between nature and culture or biology and technology, for example.

Recent research on algorithms reveals how our naturalized ideas shape the technology we create and how we use it. And Microsoft’s infamous AI chat bot Tay reminds us the AI we create can easily reflect the worst of those ideas.

Read more:
Teaching chatbots how to do the right thing

We may never entirely stop building bias into search engines and search strategies for SETI, or coding it into AI. But through collaborations between scientists and social scientists we can think critically about how we conceptualize difference.

The ConversationA critical, interdisciplinary approach will help us understand how our ideas about difference impact lives, research and possibilities for the future both here on Earth and beyond.

Michael P. Oman-Reagan, Vanier Scholar, Department of Anthropology, Memorial University of Newfoundland

This article was originally published on The Conversation. Read the original article.