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Collective intelligence out-diagnoses even professionals
The Human Diagnosis Project project is building the world's "open medical intelligence" system.
- The Human Diagnosis Project can develop medical diagnoses with startling accuracy.
- The platform combines the knowledge of medical professionals and artifical intelligence.
- The goal of the project is to provide open, readily available high-level guidance and training to health care professionals across the globe.
The world-class Mayo Clinic is often the place patients go for a second opinion on a medical diagnosis. It's a good thing they do. According to a report issued by the clinic in 2017, 88 percent of them return home with either a completely different diagnosis or a significantly altered one. Only 12 percent receive confirmation of their doctors' original conclusions.
It's hard to overstate the life-and-death importance of medical misdiagnoses, and with all the artificial intelligence and data collection tools out there, you'd think there might be a way to improve on these statistics. This said, the goal of the Human Diagnosis project, or "Human Dx," (a triple pun their site explains) is to create the world's open medical intelligence system, a "collective intelligence" that can produce vastly improved diagnostic accuracy.
In early March, JAMA published the results of an experiment conducted by Human Dx in cooperation with Harvard, and the results were impressive. Where 54 individual human medical specialists correctly diagnosed 156 test cases 66.3 percent of the time, collective intelligence achieved an 85.5 percent accuracy rate. Nine medical professionals contributed to the collective intelligence conclusions.
Human Dx founder Jayanth Komarneni tells Big Think that, "We can get numbers in the 97th, 98th [percentile], and even — if we have sufficiently large numbers of participants — we can get to super intelligent results. That means that it outperforms 100 percent of individual participants."
About Human Dx
The Human Dx project is a partnership between the social, public, and private sectors — in the U.S., it's a 501 (c)(3) not-for-profit/public-benefit corporation. According to Komarneni, Human Dx's business model is as free of cost to users as possible while still generating enough income to be self-sustaining. There are now nearly 20,000 medical professionals in almost 80 countries contributing. Among Human Dx's partners are, as the company states: the American Medical Association, the Association of American Medical Colleges, American Board of Medical Specialties, and the American Board of Internal Medicine. They're also working in collaboration with researchers at Harvard, Johns Hopkins., University of California San Francisco, Berkeley, and MIT.
While diagnoses produced by Human Dx do bring together the opinions of multiple medical professionals, it's far from a simple voting system. It incorporates its own massive data set, machine learning, and artificial intelligence in addition to the input from medical professionals to develop its diagnoses. In designing their collective intelligence, says Komarneni, Human Dx had to first re-think the idea of open intelligence itself.
"We believe that open intelligence is the third form of open knowledge," he explains. The first was open source-protocols such as those on which the internet is based, as well as operating systems such as Linux. These protocols enabled the second form, open content: Wikipedia, data libraries, and so on. Open intelligence combines the first two: "And when you think about A.I. in the context of software," says Komarneni, "it really is code which is smartly delivering content to you based on what you put into the system."
The importance of open intelligence is that without it being available at low cost or free, the cost of A.I. is going to be so prohibitive that it'll "exacerbate, as opposed to close, income, health, and other disparities in society," warns Komarneni. Nowhere will the ramification be more serious than in health care, since "there is nothing we care more about than the well-being of the people we love and ourselves."
How Human Dx collective intelligence works
Collective intelligence in the Human Dx project is not unlike a panel of participants, when are referred to as "agents." Some of these are medical professionals, but they may also include the outputs of other systems. For example, Komarneni mentions that it's entirely possible IBM's Watson could be one of these agents, or even a data set from the National Institutes of Health.
Of course, individual agents, even the human participants, express themselves in their own ways — is a lump "blue" or "blueberry-colored," for example — not to mention that contributions from some agents such as A.I. or datasets may be in the form of raw data. Before any meaningful synthesis of all these opinions can be performed, the first step is to convert them all into a common language of some sort. Human Dx's AI uses natural language processing, text prediction, and medical ontologies to derive these translations as the process's first step.
Human Dx establishes the capability, or CQ ("clinical quotient"), of each agent. To do this they rank agents' skills using test cases with known diagnoses, including "some of the most wickedly complex cases," says Komarneni. This allows Human Dx to determine how accurate agents' diagnoses can be expected to be, and how heavily they should be weighted against other participants' contributions in solving the current case.
A.I. joins the panel
At this point, the agents' inputs are synthesized to derive the most likely diagnosis, and this is combined in an A.I. model with all of the aggregated case data that's ever been captured by Human Dx — interactions in the "tens of millions" — including how "lots of other participants over many other cases have solved these cases." This A.I. model then joins the panel in arriving at the final diagnosis.
"And those [agents] combined," says Komarneni, "are how we can get to results that outperform the vast majority of individual participants."
The Harvard and Johns Hopkins studies
The Harvard study published in JAMA is the first public demonstration of the Human Dx system as a diagnostic tool. Working with an international cohort of medical students and professionals, the results were unquestionably amazing. There were 2069 users working 1572 cases — again, these were cases with known correct answers — from the Human Dx data set. About 60 percent of the participants were residents or fellows, 20 percent were attending physicians, and another 20 percent were medical students. In the study, as more medical professionals were added to the collective intelligence "panel," up to nine individuals, its accuracy consistently rose. Physicians who weren't specialists in their test-case areas achieved just a 62.5 percent accuracy score.
A previous study published in JAMA in January, and done in cooperation with Johns Hopkins, looked at Human Dx as an automatic platform for assessing the diagnostic abilities of health care professionals and students. That the scores of participants looking at 11,023 case simulations were consistent with their training level shows, in Komarneni words, "that we provided a valid, quantitative, scalable measure of medical reasoning." While he admits this doesn't sound like a big deal, it is, since it offers a far more accurate and scalable option to current multiple-choice assessments, which have been shown to correspond poorly to real-world diagnostic skills.
The future of health care and Human Dx
Komarneni says that there are basically only two ways to provide global universal health care, a pressing need since, "Almost half the world has no access to essential health services." One way, he says, would be to create a God-like A.I. system to provide health care to everyone, but, "We know that's not going to happen." God-like AI is just too hard, potentially requiring having to know everything about a patient from the tiniest details — say, the quantum behavior of electrons in mitochondria — to the huge, as in the kind of environment a patient lived in as a child.
In addition, Komarneni says, "In a world where data is locked up in many disparate silos, there isn't going to be a single collective agent. There's going to be a collective of many intelligent agents, both human and machine. The key is how do you integrate intelligence into larger buckets of intelligence than can solve the world's hardest problems."
This is where the Human Dx project, and the second approach, comes in. It actually has two components:
- The first is the expansion of existing medical professionals' diagnostic accuracy skills by providing them access to the Human Dx platform and its collective intelligence as a diagnostic tool.
- The second is helping to train new professionals, and Human Dx Training is already offering this on the Human Dx site.
For those concerned with privacy in a system such as Human Dx, Komarneni says it'll be a non-issue, explaining with an example. When two people converse, "We don't have access to the underlying data of each others' minds. We're agents that are interacting with each other to gain relevant and useful information from each other." Similarly, Human Dx's system of interacting agents doesn't require the exposure of patients' personal data. What's shared with Human Dx are the conclusions agents draw from that data, not the data itself. In the case of a dataset operating as an agent, the data would be anonymized.
Human Dx's interest in all this is developing a platform it hopes others find uses for. "We believe we're just building the enabling technology that many other stakeholders could use." As examples, Komarneni imagines, "The VA could implement their own version of this. Kaiser Permanente could implement their own version. Employers could contract with us or with their own insurers. You could even also have individual and group practices use Human Dx software to serve patients directly."
Human Dx is currently looking at ways to open up as much of the project for non-professionals as possible, and they've already made a start: On their home page is a diagnosis cloud — mouse over the various blue bubbles to see different conditions, and then click for further details. In addition, just beneath the cloud is a search field with which you can look up diseases and symptoms.
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The father of all giant sea bugs was recently discovered off the coast of Java.
- A new species of isopod with a resemblance to a certain Sith lord was just discovered.
- It is the first known giant isopod from the Indian Ocean.
- The finding extends the list of giant isopods even further.
Humanity knows surprisingly little about the ocean depths. An often-repeated bit of evidence for this is the fact that humanity has done a better job mapping the surface of Mars than the bottom of the sea. The creatures we find lurking in the watery abyss often surprise even the most dedicated researchers with their unique features and bizarre behavior.
A recent expedition off the coast of Java discovered a new isopod species remarkable for its size and resemblance to Darth Vader.
The ocean depths are home to many creatures that some consider to be unnatural.
According to LiveScience, the Bathynomus genus is sometimes referred to as "Darth Vader of the Seas" because the crustaceans are shaped like the character's menacing helmet. Deemed Bathynomus raksasa ("raksasa" meaning "giant" in Indonesian), this cockroach-like creature can grow to over 30 cm (12 inches). It is one of several known species of giant ocean-going isopod. Like the other members of its order, it has compound eyes, seven body segments, two pairs of antennae, and four sets of jaws.
The incredible size of this species is likely a result of deep-sea gigantism. This is the tendency for creatures that inhabit deeper parts of the ocean to be much larger than closely related species that live in shallower waters. B. raksasa appears to make its home between 950 and 1,260 meters (3,117 and 4,134 ft) below sea level.
Perhaps fittingly for a creature so creepy looking, that is the lower sections of what is commonly called The Twilight Zone, named for the lack of light available at such depths.
It isn't the only giant isopod, far from it. Other species of ocean-going isopod can get up to 50 cm long (20 inches) and also look like they came out of a nightmare. These are the unusual ones, though. Most of the time, isopods stay at much more reasonable sizes.
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During an expedition, there are some animals which you find unexpectedly, while there are others that you hope to find. One of the animal that we hoped to find was a deep sea cockroach affectionately known as Darth Vader Isopod. The staff on our expedition team could not contain their excitement when they finally saw one, holding it triumphantly in the air! #SJADES2018
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What benefit does this find have for science? And is it as evil as it looks?
The discovery of a new species is always a cause for celebration in zoology. That this is the discovery of an animal that inhabits the deeps of the sea, one of the least explored areas humans can get to, is the icing on the cake.
Helen Wong of the National University of Singapore, who co-authored the species' description, explained the importance of the discovery:
"The identification of this new species is an indication of just how little we know about the oceans. There is certainly more for us to explore in terms of biodiversity in the deep sea of our region."
The animal's visual similarity to Darth Vader is a result of its compound eyes and the curious shape of its head. However, given the location of its discovery, the bottom of the remote seas, it may be associated with all manner of horrifically evil Elder Things and Great Old Ones.
New study analyzes gravitational waves to confirm the late Stephen Hawking's black hole area theorem.
- A new paper confirms Stephen Hawking's black hole area theorem.
- The researchers used gravitational wave data to prove the theorem.
- The data came from Caltech and MIT's Advanced Laser Interferometer Gravitational-Wave Observatory.
The late Stephen Hawking's black hole area theorem is correct, a new study shows. Scientists used gravitational waves to prove the famous British physicist's idea, which may lead to uncovering more underlying laws of the universe.
The theorem, elaborated by Hawking in 1971, uses Einstein's theory of general relativity as a springboard to conclude that it is not possible for the surface area of a black hole to become smaller over time. The theorem parallels the second law of thermodynamics that says the entropy (disorder) of a closed system can't decrease over time. Since the entropy of a black hole is proportional to its surface area, both must continue to increase.
As a black hole gobbles up more matter, its mass and surface area grow. But as it grows, it also spins faster, which decreases its surface area. Hawking's theorem maintains that the increase in surface area that comes from the added mass would always be larger than the decrease in surface area because of the added spin.
Will Farr, one of the co-authors of the study that was published in Physical Review Letters, said their finding demonstrates that "black hole areas are something fundamental and important." His colleague Maximiliano Isi agreed in an interview with Live Science: "Black holes have an entropy, and it's proportional to their area. It's not just a funny coincidence, it's a deep fact about the world that they reveal."
What are gravitational waves?
Gravitational waves are "ripples" in spacetime, predicted by Albert Einstein in 1916, that are created by very violent processes happening in space. Einstein showed that very massive, accelerating space objects like neutron stars or black holes that orbit each other could cause disturbances in spacetime. Like the ripples produced by tossing a rock into a lake, they would bring about "waves" of spacetime that would spread in all directions.
As LIGO shared, "These cosmic ripples would travel at the speed of light, carrying with them information about their origins, as well as clues to the nature of gravity itself."
The gravitational waves discovered by LIGO's 3,000-kilometer-long laser beam, which can detect the smallest distortions in spacetime, were generated 1.3 billion years ago by two giant black holes that were quickly spiraling toward each other.
What Stephen Hawking would have discovered if he lived longer | NASA's Michelle Thaller | Big Think www.youtube.com
Confirming Hawking's black hole area theorem
The researchers separated the signal into two parts, depending on whether it was from before or after the black holes merged. This allowed them to figure out the mass and spin of the original black holes as well as the mass and spin of the merged black hole. With this information, they calculated the surface areas of the black holes before and after the merger.
"As they spin around each other faster and faster, the gravitational waves increase in amplitude more and more until they eventually plunge into each other — making this big burst of waves," Isi elaborated. "What you're left with is a new black hole that's in this excited state, which you can then study by analyzing how it's vibrating. It's like if you ping a bell, the specific pitches and durations it rings with will tell you the structure of that bell, and also what it's made out of."
The surface area of the resulting black holes was larger than the combined area of the original black holes. This conformed to Hawking's area law.
As a form of civil disobedience, hacking can help make the world a better place.
- Hackers' motivations range from altruistic to nihilistic.
- Altruistic hackers expose injustices, while nihilistic ones make society more dangerous.
- The line between ethical and unethical hacking is not always clear.
The following is an excerpt from Coding Democracy by Maureen Webb. Reprinted with Permission from The MIT PRESS. Copyright 2020.
As people begin to hack more concertedly at the structures of the status quo, the reactions of those who benefit from things as they are will become more fierce and more punitive, at least until the "hackers" succeed in shifting the relevant power relationships. We know this from the history of social movements. At the dawning of the digital age, farmers who hack tractors will be ruthlessly punished.
Somewhere on the continuum of altruism and transgression is the kind of hacking that might lead the world toward more accountable government and informed citizenries.
Of course, it must be acknowledged that hackers are engaged in a whole range of acts, from the altruistic to the plainly nihilistic and dangerous. On the altruistic side of the continuum, they are creating free software (GNU/Linux and other software under GPL licenses), Creative Commons (Creative Commons licensing), and Open Access (designing digital interfaces to make public records and publicly funded research accessible). They are hacking surveillance and monopoly power (creating privacy tools, alternative services, cooperative platforms, and a new decentralized internet) and electoral politics and decision making (Cinque Stelle, En Comú, Ethelo, Liquid Democracy, and PartidoX). They have engaged in stunts to expose the technical flaws in voting, communications, and security systems widely used by, or imposed on, the public (by playing chess with Germany's election voting machines, hacking the German Bildschirmtext system, and stealing ministers' biometric identifiers). They have punished shady contractors like HackingTeam, HBGary, and Stratfor, spilling their corporate dealings and personal information across the internet. They have exposed the corruption of oligarchs, politicians, and hegemons (through the Panama Papers, WikiLeaks, and Xnet).
More notoriously, they have coordinated distributed denial of service (DDoS) attacks to retaliate against corporate and government conduct (such as the Anonymous DDoS that protested PayPal's boycott of WikiLeaks; the ingenious use of the Internet of Things to DDoS Amazon; and the shutdown of US and Canadian government IT systems). They have hacked into databases (Manning and Snowden), leaked state secrets (Manning, Snowden, and WikiLeaks), and, in doing so, betrayed their own governments (Manning betrayed US war secrets, and Snowden betrayed US security secrets). They have interfered with elections (such as the hack and leak of the Democratic National Committee in the middle of the 2016 US election) and sown disinformation (the Russian hacking of US social media). They have interfered with property rights in order to assert user ownership, self-determination, and free software's four freedoms (farmers have hacked DRM code to repair their tractors, and Geohot unlocked the iPhone and hacked the Samsung phone to allow users administrator-level access to their devices) and to assert open access to publicly funded research. They have created black markets to evade state justice systems (such as Silk Road on the dark web) and cryptocurrencies that could undermine state-regulated monetary systems. They have meddled in geopolitics as free agents (Anonymous and the Arab Spring, and Julian Assange and his conduct with the Trump campaign). They have mucked around in and could potentially impair or shut down critical infrastructure. (The notorious "WANK worm" attack on NASA is an early, notorious, example, but hackers could potentially target banking systems, stock exchanges, electrical grids, telecommunications systems, air traffic control, chemical plants, nuclear plants, and even military "doomsday machines.")
It is impossible to calculate where these acts nudge us as a species. Some uses of hacking — such as the malicious, nihilistic hacking that harms critical infrastructure and threatens lives, and the hacking in cyberwarfare that injures the critical interests of other countries and undermines their democratic processes — are abhorrent and cannot be defended. The unfolding digital era looks very grim when one considers the threat this kind of hacking poses to peace and democracy combined with the dystopian direction states and corporations are going with digital tech.
But somewhere on the continuum of altruism and transgression is the kind of hacking that might lead the world toward more accountable government and informed citizenries, less corrupt and unfair economic systems, wiser public uses of digital tech, more self-determination for the ordinary user, fairer commercial contracts, better conditions for innovation and creativity, more decentralized and robust infrastructure systems, and an abolition of doomsday machines. In short, some hacking might move us toward a digital world in which there are more rather than fewer democratic, humanist outcomes.
It is not clear where the line between "good" and "bad" hacking should be drawn or how to regulate it wisely in every instance. Citizens should inform themselves and begin to consider this line-drawing seriously, however, since we will be grappling intensely with it for the next century or more. My personal view is that digital tech should not be used for everything. I think we should go back to simpler ways of running electrical grids and elections, for example. Systems are more resilient when they are not wholly digital and when they are smaller, more local, and modular. Consumers should have analogue options for things like fridges and cars, and design priorities for household goods should be durability and clean energy use, not interconnectedness.
In setting legal standards, prohibiting something and enforcing the prohibition are two different things. Sometimes a desired social norm can be struck by prohibiting a thing and not enforcing it strenuously. And the law can also recognize the constructive role that civil disobedience plays in the evolution of social norms, through prosecutorial discretion and judicial discretion in sentencing.
Wau Holland told the young hackers at the Paradiso that the Chaos Computer Club was "not just a bunch of techno freaks: we've been thinking about the social consequences of technology from the very beginning." Societies themselves, however, are generally just beginning to grapple with the social consequences of digital technology and with how to characterize the various acts performed by hackers, morally and legally. Each act raises a set of complex questions. Societies' responses will be part of the dialectic that determines where we end up. Should these various hacker acts be treated as incidents of public service, free speech, free association, legitimate protest, civil disobedience, and harmless pranksterism? Or should they be treated as trespass, tortious interference, intellectual property infringement, theft, fraud, conspiracy, extortion, espionage, terrorism, and treason? I invite you to think about this as you consider how hacking has been treated by societies to date.