Category Archives: Ai

Artificial intelligence "is rewiring our modern conception of healthcare delivery," according to a new Accenture report that shows an array of clinical AI applications are already well on their way to saving the industry $150 billion over the next 10 years.

In the shorter term, the report forecasts a 40 percent compound annual growth rate between now and 2021, with acquisitions of AI startups proceeding at a feverish pace.

[Also:With machine learning and AI in healthcare, can you speak the language?]

The technology represents "a significant opportunity for industry players to manage their bottom line in a new payment landscape," according to the report, which examined 10 different AI applications, ranked by their potential for cost savings. Robot-assisted surgery $40 billion Virtual nursing assistants $20 billion Administrative workflow assistance $18 billion Fraud detection $17 billion Dosage error reduction $16 billion Connected machines $14 billion Clinical trial participant identifier $13 billion Preliminary diagnosis $5 billion Automated image diagnosis $3 billion Cybersecurity $2 billion "As these, and other AI applications gain more experience in the field, their ability to learn and act will continually lead to improvements in precision, efficiency and outcomes," said Accenture researchers.

But as the industry rushes headlong to embrace a technology that "thinks and pays for itself," there are some important considerations to keep in mind, according to the report.

[Also:As AI spreads through healthcare, ethical questions arise]

First, it's key to plan for the way the healthcare workforce will be affected as the nature of employment changes with automation. It's a tricky challenge to "make the best use of both humans and AI talent," but it can be done. "For instance, AI voice-enabled symptom checkers triage patients to lower-cost retail or urgent care settings and direct patients to the emergency department only when emergency care is necessary."

Sound organizational strategy is also critical. To make the most AI, hospitals should make expertise in emerging technology a central part of their structure and governance: "For instance, assigning a lead who is tasked with keeping apprised of AI adoption within the organization," according to the report. "Governance and the operating model should also be revamped to align with an AI-enabled organization."

Patient engagement is another emerging avenue for artificial intelligence: Consumers are increasingly used to AI tools, and see them as useful and valuable. AI "can magnify care reach by integrating health data across platforms," said researchers. "However, as new technology is introduced, various data sources must be connected to enable a seamless experience for patients."

Finally, security is a critical concern. "Parties in the ecosystem will need to work together in an ethical way, and be secure in how they manage critical information on patients," according to the report. "As AI delivers benefits of greater efficiency, transparency and interoperability, organizations must maintain a clear focus on informational security."

Twitter:@MikeMiliardHITN Email the writer: mike.miliard@himssmedia.com

Like Healthcare IT News on Facebook and LinkedIn

See the original post here:

Healthcare AI poised for explosive growth, big cost savings - Healthcare IT News

Modern artificial intelligence is smart enough to beat humans at chess, understand speech, and even drive a car.

But one area where machine-learning algorithms still struggle is explaining to humans how and why theyre making particular decisions. That can be fine if computers are just playing games, but for more serious applications people are a lot less willing to trust a machine whose thought processes they cant understand.

If AI is being used to make decisions about who to hire or whether to extend a bank loan, people want to make sure the algorithm hasnt absorbed race or gender biases from the society that trained it. If a computer is going to drive a car, engineers will want to make sure it doesnt have any blind spots that will send it careening off the road in unexpected situations. And if a machine is going to help make medical diagnoses, doctors and patients will want to know what symptoms and readings its relying on.

If you go to a doctor and the doctor says, Hey, you have six months to live, and offers absolutely no explanation as to why the doctor is saying that, that would be a pretty poor doctor, says Sameer Singh, an assistant professor of computer science at the University of California at Irvine.

Singh is a coauthor of a frequently cited paper published last year that proposes a system for making machine-learning decisions more comprehensible to humans. The system, known as LIME, highlights parts of input data that factor heavily in the computers decisions. In one example from the paper, an algorithm trained to distinguish forum posts about Christianity from those about atheism appears accurate at first blush, but LIME reveals that its relying heavily on forum-specific features, like the names of prolific posters.

Developing explainable AI, as such systems are frequently called, is more than an academic exercise. Its of growing interest to commercial users of AI and to the military. Explanations of how algorithms are thinking make it easier for leaders to adopt artificial intelligence systems within their organizationsand easier to challenge them when theyre wrong.

If they disagree with that decision, they will be way more confident in going back to the people who wrote that and say no, this doesnt make sense because of this, says Mark Hammond, cofounder and CEO of AI startup Bonsai.

Last month, the Defense Advanced Research Projects Agency signed formal agreements with 10 research teams in a four-year, multimillion-dollar program designed to develop new explainable AI systems and interfaces for delivering the explanations to humans. Some of the teams will work on systems for operating simulated autonomous devices, like self-driving cars, while others will work on algorithms for analyzing mounds of data, like intelligence reports.

Each year, well have a major evaluation where well bring in groups of users who will sit down with these systems, says David Gunning, program manager in DARPAs Information Innovation Office. Gunning says he imagines that by the end of the program, some of the prototype projects will be ready for further development for military or other use.

Deep learning, loosely inspired by the networks of neurons in the human brain, uses sample data to develop multilayered sets of huge matrices of numbers. Algorithms then harness those matrices to analyze and categorize data, whether theyre looking for familiar faces in a crowd or trying to spot the best move on a chess board. Typically, they process information starting at the lowest level, whether thats the individual pixels from an image or individual letters of text. The matrices are used to decide how to weight each facet of that data through a series of complex mathematical formulas. While the algorithms often prove quite accurate, the large arrays of seemingly arbitrary numbers are effectively beyond human comprehension.

The whole process is not transparent, says Xia Ben Hu, an assistant professor of computer science and engineering at Texas A&M and leader of one of the teams in the DARPA program. His groupaims to produce what it calls shallow models: mathematical constructs that behave, at least in certain cases, similarly to deep-learning algorithms while being simple enough for humans to understand.

Another team, from the Stanford University spin-off research group SRI International, plans to use what are called generative adversarial networks. Those are pairs of AI systems in which one is trained to produce realistic data in a particular category and the other is trained to distinguish the generated data from authentic samples. The purpose, in this case, is to generate explanations similar to those that might be given by humans.

The team plans to test its approach on a data set called MovieQA, which consists of 15,000 multiple choice questions about movies along with data like their scripts and subtitled video clips.

You have the movie, you have scripts, you have subtitles. You have all this rich data that is time-synched in situations, says SRI senior computer scientist Mohamed Amer. The question could be, who was the lead actor in The Matrix?

Ideally, the system would not only deliver the correct answer, it would let users highlight certain sections of the questions and answers to see the sections of the script and film it used to figure out the answer.

You hover over a verb, for example, it will show you a pose of the person, for example, doing the action, Amer says. The idea is to kind of bring it down to an interpretable feature the person can actually visualize, where the person is not a machine-learning developer but is just a regular user of the system.

Steven Melendez is an independent journalist living in New Orleans.

More

Read the original here:

Why The Military And Corporate America Want To Make AI Explain Itself - Fast Company

World War II

conflict that involved virtually every part of the world during the years 193945. The principal belligerents were the Axis powers Germany, Italy, and Japan and the Allies France, Great Britain, the...

Read this Article

10 Deadly Animals that Fit in a Breadbox

Everybody knows that big animals can be deadly. Lions, for instance, have sharp teeth and claws and are good at chasing down their prey. Shark Week always comes around and reminds us that although shark...

Read this List

Syrian Civil War

In March 2011 Syrias government, led by Pres. Bashar al-Assad, faced an unprecedented challenge to its authority when pro- democracy protests erupted throughout the country. Protesters demanded an end...

Read this Article

September 11 attacks

series of airline hijackings and suicide attacks committed by 19 militants associated with the Islamic extremist group al-Qaeda against targets in the United States, the deadliest terrorist attacks on...

Read this Article

The Middle East: Fact or Fiction?

Take this Geography True or False Quiz at Encyclopedia Britannica to test your knowledge of Syria, Iraq, and other countries within the Middle East.

Take this Quiz

10 Places to Visit in the Solar System

Having a tough time deciding where to go on vacation? Do you want to go someplace with startling natural beauty that isnt overrun with tourists? Do you want to go somewhere where you wont need to take...

Read this List

7 Drugs that Changed the World

People have swallowed elixirs, inhaled vapors, and applied ointments in the name of healing for millennia. But only a small number of substances can be said to have fundamentally revolutionized medicine....

Read this List

World Tour

Take this geography quiz at Encyclopedia Britannica and test your knowledge of popular destinations.

Take this Quiz

American Civil War

four-year war (186165) between the United States and 11 Southern states that seceded from the Union and formed the Confederate States of America. Prelude to war The secession of the Southern states (in...

Read this Article

Geography 101: Fact or Fiction?

Take this Geography True or False Quiz at Encyclopedia Britannica to test your knowledge of various places across the globe.

Take this Quiz

Vietnam War

(195475), a protracted conflict that pitted the communist government of North Vietnam and its allies in South Vietnam, known as the Viet Cong, against the government of South Vietnam and its principal...

Read this Article

World War I

an international conflict that in 191418 embroiled most of the nations of Europe along with Russia, the United States, the Middle East, and other regions. The war pitted the Central Powers mainly Germany,...

Read this Article

View post:

Ai | ancient city, Canaan | Britannica.com

For example, Adobe's Experience Cloud, which helps brands manage customer interactions and advertising, processes 100 trillion transactions every year.

Narayen said the data gathered from those transactions will in turn feed into Adobe Sensei, which will do things like transform paper documents into editable digital files, create predictive models, and change expressions in photographs with a few clicks.

"It's a way to really bring creativity to the masses. And it's a way to enable everybody to be a creator," Narayen said. "We partner with great companies like Nvidia who are able to process this in real time, but it's all the magic that's created by our product folks."

All this ties in to what Narayen dubbed Adobe's two tailwinds that helped the software giant deliver better-than-expected earnings on Tuesday: individual creativity and a changing business landscape.

"People want to create and businesses want to transform, and we are mission-critical to both of them. We are driving tremendous innovation and executing," Narayen said.

And whether that execution is proven by 49 percent growth in Adobe's Premiere Pro video editing platform or an 86 percent jump in recurring revenues, Narayen said knowing what creators want is the key to Adobe's success.

"I think using the right lens and unleashing innovation on our product development, that's how we do it," the CEO said. "If you're a creative professional, we're just as mission-critical as a Bloomberg terminal might be for somebody in the financial community. And on the enterprise side, when small and medium businesses want to create an online digital presence, and they want to have commerce as part of their future, they use us to enable themselves to have this online presence."

When Cramer asked whether Narayen communicated these sentiments to President Donald Trump at Monday's technology council meeting at the White House, the CEO responded diplomatically.

"Design and aesthetics have never been more important, and I think as it relates to modernizing government, all businesses are transforming so that the customer experience is front and center. There's no reason why the government shouldn't do exactly the same," Narayen said.

The Adobe chief added that when it came to the meeting's central topics, modernizing the government and enhancing the skills of the U.S. workforce, he emphasized STEAM over STEM, the well known acronym for the sciences, technology, engineering and mathematics, adding arts to the mix as an equally important skill set to master.

With regards to job creation, Narayen issued somewhat of a warning to the country's leaders, urging them to remain focused on the matter.

"If you're not careful, I think it impacts the competitiveness of our country vis--vis some of these other countries," the CEO said.

Questions for Cramer? Call Cramer: 1-800-743-CNBC

Want to take a deep dive into Cramer's world? Hit him up! Mad Money Twitter - Jim Cramer Twitter - Facebook - Instagram - Vine

Questions, comments, suggestions for the "Mad Money" website? madcap@cnbc.com

Read the original post:

Adobe CEO: Microsoft partnership will automate sales, marketing with AI - CNBC

Tesla Inc. has hired a Stanford University computer scientist specializing in artificial intelligence and deep learning to lead its efforts around driverless cars.

Andrej Karpathy, previously a research scientist at OpenAI, was named director of AI and Autopilot Vision, reporting directly to Chief Executive Elon Musk, a Tesla spokesperson said.

Karpathy is one of the worlds leading experts in computer vision and deep learning, the spokesperson said. He will work closely with Jim Keller, who is responsible for Autopilot hardware and software.

Autopilot is Teslas suite of advanced driver assistance systems, which relies on an onboard Nvidia Corp NVDA, +1.52% supercomputer to make sense of data from numerous sensors in and around Tesla vehicles and the companys software.

Several Silicon Valley companies, from titans such as Apple Inc. AAPL, +0.59% to startups, as well as traditional car makers, software companies, and others elsewhere, are vying to make driverless cars a common sight on roads.

Apples CEO Tim Cook recently confirmed the companys efforts around what he called autonomous systems, and called driverless cars the mother of all AI projects.

See also: We still dont know what Apple is up to with driverless cars

Musk is co-chair of OpenAI, a nonprofit focused on AI research and on a path to safe artificial general intelligence.

The hire comes as Teslas lead of Autopilot software, Chris Lattner, earlier this week announced he was leaving the company after six months on the job.

Lattner worked for more than an decade at Apple Inc.

The Tesla spokesperson said Lattner just wasnt the right fit for Tesla, and weve decided to make a change.

The company is weeks away from starting production of the Model 3, the $35,000 all-electric sedan it hopes to sell to the masses. Tesla is expected to sell the car by the end of the year.

Musk has said that several new vehicles, including a compact SUV and an electric commercial freight truck, are coming to Teslas lineup as the company aims to produce vehicles at a rate of half a million by the end of 2018.

The stock has gained more than 74% so far this year, after a string of record highs in the past two months. That contrasts with gains of 9% for the S&P 500 index SPX, -0.06%

See the original post here:

Tesla hires AI expert to help lead team in charge of self-driving software - MarketWatch

Many workers at brick kilns like this one near Hyderabad have no hope of paying off their debt

Asif Hassan/AFP/Getty

By Matt Reynolds

Online volunteers are helping to track slavery from space. A new crowdsourcing project aims to identify South Asian brick kilns frequently the site of forced labour in satellite images.

This data will then be used to train machine learning algorithms to automatically recognise brick kilns in satellite imagery. If computers can pinpoint the location of possible slavery sites, then the coordinates could be passed to local non-governmental organisations to investigate, says Kevin Bales, who is leading the project at the University of Nottingham in the UK.

South Asian brick kilns are notorious sites of modern-day slavery. Nearly 70 per cent of the estimated 5 million brick kiln workers in South Asia are thought to be working there under force, often to pay off debts.

But no one is quite sure how many kilns there are in the so called Brick Belt that stretches across parts of Pakistan, India and Nepal. Some estimates put the figure at 20,000, but it may be as high as 50,000.

Bales is hoping that his machine learning approach will produce a more accurate number and help organisations on the ground know where to direct their anti-slavery efforts.

Google Earth

Its great to have an objective tool to identify possible slavery sites, says Sasha Jesperson at St Marys University in London. But it is just start to really find out how many people are being enslaved in the brick kiln industry you still need to visit every site and work out exactly whats going on there, she says.

So far, over 9000 potential slavery sites have been identified by volunteers taking part in the project. The volunteers are presented with a series of satellite images taken from Google Earth and they have to click on the parts of images that contain brick kilns.

As soon as 15 volunteers identify each of the nearly 400 images in the data set, Bales plans on teaching the machine learning algorithm to recognise the kilns automatically.

Hes already working on the next stage of the project, which will use a similar approach to help identify open pit mines in countries such as the Democratic Republic of the Congo, which are also often sites of forced labour.

Google Earth

But Bales thinks that his machine learning algorithms might have a trickier time categorising open pit mines than brick kilns. The kilns are usually a distinctive shape and colour, but the mines, which often look like big holes in the ground, can be harder to spot.

A lot of slavery is visible from space, says Bales but image recognition could also be a useful tool for helping track slavery where satellites cant reach. TraffickCam, a project set up by the social action group Exchange Initiative, uses image recognition to identify sex trafficking in hotel rooms.

Visitors to hotels can use TraffickCam to upload an image of the inside of their hotel room to the websites database. These photographs can then be compared with photos of sex workers that traffickers often post online. Because those photos are often taken in hotel rooms, investigators may be able use the TraffickCam database to pinpoint the location of a particular photograph. More than 150,000 hotel rooms have been documented in this way.

More on these topics:

Read more:

Volunteers teach AI to spot slavery sites from satellite images - New Scientist

Alibaba Group Holding Limited (BABA) chairman Jack Ma is preparing for the Third World War. Or at least it would seem that way from his comments to television network CNBC during an interview. According to Ma, advances in technology have caused world wars. "The first technology revolution caused World War I. The second technology revolution caused World War II. This is the third technology revolution," he said. But he did not outline the possible causes for this war.

Ma's interview was wide ranging and covered disparate topics that ranged from the future of humanity to the difference between wisdom and intelligence. He sketched the contours of a future world disrupted by artificial intelligence (AI) trends. According to Ma, the next 30 years will be marked by "very painful" changes for humanity as it enters an age defined by data and artificial intelligence. Ma said that humans will win in a war with machines. This is because machines do not possess wisdom, which comes from the heart. (See also: Alibaba's Ma: We're Not Looking to Invade US.)

That said, the age of machines will witness far-reaching changes. As machines take over labor-intensive tasks, the working week will diminish to 16 hours, Ma predicted. The extra leisure time will create a mobile population that will work across borders and put a stop to the backlash against globalization. "The only thing is how can we make trade more inclusive, knowledge more inclusive, and this is how we can deal with the instability of the world (that machines will create)," he said. Governments will have to make "hard choices," Ma added. (See also: Jack Ma: Success Story.)

Among those choices will the decision to open up borders to enable cross-border e-commerce. According to current rules, it is difficult for small businesses to trade across borders using e-commerce sites due to a phalanx of customs and duty provisions. Ma's e-commerce juggernaut is leading the charge for international e-commerce and already has a thriving business in Tmall, its cross-border e-commerce site that sells overseas goods in China. (See also: Special Delivery: Alibaba Wants Faster Traffic to Europe.)

More here:

AI Could Start Third World War: Alibaba's Jack Ma (BABA) - Investopedia

Googles AI subsidiary DeepMind is continuing to partner with new UK hospitals, announcing today that its Streams app will be used by the Taunton and Somerset NHS Foundation Trust. This is the first time that Streams has been introduced outside of London. The app doesnt use artificial intelligence, but sifts data from patients medical records to warn doctors and nurses about upcoming health problems.

According to a statement from the Taunton and Somerset NHS Foundation Trust, the Streams app will allow clinical staff to view the results of x-rays, scans or blood tests, in one place at the touch of a button. One doctor quoted by the Trust said the app was being used to improve early detection of seriously unwell patients and ensure a very rapid response.

DeepMinds activities in the UK have been criticized in recent months, with a government data advisor warning in May that the companys access to patient medical data had been conducted on an "inappropriate legal basis. These comments were made in reference to an earlier contract DeepMind had with the Royal Free Trust a collection of hospitals in London. The contract has since been replaced, but the original (and the Royal Free) are still under investigation by the UK data watchdog, the Information Commissioner's Office (ICO).

DeepMind has worked hard to reassure the public that their data is being safely handled, and the company stresses that its parent company Alphabet will not have access to any medical information. However, its possible that this latest deal will still come under scrutiny, with BBC News reporting that patients will not have the option to opt out from data sharing. This decision, though, is made by individual hospitals, rather than DeepMind itself. The Verge has reached out to the Taunton and Somerset Trust to confirm the details of the contract.

Original post:

Google's AI subsidiary DeepMind is partnering with another UK hospital - The Verge

The conversation in the technology community about artificial intelligence was first rekindled by manufacturing giant IBM and its AI platform, Watson, CEO Ginni Rometty said on Tuesday.

"We are the ones that woke up the AI world here again," Rometty told "Mad Money" host Jim Cramer in a wide-ranging interview about Washington, Warren Buffett and her business.

Rometty said that the key to her century-old company remaining an institution in this country is how many times it has been able to reinvent itself and follow the latest trends in tech.

Today, those trends are the cloud and artificial intelligence, which IBM employees refer to as "cognitive" programming.

"There's a reason we call it cognitive," Rometty told Cramer. "It's about augmenting what you and I do so we can do what we're supposed to, our best. And then that's the IBM that takes that technology and the know-how about how the world works and puts that together and actually changes business. We are the champion for business."

Rometty also stressed the distinction between AI that consumers see and use and IBM's AI area of expertise, business-oriented AI programs.

"Consumer AI in your home, it's typically speech detects to a search. That's fine. That's great," she said. "But we deal in the enterprise world, so this is training Watson. Watson is trained in industries: What does underwriting do? What does a tax preparer do? What does a doctor do? What does a customer service agent do? What does a repairperson do? And it helps them be better, and, in fact, helps them do their job."

Between IBM's dealings in cognitive programming and the internet of things, Rometty predicted that 1 billion people would interact with Watson by the end of 2017. The result would be a boon to IBM's latest transformation efforts, which Rometty said revolve around one word: data.

The CEO said that Watson will likely also play a monumental role in reforming the health care system, the first step of which would involve touching the lives of 20,000 cancer patients.

"We will be able to address, diagnose and treat 80 percent of what causes 80 percent of the cancer in the world. If that's not motivating, I don't know what is," Rometty told Cramer.

Questions for Cramer? Call Cramer: 1-800-743-CNBC

Want to take a deep dive into Cramer's world? Hit him up! Mad Money Twitter - Jim Cramer Twitter - Facebook - Instagram - Vine

Questions, comments, suggestions for the "Mad Money" website? madcap@cnbc.com

Continued here:

IBM 'woke up the AI world,' CEO Ginni Rometty says - CNBC

Something unexpected happened recently at the Facebook Artificial Intelligence Research lab. Researchers who had been training bots to negotiate with one another realized that the bots, left to their own devices, started communicating in a non-human language.

In order to actually follow what the bots were saying, the researchers had to tweak their model, limiting the machines to a conversation humans could understand. (They want bots to stick to human languages because eventually they want those bots to be able to converse with human Facebook users.) When I wrote about all this last week, lots of people reacted with some degree of trepidatious wonder. Machines making up their own language is really cool, sure, but isnt it actually terrifying?

And also: What does this language actually look like? Heres an example of one of the bot negotiations that Facebook observed:

Bob: i can i i everything else . . . . . . . . . . . . . . Alice: balls have zero to me to me to me to me to me to me to me to me to Bob: you i everything else . . . . . . . . . . . . . . Alice: balls have a ball to me to me to me to me to me to me to me Bob: i i can i i i everything else . . . . . . . . . . . . . . Alice: balls have a ball to me to me to me to me to me to me to me Bob: i . . . . . . . . . . . . . . . . . . . Alice: balls have zero to me to me to me to me to me to me to me to me to Bob: you i i i i i everything else . . . . . . . . . . . . . . Alice: balls have 0 to me to me to me to me to me to me to me to me to Bob: you i i i everything else . . . . . . . . . . . . . . Alice: balls have zero to me to me to me to me to me to me to me to me to

Not only does this appear to be nonsense, but the bots dont really seem to be getting anywhere in the negotiation. Alice isnt budging from her original position, anyway. The weird thing is, Facebooks data shows that conversations like this sometimes still led to successful negotiations between the bots in the end, a spokesperson from the AI lab told me. (In other cases, researchers adjusted their model and the bots would develop bad strategies for negotiatingeven if their conversation remained interpretable by human standards.)

One way to think about all this is to consider cryptophasia, the name for the phenomenon when twins make up their own secret language, understandable only to them. Perhaps you recall the 2011 YouTube video of two exuberant toddlers chattering back and forth in what sounds like a lively, if inscrutable, dialogue.

Theres some debate over whether this sort of twin speak is actually language or merely a joyful, babbling imitation of language. The YouTube babies are socializing, but probably not saying anything with specific meaning, many linguists say.

In the case of Facebooks bots, however, there seems to be something more language-like occurring, Facebooks researchers say. Other AI researchers, too, say theyve observed machines that can develop their own languages, including languages with a coherent structure, and defined vocabulary and syntaxthough not always actual meaningful, by human standards.

A Computer Tried (and Failed) to Write This Article

In one preprint paper added earlier this year to the research repository arXiv, a pair of computer scientists from the non-profit AI research firm OpenAI wrote about how bots learned to communicate in an abstract languageand how those bots turned to non-verbal communication, the equivalent of human gesturing or pointing, when language communication was unavailable. (Bots dont need to have corporeal form to engage in non-verbal communication; they just engage with whats called a visual sensory modality.) Another recent preprint paper, from researchers at the Georgia Institute of Technology, Carnegie Mellon, and Virginia Tech, describes an experiment in which two bots invent their own communication protocol by discussing and assigning values to colors and shapesin other words, the researchers write, they witnessed the automatic emergence of grounded language and communication ... no human supervision!

The implications of this kind of work are dizzying. Not only are researchers beginning to see how bots could communicate with one another, they may be scratching the surface of how syntax and compositional structure emerged among humans in the first place.

But lets take a step back for a minute. Is what any of these bots are doing really language? We have to start by admitting that its not up to linguists to decide how the word language can be used, though linguists certainly have opinions and arguments about the nature of human languages, and the boundaries of that natural class, said Mark Liberman, a professor of linguistics at the University of Pennsylvania.

So the question of whether Facebooks bots really made up their own language depends on what we mean when we say language. For example, linguists tend to agree that sign languages and vernacular languages really are capital-L languages, as Liberman puts itand not mere approximations of actual language, whatever that is. They also tend to agree that body language and computer languages like Python and JavaScript arent really languages, even though we call them that.

So heres the question Liberman poses instead: Could Facebooks bot languageFacebotlish, he calls itsignal a new and lasting kind of language?

Probably not, though theres not enough information available to tell, he said. In the first place, its entirely text-based, while human languages are all basically spoken or gestured, with text being an artificial overlay.

The larger point, he says, is that Facebooks bots are not anywhere near intelligent in the way we think about human intelligence. (Thats part of the reason the term AI can be so misleading.)

The expert systems style of AI programs of the 1970s are at best a historical curiosity now, like the clockwork automata of the 17th century, Liberman said. We can be pretty sure that in a few decades, todays machine-learning AI will seem equally quaint.

Its already easy to set up artificial worlds populated by mysterious algorithmic entities with communications procedures that evolve through a combination of random drift, social convergence, and optimizing selection, Liberman said. Just as its easy to build a clockwork figurine that plays the clavier.

Excerpt from:

What an AI's Non-Human Language Actually Looks Like - The Atlantic