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IBM Watson for Oncology 'underdeveloped', claims Stat report
 It was an audacious undertaking, even for one of the most storied American companies: With a single machine, IBM would tackle humanity’s most vexing diseases and revolutionize medicine.

Breathlessly promoting its signature brand — Watson — IBM sought to capture the world’s imagination, and it quickly zeroed in on a high-profile target: cancer.

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But three years after IBM began selling Watson to recommend the best cancer treatments to doctors around the world, a STAT investigation has found that the supercomputer isn’t living up to the lofty expectations IBM created for it. It is still struggling with the basic step of learning about different forms of cancer. Only a few dozen hospitals have adopted the system, which is a long way from IBM’s goal of establishing dominance in a multibillion-dollar market. And at foreign hospitals, physicians complained its advice is biased toward American patients and methods of care.

STAT examined Watson for Oncology’s use, marketing, and performance in hospitals across the world, from South Korea to Slovakia to South Florida. Reporters interviewed dozens of doctors, IBM executives, artificial intelligence experts, and others familiar with the system’s underlying technology and rollout.

The interviews suggest that IBM, in its rush to bolster flagging revenue, unleashed a product without fully assessing the challenges of deploying it in hospitals globally. While it has emphatically marketed Watson for cancer care, IBM hasn’t published any scientific papers demonstrating how the technology affects physicians and patients. As a result, its flaws are getting exposed on the front lines of care by doctors and researchers who say that the system, while promising in some respects, remains undeveloped.

“Watson for Oncology is in their toddler stage, and we have to wait and actively engage, hopefully to help them grow healthy,” said Dr. Taewoo Kang, a South Korean cancer specialist who has used the product.

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At its heart, Watson for Oncology uses the cloud-based supercomputer to digest massive amounts of data — from doctor’s notes to medical studies to clinical guidelines. But its treatment recommendations are not based on its own insights from these data. Instead, they are based exclusively on training by human overseers, who laboriously feed Watson information about how patients with specific characteristics should be treated.

IBM executives acknowledged Watson for Oncology, which has been in development for nearly six years, is in its infancy. But they said it is improving rapidly, noting that by year’s end, the system will offer guidance about treatment for 12 cancers that account for 80 percent of the world’s cases. They said it’s saving doctors time and ensuring that patients get top-quality care.

“We’re seeing stories come in where patients are saying, ‘It gave me peace of mind,’” Watson Health general manager Deborah DiSanzo said. “That makes us feel extraordinarily good that what we’re doing is going to make a difference for patients and their physicians.”

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But contrary to IBM’s depiction of Watson as a digital prodigy, the supercomputer’s abilities are limited.

Perhaps the most stunning overreach is in the company’s claim that Watson for Oncology, through artificial intelligence, can sift through reams of data to generate new insights and identify, as an IBM sales rep put it, “even new approaches” to cancer care. STAT found that the system doesn’t create new knowledge and is artificially intelligent only in the most rudimentary sense of the term.

While Watson became a household name by winning the TV game show “Jeopardy!”, its programming is akin to a different game-playing machine: the Mechanical Turk, a chess-playing robot of the 1700s, which dazzled audiences but hid a secret — a human operator shielded inside.

“Jeopardy!” champions Ken Jennings (left) and Brad Rutter watch Watson beat them to the buzzer to answer a question during a practice round in 2011. Seth Wenig/AP

In the case of Watson for Oncology, those human operators are a couple dozen physicians at a single, though highly respected, U.S. hospital: Memorial Sloan Kettering Cancer Center in New York. Doctors there are empowered to input their own recommendations into Watson, even when the evidence supporting those recommendations is thin.

The actual capabilities of Watson for Oncology are not well-understood by the public, and even by some of the hospitals that use it. It’s taken nearly six years of painstaking work by data engineers and doctors to train Watson in just seven types of cancer, and keep the system updated with the latest knowledge.

“It’s been a struggle to update, I’ll be honest,” said Dr. Mark Kris, Memorial Sloan Kettering’s lead Watson trainer. He noted that treatment guidelines for every metastatic lung cancer patient worldwide recently changed in the course of one week after a research presentation at a cancer conference. “Changing the system of cognitive computing doesn’t turn around on a dime like that,” he said. “You have to put in the literature, you have to put in cases.”

Watson grew out of an effort to transform IBM from an old-guard hardware company to one that operates in the cloud and along the cutting edge of artificial intelligence. Despite its use in an array of industries — from banking to manufacturing — it has failed to end a streak of 21 consecutive quarters of declining revenue at IBM. In the most recent quarter, revenue even slid from the same period last year in IBM’s cognitive solutions division — which is built around Watson and is supposed to be the future of its business.

In response to STAT’s questions, IBM said Watson, in health care and otherwise, remains on an upward trajectory and “is already an important part” of its $20 billion analytics business. Health care is a crucial part of the Watson enterprise. IBM employs 7,000 people in its Watson health division and sees the industry as a $200 billion market over the next several years. Only financial services, at $300 billion, is considered a bigger opportunity by the company.

At stake in the supercomputer’s performance is not just the fortunes of a famed global company. In the world of medicine, Watson is also something of a digital canary — the most visible attempt to use artificial intelligence to identify the best ways to prevent and treat disease. The system’s larger goal, IBM executives say, is to democratize medical knowledge so that every patient, no matter the person’s geography or income level, will be able to access the best care.

But in cancer treatment, the pursuit of that utopian ideal has faltered.

STAT’s investigation focused on Watson for Oncology because that product is the furthest along in clinical care, though Watson sells separate packages to analyze genomic information and match patients to clinical trials. It’s also applying Watson to other tasks, including honing preventive medicine practices and reading medical images.

Doctors’ reliance on Watson for Oncology varies among hospitals. While institutions with fewer specialists lean more heavily on its recommendations, others relegate the system to a background role, like a paralegal whose main skill is researching existing knowledge.

Hospitals pay a per-patient fee for Watson for Oncology and other products enabled by the supercomputer. The amount depends on the number of products a hospital buys, and ranges between $200 and $1,000 per patient, according to DiSanzo. The system sometimes comes with consulting costs and is expensive to link with electronic medical records. At hospitals that don’t link it with their medical records, more time must be spent typing in patient information.

At Jupiter Medical Center in Florida, that task falls to nurse Jean Thompson, who spends about 90 minutes a week feeding data into the machine. Once she has completed that work, she clicks the “Ask Watson” button to get the supercomputer’s advice for treating patients.

On a recent morning, the results for a 73-year-old lung cancer patient were underwhelming: Watson recommended a chemotherapy regimen the oncologists had already flagged.

“It’s fine,” Dr. Sujal Shah, a medical oncologist, said of Watson’s treatment suggestion while discussing the case with colleagues.

He said later that the background information Watson provided, including medical journal articles, was helpful, giving him more confidence that using a specific chemotherapy was a sound idea. But the system did not directly help him make that decision, nor did it tell him anything he didn’t already know.

Jupiter is one of two U.S. hospitals that have adopted Watson for Oncology. The system has generated more business in India and Southeast Asia. Many doctors in those countries said Watson is saving time and helping more patients get quality care. But they also said its accuracy and overall value is limited by differing medical practices and economic circumstances.

Despite IBM’s marketing blitz, with years of high-profile Watson commercials featuring celebrities from Serena Williams to Bob Dylan to Jon Hamm, the company’s executives are not always gushing. In interviews with STAT, they acknowledged the system faces challenges and needs better integration with electronic medical records and more data on real patients to find patterns and suggest cutting-edge treatments.

“The goal as Watson gets smarter is for it to make some of those recommendations in a more automated way, to sort of suggest now may be the time and let us flip the switch” when a promising treatment option emerges, said Dr. Andrew Norden, a former IBM deputy health chief who left the company in early August. “As I describe it, you’re probably getting a sense it’s really hard and nuanced.”

Such nuance is absent from the careful narrative IBM has constructed to sell Watson.

Alex Hogan, Ike Swetlitz/STAT

It is by design that there is not one independent, third-party study that examines whether Watson for Oncology can deliver. IBM has not exposed the product to critical review by outside scientists or conducted clinical trials to assess its effectiveness.

While it’s not unheard of for companies to avoid external vetting early on, IBM’s circumstances are unusual because Watson for Oncology is not in development — it has already been deployed around the world.

Yoon Sup Choi, a South Korean venture capitalist and researcher who wrote a book about artificial intelligence in health care, said IBM isn’t required by regulatory agencies to do a clinical trial in South Korea or America before selling the system to hospitals. And given that hospitals are already using the system, a clinical trial would be unlikely to improve business prospects.

“It’s too risky, right?” Choi said. “If the result of the clinical trial is not very good — [if] there’s a marginal clinical benefit from Watson — it’s really bad news to the whole IBM.”

Pilar Ossorio, a professor of law and bioethics at University of Wisconsin Law School, said Watson should be subject to tighter regulation because of its role in treating patients. “As an ethical matter, and as a scientific matter, you should have to prove that there’s safety and efficacy before you can just go do this,” she said.

Norden dismissed the suggestion IBM should have been required to conduct a clinical trial before commercializing Watson, noting that many practices in medicine are widely accepted even though they aren’t supported by a randomized controlled trial.

“Has there ever been a randomized trial of parachutes for paratroopers?” Norden asked. “And the answer is, of course not, because there is a very strong intuitive value proposition. … So I believe that bringing the best information to bear on medical decision making is a no-brainer.”

IBM said in its statement that it has collaborated with the research community and presented data on Watson at industry gatherings and in peer-reviewed journals. Some doctors said they didn’t need to see more research to know that the system is valuable. “Artificial intelligence will be adopted in all medical fields in the future,” said Dr. Uhn Lee, who runs the Watson program at Gachon University Gil Medical Center in South Korea. “If that trend, that change is inevitable, then why don’t we just start early?”

So far, the only studies about Watson for Oncology are conference abstracts. The full results haven’t been published in peer-reviewed journals — and every study, save one, was either conducted by a paying customer or included IBM staff on the author list, or both. Most trumpet positive results, showing that Watson saves doctors time and has a high concordance rate with their treatment recommendations.

The “concordance” studies comprise the vast majority of the public research on Watson for Oncology. Doctors will ask Watson for its advice for treating a slew of patients, and then compare its recommendations to those of oncologists. In an unpublished study from Denmark, the rate of agreement was about 33 percent — so the hospital decided not to buy the system. In other countries, the rate can be as high as 96 percent for some cancers. But showing that Watson agrees with the doctors proves only that it is competent in applying existing methods of care, not that it can improve them.

IBM executives said they are pursuing studies to examine the impact on doctors and patients, although none has been completed to date.

Questions about Watson have begun spilling into public view, including in a recent Gizmodo story headlined “Why Everyone is Hating on IBM Watson — Including the People Who Helped Make It.” The most prominent failure occurred last February when MD Anderson Cancer Center, part of the University of Texas, cancelled its partnership with Watson.

The MD Anderson alliance was essentially the early face of Watson in health care. The Houston hospital was among IBM’s first partners, and it was using the system to create its own expert oncology adviser, similar to the one IBM was developing with Memorial Sloan Kettering. But the project disintegrated amid internal allegations of overspending, delays, and mismanagement. In all, MD Anderson spent more than three years and $60 million — much of it on outside consultants — before shelving the effort.

The hospital declined to answer questions. But the project leader, Dr. Lynda Chin, in her first media interview on the subject, told STAT about the challenges she faced. Chin left MD Anderson before the project collapsed; a subsequent audit flagged several violations of procurement rules under her leadership.

Chin said that Watson is a powerful technology, but that it is exceedingly difficult to make functional in health care. She and her team encountered numerous roadblocks, some of which still have not been fully addressed by IBM — at MD Anderson or elsewhere.

The cancer hospital’s first major challenge involved getting the machine to deal with the idiosyncrasies of medical records: the acronyms, human errors, shorthand phrases, and different styles of writing. “Teaching a machine to read a record is a lot harder than anyone thought,” she said. Her team spent countless hours on that problem, trying to get Watson to extract valuable information from medical records so that it could apply them to its recommendations.

Chin said her team also wrestled with deploying the system in clinical practice. Watson, even if guided by doctors, is as close as medicine has ever gotten to allowing a machine to help decide the treatments delivered to human beings. That carries with it thorny questions, such as how to test the safety of a digital treatment adviser, how to ensure its compliance with regulations, and how to incorporate it into the daily work of doctors and nurses.

“Importantly,” Chin said. “How do we create an environment that can ensure the most important tenet in medicine: Do no harm?”

Finally, the project ran into a bigger obstacle: Even if you can get Watson to understand patient variables and make competent treatment recommendations, how do you get it access to enough patient data, from enough different sources, to derive insights that could significantly advance the standard of care?

Chin said that was a showstopper. Watson did not have a connected network of institutions feeding data about specific cohorts of patients. “You may have 10,000 patients for lung cancer. That is still not a very big number when you think about it,” she said.

With data from many more patients, Chin said, you could see patterns — “subsets [of patients] that respond a certain way, subsets that don’t, subsets that have a certain toxicity. That pattern would help with better personalized and precision medicine. But we can’t get there without the ability to actually have a way of aggregating them.”

IBM told STAT that Chin’s work was separate from the effort to create Watson for Oncology, which was validated by cancer specialists at Memorial Sloan Kettering prior to its deployment. The company said that Watson for Oncology can extract and summarize substantial text from patient records, though the information must be verified by a clinician, and that it has made significant progress in obtaining more data to improve Watson’s performance. It pointed to partnerships with the health care publisher Elsevier and the analytics firm Doctor Evidence.

To date, more than 50 hospitals on five continents have agreements with IBM, or intermediary technology companies, to use Watson for Oncology to treat patients, and others are using the genomics and clinical trials products.

But the partnership with Memorial Sloan Kettering, and the product that grew out of it, resulted in complications that IBM has papered over with carefully parsed statements and misleading marketing.

Tae-hyun Cho (right), the first Korean to be treated with assistance from Watson for Oncology, reviews his medical information with oncologists at Gachon University Gil Medical Center. Gachon University Gil Medical Center

In its press releases, IBM celebrates Memorial Sloan Kettering’s role as the only trainer of Watson. After all, who better to educate the system than doctors at one of the world’s most renowned cancer hospitals?

But several doctors said Memorial Sloan Kettering’s training injects bias into the system, because the treatment recommendations it puts into Watson don’t always comport with the practices of doctors elsewhere in the world.

Given the same clinical scenario, doctors can — and often do — disagree about the best course of action, whether to recommend surgery or chemotherapy, or another treatment. Those discrepancies are especially wide for second- and third-line treatments given after an initial therapy fails, where evidence of benefits is slimmer and consensus more elusive.

Rather than acknowledge this dilemma, IBM executives, in marketing materials and interviews, have sought to downplay it. In an interview with STAT, DiSanzo, the head of Watson Health, rejected the idea that Memorial Sloan Kettering’s involvement creates any bias at all.

“The bias is taken out by the sheer amount of data we have,” she said, referring to patient cases and millions of articles and studies fed into Watson.

But that mischaracterizes how Watson for Oncology works. (IBM later claimed that DiSanzo was referring to Watson in general.)

The system is essentially Memorial Sloan Kettering in a portable box. Its treatment recommendations are based entirely on the training provided by doctors, who determine what information Watson needs to devise its guidance as well as what those recommendations should be.

When users ask Watson for advice, the system also searches published literature — some of which is curated by Memorial Sloan Kettering — to provide relevant studies and background information to support its recommendation. But the recommendation itself is derived from the training provided by the hospital’s doctors, not the outside literature.

Doctors at Memorial Sloan Kettering acknowledged their influence on Watson. “We are not at all hesitant about inserting our bias, because I think our bias is based on the next best thing to prospective randomized trials, which is having a vast amount of experience,” said Dr. Andrew Seidman, one of the hospital’s lead trainers of Watson. “So it’s a very unapologetic bias.”

Seidman said the hospital is careful to keep its training grounded in clinical evidence when the evidence exists, but it is not shy about giving its recommendations when it doesn’t. “We want cancer care to be democratized,” he said. “We don’t want doctors who don’t have the thousands and thousands of patients’ experience on a more rare cancer to be handicapped. We want to share that knowledge base.”

At a recent training session of Watson on Manhattan’s Upper East Side, the tensions involved in programming the system were on full display. STAT sat in as Memorial Sloan Kettering doctors, led by Seidman, gathered with IBM engineers to train Watson to treat bladder cancer. Five IBM engineers sat on one side of the table. Across from them were three oncologists — one specializing in surgery, another in radiation, and a third in chemotherapy and targeted medicines.

Several minutes into the discussion, the question arose of which treatment to recommend for patients whose cancers persisted through six rounds of chemotherapy. The options in such cases tend to be as slim as the evidence supporting them. Should Watson recommend a radical surgery to remove the bladder? Dr. Tim Donahue, the surgical oncologist, noted that such surgery seldom cures patients and is not associated with improved survival in his experience.

Then what about another course of chemotherapy combined with radiation?

When Watson gives its recommendations, it puts the top recommendation in green, alternative options in orange, and not recommended options in red.

But in some clinical scenarios, it’s difficult to tell the colors apart.

“This is the hard part of this whole game,” Dr. Marisa Kollmeier, the radiation oncologist, said during the training. “There’s a lack of evidence. And you don’t know if something should be in green without evidence. We don’t have a randomized trial to support every decision.”

But the task in front of them required the doctors to press ahead. And they did, rifling through an array of clinical scenarios. In some cases, a large body of evidence backed up their answers. But many others fell into a gray area or were clouded by the inevitable uncertainty of patient preferences.

The meeting was one of many in a months-long process to bring Watson up to speed in bladder cancer. Subsequent sessions would involve feeding it data on real patient cases at Memorial Sloan Kettering, so doctors could reinforce Watson’s training with repetition.

That training does not teach Watson to base its recommendations on the outcomes of these patients, whether they lived, or died or survived longer than similar patients. Rather, Watson makes its recommendations based on the treatment preferences of Memorial Sloan Kettering physicians.

At some institutions using Watson, IBM’s lack of clarity on the cancer center’s role causes confusion. Some seem to think they are getting advice from doctors around the world.

“As we tell the patients, it’s like another consultation, but it’s a worldwide consultation,” said Dr. K. Adam Lee, medical director of thoracic oncology at Jupiter Medical Center, when STAT visited in June.

“Really worldwide,” added Kerri Ward, an oncology nurse at the hospital. “It pulls from 300 journals, just for oncology, the clinical database, so the national clinical database, journals, textbooks, and then Sloan Kettering is the one that’s feeding in the clinical [information] currently.”

Robert Garrett, the CEO of Hackensack Meridian Health, a group in New Jersey that is using a version of Watson for Oncology, said the information in Watson is “global.”

“If you’re a patient that has colon cancer, they have in their database, as I understand it, how colon cancer is treated around the world, by different clinicians, what’s been the most effective treatment for different phases of colon cancer,” Garrett said. “That’s what IBM Watson brings to the table.”

None of that accurately depicts how Watson for Oncology works.

Several doctors who have examined Watson in other countries told STAT that Memorial Sloan Kettering’s role has given them pause. Researchers in Denmark and the Netherlands said hospitals in their countries have not signed on with Watson because it is too focused on the preferences of a few American doctors.

Martijn van Oijen, an epidemiologist and associate professor at Academic Medical Center in the Netherlands, said Memorial Sloan Kettering is packed with top specialists but doesn’t have a monopoly on cancer expertise. “The bad thing is, it’s a U.S.-based hospital with a different approach than some other hospitals in the world,” said van Oijen, who’s involved in a national initiative to evaluate technologies like Watson and is a strong believer in using artificial intelligence to help cancer doctors.

In Denmark, oncologists at one hospital said they have dropped the project altogether after finding that local doctors agreed with Watson in only about 33 percent of cases.

“We had a discussion with [IBM] that they had a very limited view on the international literature, basically, putting too much stress on American studies, and too little stress on big, international, European, and other-part-of-the-world studies,” said Dr. Leif Jensen, who directs the center at Rigshospitalet in Copenhagen that contains the oncology department.

In countries where doctors were trained in the United States, or they use similar treatment guidelines as the Memorial Sloan Kettering doctors, Watson for Oncology can be helpful. Taiwan uses the same guidelines as Americans, so Watson’s advice will be useful there, said Dr. Jeng-Fong Chiou, vice superintendent of the Taipei Cancer Center at Taipei Medical University, which started using Watson for Oncology with patients in July.

But he also said there are differences between American and Taiwanese patients — his patients often receive lower doses of drugs to minimize side effects — and that his oncologists will have to make adjustments from Watson’s recommendations.

The generally affluent population treated at Memorial Sloan Kettering doesn’t reflect the diversity of people around the world. The cases used to train Watson therefore don’t take into account the economic and social issues faced by patients in poorer countries, noted Ossorio, the University of Wisconsin law professor.

“What it’s going to be learning is race, gender, and class bias,” she said. “We’re baking those social stratifications in, and we’re making the biases even less apparent and even less easy for people to recognize.”

Sometimes, the recommendations Watson gives diverge sharply from what doctors would say for reasons that have nothing to do with science, such as medical insurance. In a poster presented at the Global Breast Cancer Conference 2017 in South Korea, researchers reported that the treatment Watson most often recommended for breast cancer patients simply wasn’t covered by the national insurance system.

IBM said it has convened an international group of advisers to gather input on Watson’s performance. It also said that the system can be customized to reflect variations in treatment practices, differences in drug availability and financial considerations, and that the company recently introduced tools reduce the time and cost of adapting Watson.

In a response to STAT’s questions, Memorial Sloan Kettering said international journals are part of the literature it provides to Watson, including the Lancet, the European Journal of Cancer, Annals of Oncology, and the BMJ. “As we do in all areas of cancer research, we will continue to observe and study how Watson for Oncology impacts care internationally, follow the evidence, and work with IBM to optimize the system,” the hospital said.

Some hospitals abroad are customizing the system for their patients, adding information about local treatments. Nan Chen, who manages the Watson for Oncology program at Bumrungrad International Hospital in Thailand, said his oncologists use Japanese guidelines, not American guidelines, for treating gastric cancer.

But he said doctors can find this localization redundant or unnecessary: They are not that interested in being told the same guidance they just taught Watson.

“Our doctors say, this treatment is our own treatment, we know that,” Chen said. “You don’t need to turn around and put those treatments in Watson, and let Watson tell us what kind of treatment that we are using here in the hospital.”

Chen said this modified system is incredibly beneficial, however — to a hospital in the capital of Mongolia that employs zero oncology specialists.

At UB Songdo Hospital, of which Chen’s company is a majority owner, doctors are following Watson’s suggestions nearly 100 percent of the time. Patients who otherwise would have been treated by generalists with little, if any, cancer training are now benefiting from top-level expertise.

“That is the kind of thing that IBM is dreaming about,” Chen said.

In South Korea, Dr. Taewoo Kang, a surgical oncologist at Pusan National University Hospital who specializes in breast cancer, pointed to another important problem that Watson needs to solve. Right now, it provides supporting evidence for the recommendations it makes, but doesn’t actually explain how it came to recommend that particular treatment for that particular patient.

Kang said that, sometimes, he will ask Watson for advice on a patient whose cancer has not spread to the lymph nodes, and Watson will recommend a type of chemotherapy drug called a taxane. But, he said, that therapy is normally used only if the cancer has spread to the lymph nodes. And, to support the recommendation, Watson will show a study demonstrating the effectiveness of the taxane for patients whose cancer did spread to their lymph nodes.

Kang is left confused as to why Watson recommended a drug that he does not normally use for patients like the one in front of him. And Watson can’t tell him why.

Louisa Roberts (left) of IBM Watson Health speaks with Merck executive Oliver Maschinsky in the Watson booth at the 2017 ASCO cancer conference in Chicago. Heather Stone for STAT

For all the concerns, some doctors around the world who use Watson insist that artificial intelligence will one day revolutionize health care. They say that clinicians are realizing concrete benefits — saving doctors valuable time searching for studies, better educating patients, and undercutting hierarchies in the clinic that might interfere with evidence-based treatment.

In Taiwan, Chiou said Watson immediately provides the “best data” from the literature about a treatment — survival rates, for example — relieving doctors of the task of searching the literature to compare each possible treatment.

Watson’s information also empowers patients, said Lee, the doctor who runs the Watson program at Gil Medical Center in South Korea. Previously, doctors verbally explained different treatment options to patients. Now, physicians can give patients a comprehensive packet prepared by Watson, which includes potential treatment plans along with relevant scientific articles. Patients can do their own research about these treatments, and maybe even disagree with the doctor about the right course of action.

“This is one of the most important and significant changes,” Lee said.

Watson also holds senior doctors accountable to the data. At Gil Medical Center, patients sit in a room with five doctors and Watson itself, the interface displayed on a flat-screen television in the so-called “Watson center.” Lee said that Watson’s presence has a huge influence on the doctors’ decision-making process, leveling the hierarchy that traditionally prioritized the opinion of the senior doctor over junior colleagues.

Watson gives the junior physicians quick and easy access to data that might prove their elders wrong, displaying on the screen information such as the survival rate right alongside a recommended treatment. It would be humiliating for senior doctors to continue to push for a different treatment in light of this evidence, Lee said.

At Manipal Hospitals in India, Dr. S.P. Somashekhar said that while there are some regional disparities in Watson’s recommendations for patients with rectal and breast cancer, those cases are outliers: For the vast majority of patients, the program matched the recommendations given to patients by the hospital’s tumor board — a group of 20 physicians that typically study their cases for a week and spend an hour discussing them.

That means that in a handful of seconds, Watson did what it takes 20 doctors over a week to accomplish. “That is so precious and very highly valuable,” Somashekhar said. “Our physicians cannot discuss every case. For every case we discuss in the tumor board, there are five cases which we cannot discuss.”

While those benefits are significant, they fall short of breakthrough discoveries that could predict or eradicate disease.

IBM executives said that doesn’t mean Watson can’t accomplish those feats. Norden, the former deputy health officer for Watson for Oncology and Genomics, said the goal is to ultimately bring together streams of clinical trial data and real-world patient data, so that Watson could begin to pinpoint the best treatments on its own.

“My own belief is that over time we will be better at measuring and reporting outcomes, and that data will be increasingly influential,” he said. “Where cancer care is today, I don’t think that any computing system is ready to be let out into the world without a measure of expert human oversight.”

IMMERSION in 360 DEGREES: Click and drag to look around the Watson “Immersion Room” in Cambridge, Mass. Dom Smith/STAT

The bigger question for IBM is not whether health care will see a revolution in artificial intelligence but who will drive it.

One former IBM employee says the company could become a victim of its own marketing success — the unrealistic expectations it set are obscuring real accomplishments.

“IBM ought to quit trying to cure cancer,” said Peter Greulich, a former IBM brand manager who has written several books about IBM’s history and modern challenges. “They turned the marketing engine loose without controlling how to build and construct a product.”

Greulich said IBM needs to invest more money in Watson and hire more people to make it successful. In the 1960s, he said, IBM spent about 11.5 times its annual earnings to develop its mainframe computer, a line of business that still accounts for much of its profitability today.

If it were to make an equivalent investment in Watson, it would need to spend $137 billion. “The only thing it’s spent that much money on is stock buybacks,” Greulich said.

IBM said it created the market for artificial intelligence and is pleased with the pace of Watson’s growth, noting that it and other new business units grew by more than $20 billion in the past three years. “It took Facebook and Amazon more than 13 years to grow $20 billion,” the company said in a statement.

Since Watson’s “Jeopardy!” demonstration in 2011, hundreds of companies have begun developing health care products using artificial intelligence. These include countless startups, but IBM also faces stiff competition from industry titans such as Amazon, Microsoft, Google, and the Optum division of UnitedHealth Group.

Google’s DeepMind, for example, recently displayed its own game-playing prowess, using its AlphaGo program to defeat a world champion in Go, a 3,000-year-old Chinese board game.

DeepMind is working with hospitals in London, where it is learning to detect eye disease and speed up the process of targeting treatments for head and neck cancers, although it has run into privacy concerns.

Meanwhile, Amazon has launched a health care lab, where it is exploring opportunities to mine data from electronic health records and potentially build a virtual doctor’s assistant.

A recent report by the financial firm Jefferies said IBM is quickly losing ground to competitors. “IBM appears outgunned in the war for AI talent and will likely see increasing competition,” the firm concluded.

While not specific to Watson’s health care products, the report said potential clients are backing away from the system because of significant consulting costs associated with its implementation. It also noted that Amazon has 10 times the job listings of IBM, which recently didn’t renew a small number of contractors that worked for the company following its acquisition of Truven, a company it bought for $2.6 billion last year to gain access to 100 million patient records.

In its statement, IBM said that the workers’ contracts ended and that it is continuing to hire aggressively in the Cambridge, Mass.-based Watson Health and other units, with more than 5,000 positions open in the U.S.

But the outlook for Watson for Oncology is challenging, say those who have worked closest with it. Kris, the lead trainer at Memorial Sloan Kettering, said the system has the potential to improve care and ensure more patients get expert treatment. But like a medical student, Watson is just learning to perform in the real world.

“Nobody wants to hear this,” Kris said. “All they want to hear is that Watson is the answer. And it always has the right answer, and you get it right away, and it will be cheaper. But like anything else, it’s kind of human.”

Output: IBM's Watson for Oncology, an artificial intelligence programme that was intended to revolutionise the treatment of cancer, is not living up to its marketing hype and needs further development, an investigation by US health news site Stat has claimed. Stat found that Oncology for Watson did not have enough patient data to make independent decisions, while a preference for US medical methods and a claimed lack of diversity among patients, as well as the system's high cost, prompted criticism from medical experts outside the country. However, Oncology for Watson was deemed more useful in China, where there are fewer oncologists.


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Input:
RWE's renewable unit Innogy targeted by Iberdrola
 Spain-based power provider Iberdrola could be interested in acquiring German renewable energy company Innogy, a subsidiary of Germany-based power utility RWE, according to Spanish financial newspaper Expansión.

The article, which cites unidentified sources within the financial sector, says that Iberdrola has not confirmed its interest in the operation, as it “usually does not comment market rumors.”

RWE said in March it was considering every option for its renewable energy unit, and that it is in talks with market players. At that time, Bloomberg revealed that French energy giant Engie was planning to acquire Innogy. Furthermore, Reuters revealed that an unidentified source from the French government had confirmed that talks were being held, but the banks had not been given mandate to proceed with the operation.

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RWE, however, is obliged by a 2015 board resolution to maintain a 51% stake in the unit. This means the company could eventually sell only the remainder of the 77% stake it currently holds.

In May, Reuters estimated the value of Innogy at at €18.6 billion. Innogy completed the acquisition of German PV power and storage specialist Belectric in January 2017. Through this acquisition, Innogy added much-needed large-scale solar PV and storage capabilities to its portfolio. Belectric’s global portfolio consists of 280 utility-scale solar plants and rooftop arrays, amounting to more than 1.5 GW of installed solar capacity.

Output: Spanish utility Iberdrola could acquire renewable energy firm Innogy, owned by Germany utility RWE, according to anonymous sources, cited by Spanish newspaper Expansión. Iberdrola said it does not comment on "market rumours". Earlier this year, it emerged French energy giant Engie was in talks to purchase Innogy, with an anonymous French government source confirming the discussions, as RWE said at the time it was "considering every option for its renewable energy unit".


Instruction: create a high quality summary of the given input

Input:
Lawmakers Debate How Much Wiggle Room To Give States In Health Care
 One of the few things that Republicans and Democrats broadly agree on is that states should have some flexibility to experiment with different ways to pay for and deliver health care.

But they disagree — strongly — on how much. In fact, Republicans don’t agree with one another on this, and that dissent helped sink efforts this summer to “repeal and replace” the Affordable Care Act. Bridging these divides will help determine the success of a bipartisan effort in the Senate this month to help shore up the individual health insurance market.

“I’ve always said not all the wisdom is going to be in Washington,” said Sen. Ron Wyden (D-Ore.), the ranking Democrat on the powerful Finance Committee. “Progressive and conservative folks are going to say ‘we can do better.’”

The federal health law includes a provision that allows states to alter some of its rules if they can think of a better way to provide health care to their residents. These are known as “Section 1332 waivers,” bookmarking where they are located in the health law.

This KHN story also ran in Stat . It can be republished for free ( details ).

But the law strictly limits how far states can go with their experiments. It includes what are known as “guardrails.” Those limits, said Nicholas Bagley, a health law professor at the University of Michigan, “are to prevent states from undermining the Affordable Care Act goal to provide people with comprehensive coverage.”

The waivers were designed “so blue states can experiment with blue state solutions, and red states can experiment with red state solutions,” said Bagley. “But to do so and stay within the guardrails is really difficult.” For example, he said, “you can reallocate the money, but you can’t reallocate it to create losers.”

At issue is whether to broaden authority for states by revising or eliminating the “guardrails” intended to protect patients and the federal government.

Wyden, who authored the 1332 language in the ACA, is skeptical. Under the current rules, he said, “states can make changes that make health care better. But they can’t go out and make health care worse.”

It is clear that Republicans in Congress want changes to the provision. The repeal-and-replace bill that passed the House and all those considered in the Senate included some expansion of state authority to waive protections included in the health law. Bagley said the bills “would have essentially given carte blanche to states to come up with ACA alternatives without any regard to the guardrails” other than the one prohibiting additions to the federal deficit.

And Sen. Lamar Alexander (R-Tenn.), chairman of the Senate Health, Education, Labor and Pensions (HELP) Committee, who is working on a bipartisan bill, said Wednesday that “Democrats will have to agree to something — more flexibility for states — that some are reluctant to support.”

So is there a compromise between Democrats who want to maintain the protections and Republicans who want states to have a freer hand?

Maybe.

David Anderson of Duke University said one possible source of agreement would be to streamline the federal approval process, starting with the guidance issued by the Obama administration in 2015 that critics said was too restrictive.

Under the rules set by the ACA, states can use waivers to adjust things like the structure of premium assistance to those with low and moderate incomes or the individual and employer requirements to have and offer coverage. But those changes must meet four key standards: States continue to provide equally comprehensive coverage to at least the same number of people, with no higher out-of-pocket costs and without costing the federal government more than it would spend under the provisions of the ACA.

The rules around the waivers also make it hard to accomplish a truly comprehensive overhaul of a state’s health care system, as states can’t use them to reach the place where most of the money funding that system comes from: tax breaks for employer-provided insurance and the federal Medicare program. Workers don’t pay taxes on the value of employer-provided insurance, which is estimated to cost the federal Treasury some $260 billion in income and payroll taxes 2017.

“If you want to reshape your state health insurance market, you’ve got to be able to grab onto the employer market or Medicare, and you can’t” using the waiver procedure, Bagley said.

States also cannot use Section 1332 to change provisions of the Medicaid and Children’s Health Insurance Program, although they can submit simultaneous waivers to each program under separate Medicaid waiver authority in the law.

So far, only two states — Hawaii and Alaska — have won federal approval for 1332 waivers under the health law.

Hawaii has had its own system for providing health coverage based on an employer requirement for coverage since the 1970s. The state’s waiver allows it to use money allocated to help small businesses afford coverage in different ways.

Alaska’s waiver, which was approved this summer, involves a “reinsurance” plan that will help spread the costs of the state’s sickest patients more widely. “By removing high-cost conditions from the risk pool, the benefits of the [reinsurance program] are shared by the entire individual health insurance market,” Lori Wing-Heier, head of the state’s insurance department, told the HELP Committee on Wednesday. In its first year, the program dropped proposed premium increases from 40 percent to “just over 7 percent,” Wing-Heier said.

Minnesota has applied for a waiver similar to Alaska’s, and approval is expected. Earlier this spring, the Department of Health and Human Services specifically invited states to apply for waivers of that type.

Other states, though, are working on proposals that would make more comprehensive changes. Iowa, for example, wants to dramatically redistribute the money available, with bigger subsidies for the middle-class customers and smaller ones for those with lower incomes. The state says that would help draw more customers into the marketplace so that the risk pool is healthier and the premiums for everyone would decrease. It would also eliminate the help lower-income people get to pay their out-of-pocket medical costs, such as deductibles and copayments.

“The Iowa waiver on its face pretty brazenly ignores the guardrails,” said Bagley.

Oklahoma, which is seeking a waiver for its own reinsurance program, is also working on a plan that would make major changes, including encouraging people to purchase insurance with higher deductibles along with a health savings account.

Part of the difficulty with the waivers is the number of hoops states must jump through to win approval, including passing legislation, seeking public comment and holding hearings around the state.

And those are not even the biggest problems, state officials say. “The part that is stifling states right now is the six-month waiting period before they receive final approval,” Alaska’s Wing-Heier told the Senate panel.

Teresa Miller, former Pennsylvania insurance commissioner, agreed at the Senate hearing, saying, “The current process is very cumbersome.”

Anderson of Duke University said one key possibility to add flexibility would be to loosen the requirement that state changes not add to the federal deficit. “Maybe they could allow for deficit neutrality over the course of the waiver rather than year by year,” he said, in which case experiments that cost money to begin with but save over time would be allowed.

Wyden said he is willing to look at any ideas to make the waivers easier to use.

But he added that the popularity of state “reinsurance” waivers that are lowering premiums shows the waiver provision is working as intended. And, he said, if GOP members try again to roll back coverage using the waiver provision “they’re going to have to roll over me, then they’re going to have to persuade people” that it meets the 1332 requirements.

Output: One of the few things that Republicans and Democrats broadly agree on is that states should have some flexibility to experiment with different ways to pay for and deliver health care.


Instruction: create a high quality summary of the given input

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KBS Realty Advisors set for IPO of US REIT in Singapore
 It’s not unusual for U.S. real estate firms to go public. It’s unusual to do it all the way across the Pacific. California-based KBS Realty Advisors wants to raise around $500 million on Singapore’s stock market by listing some of its U.S. properties as a real estate investment trust through a joint venture with local asset manager Keppel.

The new public company would include close to a dozen U.S. buildings in cities such as Seattle and Houston, the Wall Street Journal reported.

Canadian insurer Manulife Financial listed a REIT in Singapore last year that raised $470 million and included U.S. properties. Singapore’s stock market includes 40 REITs with a combined market value of $60 billion.

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Last year a KBS-managed REIT became the first U.S. trust to raise bonds in Israel.

KBS’ New York City holdings include a Williamsburg rental building at 424 Bedford Avenue and a Financial District office building at 110 William Street. [WSJ] — Konrad Putzier

Output: California-based KBS Realty Advisors is set to launch an initial public offering in Singapore, where it aims to raise around $500m. KBS said it would list US properties in cities including Seattle and Houston as a real estate investment trust (REIT) via a joint venture with local asset manager Keppel. Last year, Canadian insurer Manulife Financial listed a REIT in the country, raising $470m. Singapore’s stock market features 40 REITs that have a combined market value of $60bn.


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Input:
AI has better ‘gaydar’ than humans: Stanford University
 MODERN artificial intelligence is much feted. But its talents boil down to a superhuman ability to spot patterns in large volumes of data. Facebook has used this ability to produce maps of poor regions in unprecedented detail, with an AI system that has learned what human settlements look like from satellite pictures. Medical researchers have trained AI in smartphones to detect cancerous lesions; a Google system can make precise guesses about the year a photograph was taken, simply because it has seen more photos than a human could ever inspect, and has spotted patterns that no human could.

AI’s power to pick out patterns is now turning to more intimate matters. Research at Stanford University by Michal Kosinski and Yilun Wang has shown that machine vision can infer sexual orientation by analysing people’s faces. The researchers suggest the software does this by picking up on subtle differences in facial structure. With the right data sets, Dr Kosinski says, similar AI systems might be trained to spot other intimate traits, such as IQ or political views. Just because humans are unable to see the signs in faces does not mean that machines cannot do so.

The researchers’ program, details of which are soon to be published in the Journal of Personality and Social Psychology, relied on 130,741 images of 36,630 men and 170,360 images of 38,593 women downloaded from a popular American dating website, which makes its profiles public. Basic facial-detection technology was used to select all images which showed a single face of sufficient size and clarity to subject to analysis. This left 35,326 pictures of 14,776 people, with gay and straight, male and female, all represented evenly.

Out of the numbers

The images were then fed into a different piece of software called VGG-Face, which spits out a long string of numbers to represent each person; their “faceprint”. The next step was to use a simple predictive model, known as logistic regression, to find correlations between the features of those faceprints and their owners’ sexuality (as declared on the dating website). When the resulting model was run on data which it had not seen before, it far outperformed humans at distinguishing between gay and straight faces.

When shown one photo each of a gay and straight man, both chosen at random, the model distinguished between them correctly 81% of the time. When shown five photos of each man, it attributed sexuality correctly 91% of the time. The model performed worse with women, telling gay and straight apart with 71% accuracy after looking at one photo, and 83% accuracy after five. In both cases the level of performance far outstrips human ability to make this distinction. Using the same images, people could tell gay from straight 61% of the time for men, and 54% of the time for women. This aligns with research which suggests humans can determine sexuality from faces at only just better than chance.

Dr Kosinski and Mr Wang offer a possible explanation for their model’s performance. As fetuses develop in the womb, they are exposed to various levels of hormones, in particular testosterone. These are known to play a role in developing facial structures, and may similarly be involved in determining sexuality. The researchers suggest their system can pick up subtle signals of the latter from the former. Using other techniques, the program was found to pay most attention to the nose, eyes, eyebrows, cheeks, hairline and chin for determining male sexuality; the nose, mouth corners, hair and neckline were more important for women.

The study has limitations. Firstly, images from a dating site are likely to be particularly revealing of sexual orientation. The 91% accuracy rate only applies when one of the two men whose images are shown is known to be gay. Outside the lab the accuracy rate would be much lower. To demonstrate this weakness, the researchers selected 1,000 men at random with at least five photographs, but in a ratio of gay to straight that more accurately reflects the real world; approximately seven in every 100. When asked to select the 100 males most likely to be gay, only 47 of those chosen by the system actually were, meaning that the system ranked some straight men as more likely to be gay than men who actually are.

However, when asked to pick out the ten faces it was most confident about, nine of the chosen were in fact gay. If the goal is to pick a small number of people who are very likely to be gay out of a large group, the system appears able to do so. The point is not that Dr Kosinski and Mr Wang have created software which can reliably determine gay from straight. That was not their goal. Rather, they have demonstrated that such software is possible.

To calculate the selves of others

Dr Kosinski is no stranger to controversial research. He invented psychometric profiling using Facebook data, which relies upon information in a person’s profile to model their personality. The Trump campaign used similar models during last year’s presidential campaign to target voters, an approach which has generated criticism.

Dr Kosinski says he conducted the research as a demonstration, and to warn policymakers of the power of machine vision. It makes further erosion of privacy “inevitable”; the dangers must be understood, he adds. Spouses might seek to know what sexuality-inferring software says about their partner (the word “gay” is 10% more likely to complete searches that begin “Is my husband…” than the word “cheating”). In parts of the world where being gay is socially unacceptable, or illegal, such software could pose a serious threat to safety. Dr Kosinski is at pains to make clear that he has invented no new technology, merely bolted together software and data that are readily available to anyone with an internet connection. He has asked The Economist not to reveal the identity of the dating website he used, in order to discourage copycats.

It is true that anyone wishing to replicate Dr Kosinski’s work to determine intimate traits from faces will face significant challenges in applying laboratory science to the outside world. But they will be helped by ever-growing volumes of data and improving algorithms. “The latter, over time, inevitably win,” says Alessandro Acquisti of Carnegie Mellon University, who has shown that an individual’s social security number can be discovered using face recognition and online information. For those with secrets to keep, all this is bad news.

Dig deeper

Leader:

What machines can tell from your face

Science and technology:

Researchers produce images of people’s faces from their genomes

Business:

Ever better and cheaper, face-recognition technology is spreading

Output: Artificial intelligence can tell from photographs whether a person is straight or gay, according to research from Stanford University. The study, based on 35,000 images posted on a US dating website, found that an algorithm could correctly identify gay men 81% of the time and gay women 74% of the time. By contrast, human viewers correctly identified orientation in 61% of cases for men and 54% of cases for women. The research has highlighted concerns about the ethical implications of facial recognition software and its potential implications in relation to privacy and discrimination.


Instruction: create a high quality summary of the given input

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AI has better ‘gaydar’ than humans: Stanford University
 Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research that suggests machines can have significantly better “gaydar” than humans.

The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the biological origins of sexual orientation, the ethics of facial-detection technology, and the potential for this kind of software to violate people’s privacy or be abused for anti-LGBT purposes.

The machine intelligence tested in the research, which was published in the Journal of Personality and Social Psychology and first reported in the Economist, was based on a sample of more than 35,000 facial images that men and women publicly posted on a US dating website. The researchers, Michal Kosinski and Yilun Wang, extracted features from the images using “deep neural networks”, meaning a sophisticated mathematical system that learns to analyze visuals based on a large dataset.

The research found that gay men and women tended to have “gender-atypical” features, expressions and “grooming styles”, essentially meaning gay men appeared more feminine and vice versa. The data also identified certain trends, including that gay men had narrower jaws, longer noses and larger foreheads than straight men, and that gay women had larger jaws and smaller foreheads compared to straight women.

Human judges performed much worse than the algorithm, accurately identifying orientation only 61% of the time for men and 54% for women. When the software reviewed five images per person, it was even more successful – 91% of the time with men and 83% with women. Broadly, that means “faces contain much more information about sexual orientation than can be perceived and interpreted by the human brain”, the authors wrote.

The paper suggested that the findings provide “strong support” for the theory that sexual orientation stems from exposure to certain hormones before birth, meaning people are born gay and being queer is not a choice. The machine’s lower success rate for women also could support the notion that female sexual orientation is more fluid.

While the findings have clear limits when it comes to gender and sexuality – people of color were not included in the study, and there was no consideration of transgender or bisexual people – the implications for artificial intelligence (AI) are vast and alarming. With billions of facial images of people stored on social media sites and in government databases, the researchers suggested that public data could be used to detect people’s sexual orientation without their consent.

It’s easy to imagine spouses using the technology on partners they suspect are closeted, or teenagers using the algorithm on themselves or their peers. More frighteningly, governments that continue to prosecute LGBT people could hypothetically use the technology to out and target populations. That means building this kind of software and publicizing it is itself controversial given concerns that it could encourage harmful applications.

But the authors argued that the technology already exists, and its capabilities are important to expose so that governments and companies can proactively consider privacy risks and the need for safeguards and regulations.

“It’s certainly unsettling. Like any new tool, if it gets into the wrong hands, it can be used for ill purposes,” said Nick Rule, an associate professor of psychology at the University of Toronto, who has published research on the science of gaydar. “If you can start profiling people based on their appearance, then identifying them and doing horrible things to them, that’s really bad.”

Rule argued it was still important to develop and test this technology: “What the authors have done here is to make a very bold statement about how powerful this can be. Now we know that we need protections.”

Kosinski was not immediately available for comment, but after publication of this article on Friday, he spoke to the Guardian about the ethics of the study and implications for LGBT rights. The professor is known for his work with Cambridge University on psychometric profiling, including using Facebook data to make conclusions about personality. Donald Trump’s campaign and Brexit supporters deployed similar tools to target voters, raising concerns about the expanding use of personal data in elections.

In the Stanford study, the authors also noted that artificial intelligence could be used to explore links between facial features and a range of other phenomena, such as political views, psychological conditions or personality.

This type of research further raises concerns about the potential for scenarios like the science-fiction movie Minority Report, in which people can be arrested based solely on the prediction that they will commit a crime.

“AI can tell you anything about anyone with enough data,” said Brian Brackeen, CEO of Kairos, a face recognition company. “The question is as a society, do we want to know?”

Brackeen, who said the Stanford data on sexual orientation was “startlingly correct”, said there needs to be an increased focus on privacy and tools to prevent the misuse of machine learning as it becomes more widespread and advanced.

Rule speculated about AI being used to actively discriminate against people based on a machine’s interpretation of their faces: “We should all be collectively concerned.”

Contact the author: sam.levin@theguardian.com

Output: Artificial intelligence can tell from photographs whether a person is straight or gay, according to research from Stanford University. The study, based on 35,000 images posted on a US dating website, found that an algorithm could correctly identify gay men 81% of the time and gay women 74% of the time. By contrast, human viewers correctly identified orientation in 61% of cases for men and 54% of cases for women. The research has highlighted concerns about the ethical implications of facial recognition software and its potential implications in relation to privacy and discrimination.


Instruction: create a high quality summary of the given input

Input:
Solutions proposed to make housing in Australia more affordable
 The housing affordability crisis will drag on for at least 40 years unless governments introduce bold new policy, a major report says.

The damning outlook from the Committee for Economic Development of Australia said government policy at all levels needed to reflect that the Australian dream of owning a home is now over for many people.

“CEDA’s research shows that barring any major economic jolts, demand pressures are likely to continue over the next 40 years and supply constraints will continue,” said Rodney Maddock, CEDA Research and Policy Committee Chairman.

“This is particularly the case in capital cities with a growing population and where an increasing proportion of Australia’s population are expected to reside.”

While the report predicted bad news, CEDA made eight recommendations on how governments could contain the crisis.

Professor Maddock said he was hopeful the solutions could be adequately implemented in time.

“It’s such an important political issue at the moment, I think that we’re starting to get the more urgent responses that you might want,” he told The New Daily.

“It’s not something you can put off forever, because voters are going to get angrier and angrier.”

1. Prioritise shelter for the disadvantaged

The first solution was for Australia to provide 20,000 new affordable homes for low-income people each year, under the recommendation of Sydney University expert Judith Yates.

“Prolonged housing affordability issues will result in more people entering retirement without owning their home and low socioeconomic households pushed to outer or regional areas where transport infrastructure is poor and job prospects are lower,” Prof Maddock said.

“In the long term this could have budget implications for governments as more people become reliant on government assistance.”

2. Relax planning restrictions to increase housing affordability

The report recommended relaxing planning restrictions, particularly those imposed by local councils, to make them more consistent and allow for increased density.

One of the biggest takeaways of the report was that Sydney and Melbourne needed to forego white picket fences for apartments.

“The point is, if we don’t adjust supply then it’s going to get harder and harder to buy the very limited number of houses that are available in good locations,” Prof Maddock said.

“If we allow a lot more apartment buildings and a lot more density, then it’ll be like living in London or New York.

“People are becoming a lot more accustomed to the idea that we’re going to have a lot more apartment dwelling … There’s an emotional adjustment going on.”

3. Develop consistent planning and funding for transport

The report said faster and more convenient transport networks would increase the amenity of outer suburbs and ease congestion.

Prof Maddock said we needed to change the structure of our cities to have a range of employment hubs. For example, Parramatta in Sydney’s west has become a secondary business district and decreased the commute time for residents in the outer suburbs.

4. Better legal protection and certainty for renters

The report said more protections for renters were required as the likelihood Australians rent their whole lives increases.

“It seems quite likely that many people are going to end up living in rental accommodation for all their lives,” Prof Maddock said.

He recommended renters be given long-term rental options.

5. Offer incentives to downsize

The report recommended the government relax rules for means testing income from downsizing, if it freed up more land.

Prof Maddock said this change was slowly occurring naturally over time as house prices and land prices continue to rise.

“It’ll become more sensible for investors to put more houses on a piece of land,” he said.

6. Phase out stamp duty in favour of annual land tax

The government should begin charging an annual land tax instead of stamp duty, the report said.

7. Review asset tests for retirees

The report advised the government to review the way pensions, superannuation and housing interacted for retirees.

8. Increase capital gains taxes

Taxing a larger component of capital gains would also make investments less attractive, the report said.

“Easing some of the tax incentives to invest in or retain residential property may also assist,” Prof Maddock said.

Output: The Committee for Economic Development of Australia (CEDA) has said that unless the government introduces new policies, housing affordability will continue to be a problem for 40 years. CEDA said that owning a home will be unattainable for many Australians. The committee has suggested that the government make several changes: prioritise shelter for disadvantaged citizens, relax planning restrictions to favour flats over houses; fund and plan transport more effectively; protect renters’ legal rights, incentivise downsizing, replace stamp duty with an annual land tax, review the current retiree asset tests and increase capital gains tax.


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Growing demand in central US prompts two hirings for XL Catlin
 NEW YORK, Aug. 31, 2017 /PRNewswire/ -- XL Catlin's Global Excess Casualty insurance business has realigned its US Central region and appointed new regional underwriting managers to meet continued increased demand for quality excess casualty and umbrella insurance products.

According to Barbara Luck, President of XL Catlin's Global Excess Casualty business, "We've had tremendous success developing and growing client and broker relationships and business throughout the US. Our continued successes are prompting us to make these regional changes. Given the size of the US market and continued increased demand for our excess coverages, we decided to create a North Central and South Central region to better enable our team to deliver more attentive service and delivery of our excess and umbrella liability coverages to brokers and clients. This new regional structure better prepares our team for continued business growth."

Kevin Nieft has been promoted to Vice President, Underwriting Manager Excess Casualty and will lead the North Central Region. Kevin joined XL Catlin in April 2003 and has held various underwriting positions and most recently was an underwriting director. Prior to joining XL Catlin, Kevin held underwriting positions in Kemper Insurance Company and Fireman's Fund Insurance Company.

Mona Carpenter has been promoted to Vice President, Underwriting Manager Excess Casualty and will lead the South Central Region. Mona joined XL Catlin in October 2016 from Swiss Re where she held the position of Vice President Senior Underwriter. Prior to that position, Mona held various underwriting and management positions at AIG and The Hartford.

Ms. Luck added: "We're fortunate to have a deep bench of strong talent to build out our regional leadership. Both Kevin and Mona bring their underwriting expertise of the Excess Casualty product and strong marketplace knowledge and relationships to their new roles. Under their leadership, our North Central and South Central regions are well positioned to take a more geographic focused approach in addressing our broker and client's excess and umbrella liability needs.

Helping a wide range of businesses -- from Upper Middle Market (UMM) to Fortune 1000 companies -- XL Catlin's Global Excess Casualty insurance team provides Lead Umbrella, Excess, Occurrence, Claims Made, Occurrence Reported and Primary Rail and Excess insurance coverages from global access points with underwriting centers in Bermuda, Dublin, Ireland, London, UK and 13 cities in North America. Liability limits up to $100 million are available.

About XL Catlin Insurance Operations

XL Catlin insurance companies offer property, casualty, professional, financial lines and specialty insurance products globally. Businesses that are moving the world forward choose XL Catlin as their partner. To learn more, visit xlcatlin.com.

About XL Catlin

XL Catlin is the global brand used by XL Group Ltd's (NYSE:XL) insurance and reinsurance companies which provide property, casualty, professional and specialty products to industrial, commercial and professional firms, insurance companies and other enterprises throughout the world. Clients look to XL Catlin for answers to their most complex risks and to help move their world forward. To learn more, visit xlcatlin.com .

View original content with multimedia:http://www.prnewswire.com/news-releases/xl-catlins-global-excess-casualty-insurance-business-promotes-new-regional-underwriting-leaders-300512210.html

SOURCE XL Catlin

Output: Insurer XL Catlin's global excess casualty business has appointed underwriting managers for the north central and south central US regions to cope with stronger demand for excess casualty and umbrella insurance products. Kevin Nieft will become vice-president, underwriting manager, excess casualty for north central and Mona Carpenter will be vice-president, underwriting manager, excess casualty for south central. XL Catlin's global excess casualty products cover umbrella, excess, claims made, occurrence, occurrence reported and primary rail.


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Redrow Redrow nears completion on £70m Devonport Estate
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The biggest city regeneration scheme in the South West will be complete when the last few families move into a £70million Devonport estate next month.

Developer Redrow has virtually finished construction at the vast 464-property Vision project in what was once the Royal Navy South Yard Enclave.

The final building, Zone G, on what was the sales office’s car park on the corner of Phelps Road and Chapel Street, is nearly ready.

And by October 2017 all homes will be filled on the immense estate and it will be home to more than 1,100 people.

(Image: Penny Cross)

That will complete the ambitious scheme which Redrow started in 2007, in what was once a dockyard stores area.

But the firm is keen to point out its legacy will continue, as it has invested in an array of community projects and has provided £700,000 towards the transformation of the former Devonport Market Hall into a digital industry hub.

And it has had a major impact on the economy of he city, with up to 80 construction workers, including apprentices, on the site each day during the decade-long build.

(Image: Penny Cross)

Nigel Palmer, managing director for Redrow Homes’ South West division, said: “We have employed 70 to 80 people here on a daily basis,” he said. “Then there is the spin-offs, money going to the local stores.

“Then there is the legacy, we have invested £700,000 into the Market Hall, to reinstate the bells and clock tower, and for security and upkeep of the building.”

He said £3.7million had been paid over in Section 106 payments, contributions made to the local authority.

(Image: Penny Cross)

“That went to education, transport, highways, and for public areas, such as Granby Green, which benefited from £250,000.”

The Devonport Views 42-flat extra-care housing block for older people was paid for by Redrow but managed by Devon and Cornwall Housing.

But Mr Palmer stressed Redrow had gone beyond it’s statutory obligations, and pumped cash and support into community organisations and events, including St Aubyn’s Church, Devonport Linc, Royal Society for the encouragement of Arts, Devonport Boxing Club, three primary schools, police cadets, carol festivals, family fun days and poetry events, including sponsorship of the PlymLit literary festival in 2016 and 2017.

(Image: Penny Cross)

“I’m really proud at what the guys have achieved,” Mr Palmer said. “They’ve done a fantastic job here and left a legacy.”

Vision, alongside other neighbouring housing schemes and social enterprise-led business initiatives, has transformed what was once one of Plymouth’s most crime and deprivation-troubled quarters into a pleasant, modern, and prosperous area.

Other projects surrounding Vision include the redevelopment of the former naval base at Mount Wise, and replacement of housing in between it and Vision, and at Granby Green.

(Image: Penny Cross)

Some of this new housing was created by Linden Homes – where Mr Palmer worked before joining Redrow.

And as a “Plymouth boy”, who was educated at nearby Devonport High School for Boys, he’s well qualified to give a view on the area’s improvement.

“It’s transformed the whole area,” he said. “The West side of Plymouth has changed for the better.”

Output: Housing developer Redrow will shortly complete construction at the 464 unit Vision regeneration project in Plymouth. The £70m ($93m) project is based at the old site of the Royal Navy South Yard Enclave, and can house over 1,100 residents. The project was initiated in 2007, and involved the provision of £700,000 by Redrow to transform the former Devonport Market Hall into a digital industry meeting place.


Instruction: create a high quality summary of the given input

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BNP Paribas buys majority stake in Belgian robo-adviser Gambit
 BNP Paribas has made a move into the robo-advisory sector, buying a majority stake in Belgian specialist Gambit Financial Solutions. Terms of the deal were not disclosed.

While Gambit will maintain its independence, it will become the preferred partner for robo-advisory solutions for BNP Paribas Group’s retail and wealth management networks.

Launched in 2007 as a spin-off from HEC - University of Liege, Gambit has seen its robo-advisory technology rolled out by private and retail banks in Belgium, Luxembourg, France and Switzerland.

The firm, which has a 50-strong team, has also recently launched a proprietary business-to-consumer robo-advisor called Birdee.

Frédéric Janbon, CEO, BNP Paribas Asset Management, says: "The partnership with one of the most advanced robo-advisory solutions available in the market is a key milestone in our digital transformation and marks our commitment to delivering quality investment solutions to our clients."

Output: Paris-based banking group BNP Paribas has bought a majority stake in the Belgian robo-advisory specialist firm Gambit Financial Solutions. The company was launched in 2007 as a spin-off from the HEC - University of Liege, and its technology has been used by private and retail banks in Belgium, Luxembourg, France and Switzerland. Under the deal, Gambit will maintain its independence, but will become the preferred partner for robo-advisory solutions for BNP Paribas's retail and wealth management networks.


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Social trading platform eToro lets users trade cryptocurrencies
 Social trading brokerage and platform provider eToro today announced in a corporate statement that it is offering clients the opportunity to trade in the five most popular Cryptocurrencies Cryptocurrencies By using cryptography, virtual currencies, known as cryptocurrencies, are nearly counterfeit-proof digital currencies that are built on blockchain technology. Comprised of decentralized networks, blockchain technology is not overseen by a central authority.Therefore, cryptocurrencies function in a decentralized nature which theoretically makes them immune to government interference. The term, cryptocurrency derives from the origin of the encryption techniques that are employed to secure the netw By using cryptography, virtual currencies, known as cryptocurrencies, are nearly counterfeit-proof digital currencies that are built on blockchain technology. Comprised of decentralized networks, blockchain technology is not overseen by a central authority.Therefore, cryptocurrencies function in a decentralized nature which theoretically makes them immune to government interference. The term, cryptocurrency derives from the origin of the encryption techniques that are employed to secure the netw Read this Term directly on its own Trading Platform Trading Platform In the FX space, a currency trading platform is a software provided by brokers to their respective client base, garnering access as traders in the broader market. Most commonly, this reflects an online interface or mobile app, complete with tools for order processing.Every broker needs one or more trading platforms to accommodate the needs of different clients. Being the backbone of the company’s offering, a trading platform provides clients with quotes, a selection of instruments to trade, real In the FX space, a currency trading platform is a software provided by brokers to their respective client base, garnering access as traders in the broader market. Most commonly, this reflects an online interface or mobile app, complete with tools for order processing.Every broker needs one or more trading platforms to accommodate the needs of different clients. Being the backbone of the company’s offering, a trading platform provides clients with quotes, a selection of instruments to trade, real Read this Term.

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Effective immediately, eToro customers can trade the actual underlying assets of Bitcoin, Ethereum, Ethereum Classic, Litecoin and Ripple. The company is already offering access to the five cryptocurrencies, plus exposure to Dash, through its recently launched investment instrument Crypto CopyFund.

By taking away part of the risk usually associated with trading such exotic assets, eToro allows its clients profit directly from the active exchange rates. Joining over 1,200 assets, trading of the new instruments will be done from the same accounts clients use for other trades, adding a layer of security to the exciting but volatile cryptocurrency market.

The step confirms that there is significant demand amongst traders for such alternative asset classes, with the launch just one more example of a brokerage jumping on the cryptocurrency bandwagon.

The list of brokers that have launched cryptocurrency trading pairs in recent months includes Ayondo, Plus500, Avatrade, FXOpen, XTB, JFD Brokers, Instaforex, and many others. As such, it is likely that more retail platforms will follow suit to avoid falling behind their competitors.

Commenting on the launch, Yoni Assia, co-founder and CEO of eToro, said: "Cryptocurrencies have come of age over the last year, but buying and owning the underlying crypto asset is still very difficult. At eToro, we've already simplified the worlds of trading and investing, and now we have an opportunity to use our experience and expertise to simplify cryptocurrencies. By using our platform, investors benefit from the peace of mind that comes with our long-track record in the cryptocurrency market."

Founder of Litecoin Charlie Lee said: "By making Litecoin available on a safe, simple, and secure platform, eToro will help increase the adoption of Litecoin among a wider audience."

Founder and CEO of Digital Currency Group (DCG) Barry Silbert said: "By showing their support for Ethereum Classic, among others, eToro supports our position that digital currency as an asset class has not only arrived, but is here to stay."

Output: eToro, the social trading brokerage firm, has given a boost to the digital currency sector by enabling customers to trade bitcoin, ethereum, ethereum classic, litecoin and ripple cryptocurrencies on its platform. The move allows clients to benefit from active exchange rates, and is further evidence of the growing demand for alternative asset classes. Ayondo, XTB, JFD Brokers and Instaforex, among others, have also also launched cryptocurrency trading pairs, with market expectations that more retail platforms will follow.


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Blockchain wallet partners with Indian exchange UnoCoin
 Leading bitcoin wallet Blockchain has announced that it has teamed up with Indian bitcoin exchange Unocoin to enable Blockchain users across the country to quickly and easily fund their wallets.

We’ve teamed up with Unocoin to bring users in India an easy and safe way to fund their Blockchain wallets! https://t.co/rsiyxeEiG6 pic.twitter.com/JT6tHQafds — Blockchain (@blockchain) September 7, 2017

“Millions of Indians have embraced digital assets as a reliable way to save and transfer money. Together with Unocoin we are committed to making digital currency simple and more accessible throughout India. Whether it’s high fees, untrustworthy service providers, or confusing identity verification procedures, it’s often been a slow and challenging process to get started with bitcoin. Today’s integration is an important step forward in eliminating the friction that many have experienced in buying bitcoin.”

According to the official announcement, Blockchain has integrated Unocoin’s exchange directly within its wallet to give users greater purchasing power without compromising security or control. The integration is currently available to web users. Blockchain said:

“For the first time ever, your Blockchain wallet can be funded in just a few clicks by linking your bank account, which is subject to bank transfer speed.

Blockchain said that it plans to expand the integration to Android and iOS wallet users in the near future.

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Output: Bitcoin wallet Blockchain has partnered with Indian's largest bitcoin exchange Unocoin, enabling customers to transfer funds quickly. The move was an "important step forward in eliminating the friction that many have experienced in buying bitcoin" and gave users "greater purchasing power without compromising security or control", according to Blockchain. The functionality is available only to web users, with mobile integration set to follow.


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ILS likely to contribute to reinsurance pricing drop: Fitch
 Pricing in the global reinsurance sector will continue declining throughout 2018 as competition from alternative sources of reinsurance capacity intensifies and margins across the sector deteriorate further, according to analysis by Fitch Ratings.

The current low-interest rate environment is expected to remain, dampening returns on the investment side of the balance sheet as underwriting profits come under increasing pressure from falling rates and intense competition.

Fitch expects pricing in the reinsurance industry to deteriorate in 2018 as alternative capital, or insurance-linked securities (ILS) intensifies the competition for reinsurance business.

“This will mainly be driven by the collateralised reinsurance segment, where funds are likely to expand their reinsurance capacity at lower pricing margins,” explains Fitch.

Furthermore, Fitch expects that market conditions will likely remain favourable for catastrophe bond issuance in 2018 as investors look to diversify risks, on the back of what’s set to be a record year for cat bond issuance after an impressive Q2 for the expanding sub-sector of the broader ILS arena.

Fitch warns of “shrinking headroom” for global reinsurance companies, exacerbated by the impacts of hurricane Harvey and further deterioration of pricing metrics. However, the ratings agency doesn’t expect any substantial impact on ratings over the next 12 to 18 months, but warns that the deterioration of the pricing environment beyond its expectations, could lead to some negative actions.

Discussing hurricane Harvey, Fitch notes that a relatively light opening six months for catastrophe losses across the industry should assist companies’ as they absorb losses from the event, which brought record-levels of flooding to Houston, Texas.

Fitch doesn’t expect the losses to be enough to turn the market from its soft state and have any impact on pricing outside of the directly affected regions, and overall, expects much of the loss to be retained by primary insurers and be more of an earnings event for the reinsurance sector.

However, Harvey does leave some companies with perhaps a smaller catastrophe budget for the remainder of the year than desirable, which suggests that above-average catastrophe losses for the remainder of the year could push some firms into a very challenging position, to say the least.

“Combined with low investment yields, which are likely to persist in 2018, the significant decline in premium rates over the last few years has made it harder for reinsurers to write business at a profit margin that exceeds their cost of capital. Their ability to use prior-year reserves to mitigate the pressure on operating profit is also dwindling, and we do not expect firms to be able to maintain reserve releases at their current levels in the medium term,” warns Fitch.

For the reinsurance companies that Fitch monitors, it expects the group to report a combined ratio of 96.9% in 2018, and an operating ratio of 89.9%. However, should these ratios rise to above 100% and 90%, respectively, in the mid-term, Fitch could revise its rating outlook for the sector to negative.

Output: The growth of insurance-linked securities (ILS) – capital market investment vehicles backed by insurance policies – will contribute to a further decline in reinsurance pricing during 2018, according to Fitch Ratings. ILS and other sources of reinsurance capacity have already dented pricing in the sector. The decline may lead to rating downgrades for some reinsurance companies, Fitch said. Conversely, the ratings firm predicts the market for catastrophe bonds will remain favourable as investors look to diversify risk.


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Renaissance integrates digital resources from Education.com
 Personalized Learning

Renaissance Flow 360 Integrates Teacher-Approved Resources

Renaissance has partnered with Education.com in order to bring teacher-approved digital resources, tools and materials from the online education hub to the Renaissance Flow 360 platform.

Teachers can use Renaissance Flow 360 to track students' level of mastery at the domain, standard, skill and subskill level. Image: Renaissance.

The pre-K–12 learning analytics company launched Renaissance Flow 360 earlier this year to support personalized learning at schools by “connecting assessment, planning, instruction and practice in one place,” according to a prepared statement.

To date, an estimated 6.8 million teachers have signed up to use Education.com's digital learning materials, which will now be mapped to Renaissance’s learning progressions. The integration also enables teachers to use Renaissance Flow 360 "to track a complete view of student’s mastery of state standards and skill level at group or individual levels."

There are more than 30,000 teacher-approved educational resources on Education.com.

Through the partnership, Education.com joins Achieve 3000, Classworks, Edgenuity, Edmentum and the MIND Research Institute as part of the Renaissance Growth Alliance Partners program.

Output: US learning analytics company Renaissance has added Education.com to its list of partners, allowing integration of materials from the online education provider to its existing services. The company launched its Renaissance Flow 360 platform earlier this year, to support personalised learning in schools by providing teachers with a means of coordinating assessments with lesson plans to track students' progress. Digital materials from Education.com are currently used by an estimated 6.8 million teachers, and these will now be mapped onto Renaissance's system.


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EY and Microsoft partner to provide marine insurance blockchain
 Accounting giant EY said Wednesday that it plans to launch the first blockchain platform for marine insurance, alongside Microsoft , A.P Moller-Maersk and others.

The distributed ledger will be used to capture information about shipments, risk and liability, and to help firms comply with insurance regulations.

It will also ensure transparency across an interconnected network of clients, brokers, insurers and other third parties.

EY explained that its decision to secure marine insurance data with blockchain was due to a "complete inefficiency" in the sector.

"The reason we chose marine (insurance) as the starting point for this sort of market is mainly because of its complete inefficiency," Shaun Crawford, global insurance leader at EY, told CNBC via phone earlier this week ahead of the announcement.

Crawford said the industry was "over capacity" and that there was "a lot of cost to it."

He added: "It's facing high administrative burdens of managing and writing claims with a lot of paperwork. All contracts are signed multiple times. They go from ship to ship, port to port, through quite a journey."

Distributed ledgers are groupings of data shared across multiple locations without the need for central administrators and other middle men.

The original blockchain was built to serve as the distributed ledger for bitcoin transactions. But various blockchain experts believe the technology can provide transparency for a multitude of different industries, not just the financial services.

"We're not talking about a new currency here, we're not talking about money. We're talking about data aggregation," EY's Crawford added.

Maersk said the blockchain platform would enable the shipping giant to maintain a smoother relationship with the insurance market.

Output: EY has collaborated with Microsoft, shipping firm Moller-Maersk and other companies to develop the world's first blockchain platform for marine insurance, aiming to streamline a sector bogged down by "complete inefficiency". Shaun Crawford, global insurance leader at EY, said the project aimed to bring transparency to the industry and reduce the high administrative burdens, while capturing information about shipments, risk and liability in a secure manner. The platform will be built by blockchain firm Guardtime using Microsoft's Azure cloud, and is set to be launched in 2018.


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Growing demand in China for online US English tutors
 Firms providing overseas internet tutors could share US$165-billion market in five years, says one research report, as parents look to give their children a head start

Output: Growing demand amongst Chinese parents for online tutors from the US is contributing to a growing market, which could double in value to $165bn in the next five years, according to banking group UBS. Online start-ups include Beijing-based VIPKid, which recruits American teachers to teach online classes to Chinese students. The company has grown to 200,000 students and has revenue projected to reach $765m this year. The company has set up a research institute to process the huge amounts of data gathered from the two million classes taught each month, to help improve their effectiveness.