Last week, the Dutch Scientific Council for Government Policy (WRR) found that the Netherlands is not well prepared for the consequences of artificial intelligence (AI). In Challenge AI, The New Systems Technology (in Dutch), the council calls for regulation of technology and data, its use, and social implications. And rightly so. Machines will have more computing power than humans in a few decades. If devices with artificial intelligence then start to think and decide for themselves, it is to be hoped that they will observe a number of commandments.

AI is also entering mobility, and the problems the WRR refers to are also at play there. The most imaginative AI appearance in mobility is the autonomous car. It is potentially much safer and more comfortable, but there are tricky liability issues if an accident occurs. Should you as a human always be able to override the system? And what would it take for a self-driving car to interpret the law flexibly when necessary? This is something we, as humans, do every minute in daily traffic, precisely in the service of safety.

One day, when I was driving along with traffic at 120 km/h on the E25 through the Ardennes, my automatic cruise control suddenly lowered the speed limit to 70 km/h because the road workers had forgotten to remove a speed sign. Fortunately, I was able to override that and not adhere to that officially legal speed limit. Despite this example, however, in the future, we should not start allowing extremely smart machines to be flexible with the rules, just like us, without any ethical or moral framework. That could lead to dystopian states where machines, perhaps unintentionally, start endangering humanity.

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But the AI issues in mobility go far beyond the self-driving car. What if Google or TomTom takes over traffic management from the road authority? What if the big tech giants take over the entire planning of public transport once people plan their journeys solely through their services? What if those platforms, after a friendly free initial period, start abusing their achieved monopolies? Who will guarantee availability and safety? Cab services like Uber are more popular than the classic taxi, but who can oblige them, as with regulated cab transport, to also accept guide dogs and wheelchairs, for example, so that a significant part of society is not left aside?

Artificial intelligence will make mobility better, safer, and more comfortable. But these systems need ethical and moral frameworks within which they can achieve this. In the Netherlands, companies, and knowledge institutions have already united in the Dutch AI Coalition. They received 276 million from the growth fund earlier this year to strengthen the Dutch position internationally. Wisely, the first part of that goes to so-called Elsa labs: Ethical, Legal & Societal aspects of AI, in which consortia focus on these aspects. Just as in mobility, AI will help steer other areas as well, but we still want to be able to take the wheel ourselves.

Maarten Steinbuch and Carlo van de Weijer are alternately writingthis weekly column, originally published (in Dutch)in FD. Did you like it? Theres more to enjoy: a book with a selection of these columns has just been published by24U and distributed byLecturis.

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Artificial intelligence and mobility, who's at the wheel? - Innovation Origins

December 7th, 2021

2:00 PM - 3:00 PM EDT

*Eligible for HRCI and SHRM recertification credits

With the expansion of Talent Acquisition responsibilities and complex landscape from hiring recovery, talent redeployment, the great resignation, and DE&I initiatives, there has never been a greater need for intelligent, augmentation and automation solutions for recruiters, managers, and sourcers. There is also growing awareness of problematic artificial intelligence solutions being used across the HR space and the perils of efficiency and effectiveness solutions at the cost of fairness and diversity goals. These concerns are compounded with increased inquiries from employees and candidates of the AI solutions used to determine or influence their careers, particularly whats inside the AI and how they are tested for bias. Join this one-hour webinar hosted by HiredScore CEO & Founder Athena Karp as she shares:

Speakers

Athena Karp

CEO & Founder @HiredScore

Athena Karp is the founder and CEO of HiredScore, an artificial intelligence HR technology company that powers the global Fortune 500. HiredScore leverages the power of data science and machine learning to help companies reach diversity and inclusion goals, adapt for the future of work, provide talent mobility and opportunity, and HR efficiencies. HiredScore has won best-in-class industry recognition and honors for delivering business value, accelerating HR transformations, and leading innovation around bias mitigation and ethical AI.

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[Webinar] Balancing Compliance with AI Solutions - How Artificial Intelligence Can Drive the Future of Work by Enabling Fair, Efficient, and Auditable...

The words "artificial intelligence" evoke a futuristic world, but at certain Long Island hospitals, the future is here and now.

At some hospitals, nurses track the severity of patients symptoms with help from artificial intelligence, a broad term that encompasses computer programs that can be fed huge volumes of data and trained to analyze new data.

Others use A.I. to predict which patients are at risk of becoming ill again because they dont follow instructions after theyre discharged, or those who are healthy enough to be allowed to sleep through the night instead of being awakened to have their vital signs checked. Still others use the technology to speed the analysis of sleep studies that help diagnose conditions such as sleep apnea.

The ventures vary widely in their origins, scope and funding. One is a new company called Truveta, formed in an unusual alliance between New Hyde Park-based Northwell Health and 19 other health systems across the country. The company, which recently announced $200 million in new private funding, pulls information from millions of the networks patient records anonymized to protect confidentiality and provides real-time analysis to health care providers.

Northwell Healthhas joined forces with 19 other health systems to start acompany called Truveta, which recently announced $200 million in new private funding from its member networks and its CEO, Terry Myerson. Using information from millions of the networks anonymized patient records, the company provides real-time analysis to health-care providers.

NYU Langone Hospital-Long Islandin Mineola has launched an A.I.-powered program that tracks COVID-19 patients vital signs, lab results and other information, recording17 data points every 30 minutes to detect signs of potential deterioration.

Mount Sinai South Nassau in Oceansideuses A.I. to detect patients' risks of falling or becoming severely ill, and to predict how much nursing care they will need.

Stony Brook University'sDepartment of Biomedical Informaticshas received more than $5 million in federal grants to research the potential use of A.I. in diagnosing and treating cancer.

Catholic Health uses A.I.to analyze patients' brain waves, breath patterns, cardiac signals, leg movements and other data points recorded during sleep studies, speeding up the completion of reports that are reviewed by board-certified physicians.

Sources: Northwell Health, NYU Langone Health,Mount Sinai South Nassau,Stony Brook University,Catholic Health

Northwell sees "revolutionary potential" in A.I., Dr. Martin Doerfler, Northwells senior vice president of clinical strategy and development, said in an interview, "and we wanted to be part of it."

On a different scale, another new program got its start on a local nurses laptop during the coronavirus surge last year. After months of research and development, it evolved into an A.I. tool that flags COVID-19 patients at NYU Langone Hospital-Long Island who are at high risk of becoming severely ill in the next 12 hours.

The A.I. program "doesn't take over your decision-making and it never should," said Jeanmarie Moorehead, senior director of operations at the Mineola hospital. "But it is definitely value-added, tremendous value-added to the clinician."

What the A.I. efforts have in common is an ambitious effort to use specialized computer programs to comb through columns of data too vast to be understood by a human being, detect patterns and use that information to guide health care providers in diagnosing and treating patients.

The use of A.I. in health care is on the rise, with global funding in the sector reaching $8.5 billion from January through September nearly double the amount in all of 2019, according to CB Insights, a company that tracks A.I. investments. The United States was the biggest spender, with investments in A.I. in health care totaling $5.45 billion from January through September, the company reported.

Health care technology, including A.I., "is clearly seeing an increased level of investment," especially over the last year and a half, said Peter Micca, a partner and national health tech leader with Deloitte & Touche LLP in Manhattan. "COVID has only accelerated the awareness around the importance of technology in health care."

One hurdle is that, in contrast with industries such as finance and social media, health care data "is completely fragmented," Doerfler said. "We need to know the answers that are hidden inside the fragmented data, and you don't get the answers until you get the data sets large enough that you can find the answers quickly."

Incomplete data sets often lack diversity of race, gender, socioeconomic status and other characteristics, and overrepresent middle-aged white men with health insurance, Doerfler said. By contrast, said Terry Myerson, Truveta's CEO, the data set drawn from its 20 networks represents 16% of all clinical care provided in the United States and reflects "the diversity of our country."

The goal of Truveta, Myerson said, is to "empower our clinicians to be experts" and "help families make the most informed decisions about their care."

Some industry analysts warn of potential pitfalls in the adoption of A.I. At the annual conference of Stony Brook University's Center of Excellence in Wireless and Information Technology this month, Daniel Holewienko, executive director, big data and business intelligence at Henry Schein in Melville, said failing to embrace A.I. would put health care companies "at a competitive disadvantage."

Still, he said, those adopting the new technology can face high costs and difficulties integrating it into their current systems, among other challenges. Protecting privacy, preventing bias and making sure clinicians do not place excessive faith in the machines are among the other concerns, health care providers say.

Dr. Joel Saltz, founding chair of the Department of Biomedical Informatics at Stony Brook University, said the industry has proceeded cautiously in adopting A.I. The advanced technology has become more widely used in the last five years or so, he said.

"These things are incremental, especially in health care, because you've got to make sure they're safe and effective," said Saltz, who is working with colleagues on a project led by the federal Food and Drug Administration, focusing on the use of A.I. in digital pathology. Such tools, he said, are used for "decision support," to aid doctors and nurses rather than replace their work.

Stony Brook's biomedical informatics department is working on three projects funded by more than $5 million in federal grants to research the potential use of A.I. in diagnosing and treating cancer. An A.I. program can examine hundreds of slides and analyze millions of cells, complementing doctors' ability to visually classify tumors, Saltz said. "Think about the difference between a paper map and Google Earth," Saltz said. "It really opens up a whole new way of doing things."

It's possible that some of the research could be put into clinical practice within 10 years, he said.

In some cases, the COVID-19 crisis has sparked innovation by doctors, researchers and nurses as they raced to understand the new virus and find ways to save patients lives. Nurses have been key players in using and, in at least one case, helping to develop the new technology.

At NYU Langone Hospital-Long Island in Mineola, for instance, computers are running a new A.I.-powered program that keeps an eye on COVID-19 patients vital signs, lab results and other information, using patients' electronic medical records to monitor 17 data points every 30 minutes and detect signs of impending danger.

A paper version of the program was born of necessity during the first COVID surge in early 2020. At the time, nurse clinician Cathrine Abbate was seeking a rapid, consistent way to communicate with her fellow nurses and doctors about the severely ill patients suffering from a new and brutal virus.

On video conference calls before and after their shifts, Abbate and other nurses brainstormed about the warning signs that tended to precede a rapid decline in patients condition, such as needing large amounts of oxygen or not being able to eat or move. With that information, she used Microsoft Word to create a blank grid that she printed out at her home in Huntington Station. The grid included seven columns, tracking information about the patients condition. In the hospital, using copies of the grid made it easier for nurses to quickly rank the severity of each symptom and give an overall rating from 1 to 10, with 10 being the worst, she said.

"We needed to be able to fluidly communicate with each other about how the patients were doing," Abbate recalled. "It was just a way to create a language for ourselves."

Nurse manager Sarojini Seemungal helped implement the new system on the 30-bed unit, and alerted her own managers. Moorehead brought it to the attention of researchers at NYU Langone in Manhattan who specialize in analyzing data.

The researchers spent months meeting weekly with nurses and developing an A.I. program that provides information to a rapid response team of critical care nurses at the Long Island hospital who give special attention to the highest-risk patients, said Dr. Yindalon Aphinyanaphongs, director of operational data science and machine learning at NYU Langone Health.

The program acts as a "tireless monitor," taking information about thousands of previous patients including many whose conditions deteriorated and using it to predict whether current patients are likely to decline, he said.

Theres a lot of "hype" about A.I. and its subset machine learning, a term that refers to computers learning from examples, Aphinyanaphongs said.

"A lot of times when people think of artificial intelligence, they think of, you know, WALL-E," he said, in a reference to the 2008 animated movie about a lonely robot. But in fact, "the value in some of these models has to do with, not doing something better than humans, but doing things faster than humans can do," and more consistently, he said.

A tool like the one developed by the nurses and researchers, he said, can take a health care provider who has little experience with COVID, and it "can help elevate their experience and their expertise to the point where they're functioning at the same sort of assessment level as someone who has seen a lot of COVID patients."

The program can be downloaded for free by other hospitals that use the Epic electronic medical records system, Aphinyanaphongs said.

At Mount Sinai South Nassau in Oceanside, computers use A.I. to make sure patients receive precise, personalized care, taking into account the severity of their illnesses and other factors, said Stacey Conklin, chief nursing officer and senior vice president of patient care services. Those at higher risk of falls, for example, get extra help moving around if needed, she said.

A.I. "takes a lot of the subjectivity away from staffing, and allows us to really put the resources where they're needed most," Conklin said. "If I as a manager am trying to figure out where to put all of my resources, it's very helpful for me to be able to look broadly across the unit and see what's going on with all the patients so that I can ensure that the patients are getting the best care."

At the Catholic Health systems six sleep labs, A.I. is used to analyze the sleep studies of patients who spend the night hooked up to machines that record brain waves, breath patterns, cardiac signals, leg movements and other data points to diagnose conditions such as sleep apnea, said Brendan Duffy, director of sleep services at the network.

The data can fill hundreds of pages, and analyzing the information is "a very time-consuming, very meticulous" process that used to take one to two hours for each report, Duffy said.

Once the health system started using the A.I. program about three months ago, he said, that time was reduced to about 20 minutes, he said.

The new system means the sleep labs can get patients on the calendar for follow-up appointments more quickly, so patients spend less time driving while drowsy or suffering compromised immune systems due to sleep deprivation, he said.

But despite their remarkable efficiency, he said, the computers cant have the last word.

A board-certified physician reviews the sleep reports "each and every time, and that's nonnegotiable," he said.

At Northwells Feinstein Institutes for Medical Research in Manhasset, researchers used A.I. to analyze 24 million patient vital sign measurements. The results helped them predict which patients were low-risk enough to sleep through the night with a nurse looking in on them periodically, instead of being awakened to have their vitals checked, according to an article published last year in the journal Nature Partner Journals Digital Medicine.

The health system also is using A.I. to identify certain high-risk patients, said Dr. Jamie Hirsch, director of Northwells data science program.

In presentations about A.I., Hirsch tells his fellow physicians the technology can help identify people such as a fictional patient he has dubbed "Ethel," a sprightly 87-year-old grandmother who is "fiercely independent," but who feels overwhelmed in the hospital, lives alone and might need more assistance than she realizes.

In a busy hospital filled with hundreds of patients, a patient like Ethel might not get the hand-holding she needs, he said.

But when an A.I. program is trained to flag patients who are older, live alone and are coping with a bewildering array of medications and discharge instructions, he said, "now you have a patient experience specialist that's going to come in and say, How are you? Let's sit down, let's talk, you know, how can we make your experience better . How do we get you home, so you can continue living that independent life that you so value?"

He said, "It allows us to focus our energies in the right way, to the right person, at the right time."

Maura McDermott covers health care and other business news on Long Island.

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At LI hospitals, the artificial intelligence revolution has already begun - Newsday

Current trends in AI are nothing if not remarkable. Day after day, we hear stories about systems and machines taking on tasks that, until very recently, we saw as the exclusive and permanent preserve of humankind: making medical diagnoses, drafting legal documents, designing buildings, and even composing music.

Our concern here, though, is with something even more striking: the prospect of high-level machine intelligence systems that outperform human beings at essentially every task. This is not science fiction. In a recent survey the median estimate among leading computer scientists reported a 50% chance that this technology would arrive within 45 years.

Importantly, that survey also revealed considerable disagreement. Some see high-level machine intelligence arriving much more quickly, others far more slowly, if at all. Such differences of opinion abound in the recent literature on the future of AI, from popular commentary to more expert analysis.

Yet despite these conflicting views, one thing is clear: if we think this kind of outcome might be possible, then it ought to demand our attention. Continued progress in these technologies could have extraordinarily disruptive effects it would exacerbate recent trends in inequality, undermine work as a force for social integration, and weaken a source of purpose and fulfilment for many people.

In April 2020, an ambitious initiative called Positive AI Economic Futures was launched by Stuart Russell and Charles-Edouard Boue, both members of the World Economic Forums Global AI Council (GAIC). In a series of workshops and interviews, over 150 experts from a wide variety of backgrounds gathered virtually to discuss these challenges, as well as possible positive Artificial Intelligence visions and their implications for policymakers.

Those included Madeline Ashby (science fiction author and expert in strategic foresight), Ken Liu (Hugo Award-winning science fiction and fantasy author), and economists Daron Acemoglu (MIT) and Anna Salomons (Utrecht), among many others. What follows is a summary of these conversations, developed in the Forum's report Positive AI Economic Futures.

Participants were divided on this question. One camp thought that, freed from the shackles of traditional work, humans could use their new freedom to engage in exploration, self-improvement, volunteering, or whatever else they find satisfying. Proponents of this view usually supported some form of universal basic income (UBI), while acknowledging that our current system of education hardly prepares people to fashion their own lives, free of any economic constraints.

The second camp in our workshops and interviews believed the opposite: traditional work might still be essential. To them, UBI is an admission of failure it assumes that most people will have nothing of economic value to contribute to society. They can be fed, housed, and entertained mostly by machines but otherwise left to their own devices.

People will be engaged in supplying interpersonal services that can be provided or which we prefer to be provided only by humans. These include therapy, tutoring, life coaching, and community-building. That is, if we can no longer supply routine physical labour and routine mental labour, we can still supply our humanity. For these kinds of jobs to generate real value, we will need to be much better at being human an area where our education system and scientific research base is notoriously weak.

So, whether we think that the end of traditional work would be a good thing or a bad thing, it seems that we need a radical redirection of education and science to equip individuals to live fulfilling lives or to support an economy based largely on high-value-added interpersonal services. We also need to ensure that the economic gains born of AI-enabled automation will be fairly distributed in society.

One of the greatest obstacles to action is that, at present, there is no consensus on what future we should target, perhaps because there is hardly any conversation about what might be desirable. This lack of vision is a problem because, if high-level machine intelligence does arrive, we could quickly find ourselves overwhelmed by unprecedented technological change and implacable economic forces. This would be a vast opportunity squandered.

For this reason, the workshop attendees and interview participants, from science-fiction writers to economists and AI experts, attempted to articulate positive visions of a future where Artificial Intelligence can do most of what we currently call work.

These scenarios represent possible trajectories for humanity. None of them, though, is unambiguously achievable or desirable. And while there are elements of important agreement and consensus among the visions, there are often revealing clashes, too.

The economic benefits of technological progress are widely shared around the world. The global economy is 10 times larger because AI has massively boosted productivity. Humans can do more and achieve more by sharing this prosperity. This vision could be pursued by adopting various interventions, from introducing a global tax regime to improving insurance against unemployment.

Large companies focus on developing AI that benefits humanity, and they do so without holding excessive economic or political power. This could be pursued by changing corporate ownership structures and updating antitrust policies.

Human creativity and hands-on support give people time to find new roles. People adapt to technological change and find work in newly created professions. Policies would focus on improving educational and retraining opportunities, as well as strengthening social safety nets for those who would otherwise be worse off due to automation.

The World Economic Forums Centre for the Fourth Industrial Revolution, in partnership with the UK government, has developed guidelines for more ethical and efficient government procurement of artificial intelligence (AI) technology. Governments across Europe, Latin America and the Middle East are piloting these guidelines to improve their AI procurement processes.

Our guidelines not only serve as a handy reference tool for governments looking to adopt AI technology, but also set baseline standards for effective, responsible public procurement and deployment of AI standards that can be eventually adopted by industries.

We invite organizations that are interested in the future of AI and machine learning to get involved in this initiative. Read more about our impact.

Society decides against excessive automation. Business leaders, computer scientists, and policymakers choose to develop technologies that increase rather than decrease the demand for workers. Incentives to develop human-centric AI would be strengthened and automation taxed where necessary.

New jobs are more fulfilling than those that came before. Machines handle unsafe and boring tasks, while humans move into more productive, fulfilling, and flexible jobs with greater human interaction. Policies to achieve this include strengthening labour unions and increasing worker involvement on corporate boards.

In a world with less need to work and basic needs met by UBI, well-being increasingly comes from meaningful unpaid activities. People can engage in exploration, self-improvement, volunteering or whatever else they find satisfying. Greater social engagement would be supported.

The intention is that this report starts a broader discussion about what sort of future we want and the challenges that will have to be confronted to achieve it. If technological progress continues its relentless advance, the world will look very different for our children and grandchildren. Far more debate, research, and policy engagement are needed on these questions they are now too important for us to ignore.

Written by

Stuart Russell, Professor of Computer Science and Director of the Center for Human-Compatible AI, University of California, Berkeley

Daniel Susskind, Fellow in Economics, Oxford University, and Visiting Professor, Kings College, London

The views expressed in this article are those of the author alone and not the World Economic Forum.

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6 positive AI visions for the future of work - World Economic Forum